The coal mine underground reservoir is an appropriate solution between coal mining and groundwater resource protection and utilization. By calculating the storage capacity of a groundwater reservoir, the storage coefficient has been proved to be always an empirical value. Based on the mathematical derivation of the vertical fracture area ratio and the horizontal fracture area rate of the collapse zone and the fissure zone in the goaf area of the coal seam, the mathematical models of tem are derived, and the model for calculating the water storage coefficient is derived. The water storage coefficient derived from the theoretical model had more basis and more advanced than the traditional empirical value. By using this method, the practical calculation of No.1 underground reservoir of the DaLliuta Coalmine in Shenhua Shendong, has got a perfect matching with the actual groundwater storage capacity.

The development of an underground gas storage (UGS) project and its subsequent management must ensure technical feasibility, commercial value and long-term efficiency. The UGS industry has borrowed much of its knowledge from other disciplines (primarily oil and gas reservoir engineering), but it has also developed its own technology. This paper provides a methodological approach based on current practices and available methods for designing and safely operating a UGS (including the so-called “delta-pressure” option to enhance UGS performance) and highlights what is special in UGS compared to oil and gas reservoirs.

The collapsible loess will rapidly soften and lose its bearing capacity when soaked in water. Under a mild condition (20°C), the biomimetic inorganic agent, Diammonium phosphate (DAP), reacts with calcite in the collapsible loess, producing a stronger bonding material, hydroxyapatite (HAP), to modify and stabilize the soil. Uniaxial compression, permeability tests and morphological analysis using XRD and SEM/EDX microscopy were carried out to assess the effectiveness of DAP stabilization on the collapsible loess. The results indicated that HAP improved the inter-particle bonding within loess, filled the pores within particles, reduced the permeability, and consequently mitigated collapsibility of loess. The compressive strength of DAP-treated loess increased as DAP concentration increased. Following 28-days curing, the compressive strength of the loess treated with a 3.0 mol/L DAP solution was six times greater than that of the untreated group. DAP's reinforcement effect on loess was superior to that of cement. The compressive strength of DAP-treated loess was about double that of cement-treated loess and the permeability coefficient was reduced by more than 50% at equivalent solid content. Furthermore, DAP generated 68% fewer carbon emissions compared to Portland cement. Considering eco-friendly and sustainable development, DAP offers a more competitive alternative for modification and stabilization of loess.

Reservoirs created by damming rivers significantly modify the environment and problems may arise: the storage of nutrients and organic matter in reservoirs often leads to decreased water quality due to eutrophication. Reservoirs built on lowland rivers are exposed to significant nutrient loads, often leading to eutrophication. In this article, the Sulejów Reservoir, in Central Poland, was the subject of the research, which focused on the use of Sentinel-2 remote sensing data to detect phytoplankton blooms, and on understanding the pattern of wind-driven surface currents using the CCHE2D model (a depth-averaged hydrodynamic model). The calculation of the total phosphorus load has shown that the reservoir mainly acts as nutrient storage. Still, during the low flow and intensive phytoplankton bloom, it can be a source of nutrients. The distribution of phytoplankton bloom on the Sulejów Reservoir was documented using eight Sentinel-2 satellite images from the vegetation season of 2020 and the Normalized Difference Chlorophyll Index (NDCl). Coupling remote sensing data and numerical modelling helps to interpret the hydrodynamic model results and understand nutrients and sediment dynamics within the reservoir. Hydrodynamic modelling combined with remote sensing data can be a valuable tool for selecting appropriate locations for water quality measurements at monitoring stations.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

The paper presents the results of high precision control survey carried out in the underground mining of Oyu Tolgoi project using terrestrial laser scanning technology. The purpose of the measurements is to ensure the heading, total length and volume of the penetration and excavation works are being implementing in accordance with the planned and designed dimensions. We established a network of 18 reference points in the tunnel of the selected underground level which were repeatedly measured 4 times by two round readings of the Trimble S7 tacheometry and processed by using the Trimble Business Center software. All points except the one was within the permissible error. Based on these points the excavation length and volumes were determined using the Trimble SX12 laser scanner. The difference between the planned work quantity provided by the Oyu Tolgoi project and the actual values measured by the laser scanning was calculated using the comparative method. The TLS partial control measurements in the excavations made through the ore bodies revealed the length of 20285.72 m and volume of 441128.80 m3 for underground 7 mine levels while their project values were 16158.26 m length and 422837.50 m3 volume, respectively.

This paper provides a data set collected with an underground shaft mobile mapping system equipped with rotated Velodyne VLP-16, Velodyne Ultra Puck VLP-32c, Livox Tele-15, and IMU Xsens MTi-30. The ground truth data was acquired with a geodetic survey including 15 ground control points and 6 Faro Focus 3D Terrestrial Laser Scanner stations of a total 273,784,932 of 3D measurement points. The aim of the paper is to describe the data set of a mining shaft. Obtained mobile mapping data can be the basis for detailed analyzes of the technical condition of the shaft. This data set provides an end-user case study of realistic applications in mobile mapping technology. It provides ground truth data, mobile mapping data and software tools for manipulation and visualization. The project is released and maintained at https://michalpelka.github.io/mine-mapping-dataset/.

Many parameters and complex boundaries are involved in the spatial arrangement of an under-ground powerhouse for a hydropower station, which requires reference to many relevant cases and specifications. However, in practical applications, retrieving relevant cases or specifications is difficult, and there is a lack of knowledge of cascading logic among design parameters. For this question, a targeted knowledge graph based on knowledge graph management technology is established to support subsequent applications. This paper proposes a new concept of con-structing a knowledge graph for building information modeling (BIM) underground power-houses of hydropower stations. Firstly, the ontology skeleton of hydropower station spatial ar-rangement design, which represents the knowledge organization structure of the knowledge graph, is reconstructed by carefully analyzing the requirements for intelligent modeling of un-derground powerhouses. A large amount of unstructured data is identified based on optical character recognition (OCR) technology and is divided into words to extract correlation knowledge based on THULAC. In the next step, the knowledge triad of the spatial arrangement of the underground powerhouse is extracted based on ChatGPT and stored in a Neo4j knowledge base to build a knowledge graph. Finally, the knowledge graph is serviced to realize the query of knowledge and parameter recommendation to assist the digital intelligent design of spatial arrangement of an underground powerhouse of pumped storage hydropower stations.

UAV has become powerful devices for both practitioners and researchers. In recent years, there has been a substantial growth in the usage of UAV for a wide range of applications in research and engineering. UAV are mostly utilized for image capturing techniques due to their time savings, low cost, minimum field work, and high precision. The purpose of this study is to generate an accurate and reliable 3D modelling process using UAVs photogrammetric technology; hence this study allows the techniques to evaluate the practicability of modelling and mapping inaccessible tunnels using images recorded by UAVs and photogrammetry. As a result, the approach was always employed to depict the true state of the place. This research incorporates three experiments. The first experiment is to build a 3D model using only one-directional light source and evaluate the accuracy of 3D photogrammetric model and conducted at the concrete tunnel. The second one is to build a 3D model of underground sewer tunnel using different light sources one-directional and omni-directional. The last experiment was to build 3D model using an UAV system which is developed based on first and second experiment’s result, evaluate an accuracy of 3D photogrammetric model and conducted at the tunnel named in the research as a “pedestrian tunnel. There is certain limitation in this study such as Adding a payload to a drone changed its weight distribution, which affected its stability. If the payload was not properly balanced, it caused the drone to fly unevenly, making it more difficult to control.

Studies have shown the unconditional danger of biological attacks on underground hydroelectric pumped-storage power stations. A hypothetical list of biological damage to water conduits and dams is determined. Relevant predictions are given, as well as accident events of hydraulic structures are described. A universal scheme for the application of hazard protection measures, which can be comprehensive, has been developed. Praemonitus praemunitus – precautions should be taken.

In order to achieve the target, several activities are being undertaken, including the development of multipurpose reservoir planning for the water supply and sanitation infrastructure, irrigation, and hydropower development for the H project. To undertake this work, the main data given was rainfall data, flow data, catchment area, base population for water supply, and so on. This report presents a specifically preliminary study and design of water supply, irrigation, and hydropower development for the project, which is carried out in accordance with the scope of work given by our professor. The preliminary study and design are therefore to investigate scenarios and alternatives and prepare a document of water supply, irrigation, and hydropower infrastructures for the provision of the assignment. This report, as required in the assignment, contains project background, water sources assessment, selection of suitable hydropower potential, and irrigation sizing, design criteria, descriptions of the proposed scheme, preliminary design of water supply components. The objective of the project is to recommend and design a cost-effective water supply system, irrigation, and hydropower development to supply reliable, sufficient, and safe water from a defined water source to the H project. The specific objectives of the investigation works are: • To assess potential water source alternatives for water supply • Selecting appropriate size for the reservoir which could satisfy all water demand • Assess and select suitable irrigation development and hydropower potential. • Preliminary study and design of all components of the reservoir and appurtenant structures The scope of the project generally focuses on preliminary study and design of water supply, irrigation and hydropower development components from water sources potential and the water balance output.

The development effect of water flooding in ultra-low permeability reservoir was poor due to its poor physical property and high shale content, the experimental study of air flooding which help to complement producing energy was carried out. Based on the Accelerating Rate Calorimeter experimental results, the crude oil of N block in L oilfield can produce low-temperature oxidation reaction, which was the basic condition of air flooding. Three groups of experiment natural cylinder core were designed for oil displacement, water flooding and air flooding were used respectively, and the relationship of differential pressure, oil recovery, injection capacity with injection volume was investigated. It has been showed on the result that the recovery efficiency improved sharply than water flooding, the effect of depressurization and augmented injection was obvious, and the air displacement was validation.

With the pressure of the increasing density of urban areas, some public infrastructures are moving to the underground to free up space above, such as utility lines, rail lines and roads. In the big data era, the three dimensional (3D) data can be beneficial to understand the complex urban area. Comparing to spatial data and information of the above ground, we lack of the precise and detailed information about underground infrastructures, such as the spatial information of underground infrastructure, the ownership of underground objects and the interdependence of infrastructures in the above and below ground. How to map reliable 3D underground utility networks and use it in the land administration? First, to explain the importance of this work and find a possible solution, this paper observes the current issues of the existing underground utility database in Singapore. A framework for utility data governance is proposed to manage the work process from the underground utility data capture to data usage. This is the backbone to support the coordination of different roles in the utility data governance and usage. Then, an initial design of the 3D underground utility data model is introduced to describe the 3D geometric and spatial information about underground utility data and connect it to the cadastral parcel for land administration. In the case study, the newly collected data from mobile Ground Penetrating Radar is integrated with the existing utility data for 3D modelling. It is expected to explore the integration of new collected 3D data, the existing 2D data and cadastral information for land administration of underground utilities.

Reservoir routing has been a routine procedure in hydrology, hydraulics and water management. It is typically based on the mass balance (continuity equation) and a conceptual equation relating storage and outflow. If the latter is linear, then there exists an analytical solution of the resulting differential equation, which can directly be utilized to find the outflow from known inflow, and to obtain macroscopic characteristics of the process, such as response and residence times, and their distribution functions. Here we streamline the reservoir routing framework and extend it to find approximate solutions for nonlinear cases. The proposed framework can also be useful for climatic tasks, such as describing the mass balance of atmospheric carbon dioxide and determining characteristic residence times, which have been an issue of controversy. Application of the theoretical framework results in excellent agreement with real world data. In this manner, we easily quantify the atmospheric carbon exchanges, and obtain reliable and intuitive results, without the need to resort to complex climate models. The mean residence time of atmospheric carbon dioxide turns out to be no more than four years and the response time is smaller than that, thus opposing the much longer mainstream estimates.

Reservoir computing is a machine learning method that uses the response of a dynamical system to a certain input in order to solve a task. As the training scheme only involves optimising the weights of the responses of the dynamical system, this method is particularly suited for hardware implementation. Furthermore, the inherent memory of dynamical systems which are suitable for use as reservoirs mean that this method has the potential to perform well on time series prediction tasks, as well as other tasks with time dependence. However, reservoir computing still requires extensive task dependent parameter optimisation in order to achieve good performance. We demonstrate that by including a time-delayed version of the input for various time series prediction tasks, good performance can be achieved with an unoptimised reservoir. Furthermore, we show that by including the appropriate time-delayed input, one unaltered reservoir can perform well on six different time series prediction tasks at a very low computational expense. Our approach is of particular relevance to hardware implemented reservoirs, as one does not necessarily have access to pertinent optimisation parameters in physical systems but the inclusion of an additional input is generally possible.

According to the structural features, sedimentary evolution, types of sedimentary facies, source rocks features, diagenesis evolution, reservoir features and hydrocarbon formation mechanism, exploration status and hydrocargon resource potential, this article analyzed the major control fac-tors and hydrocarbon distribution rules of the lithologic reservoirs in continental fault basin. The research shows that three major control factors and one coupled factor (fractures act as a tie) in-fluence hydrocarbon formation of lithologic traps in Nantun Formation of Tanan Sag, which in-clude sand body types, effective source rocks and effective reservoirs. With the increase in depth, enough hydrocarbon generate in source rock under thermal evolution. Hydrocarbon generation and expulsion are more intensive when it comes to the depth threshold and critical conditions of hydrocarbon supplying are met. Traps that surrounded or contacted by source rock, or communi-cated by fault are qualified to form reservoirs. As buried depth increases, hydrocarbon genera-tion-expulsion intensity grows and the trap is more petroliferous. Hydrocarbon accumulation and reservoir formation are also controlled by sandbody accumulation conditions. When it meets the critical conditions of hydrocarbon generation and concrete oil and gas are charged in, better phys-ical properties of sandbody always indicate more hydrocarbon accumulation in the trap. Alloca-tion of sand type, effective source rock and effective reservoir is optimized under the effect of fractures, and coupled hydrocarbon reservoir with these three elements.

This paper presents a methodology for determining the sensitivity of the main air flow directions in ventilation subnetworks to changes of aerodynamic resistance and of air density in mine workings. Formulae for determination of the sensitivity of the main subnetwork air flows by establishing the degree of dependency of the air volume stream in a given working on the variations in resistance or air density of other workings of the network have been developed. They have been implemented in the VentGraph mine ventilation network simulator. This software, widely used in Polish collieries provides an extended possibility to predict the process of ventilation, air distribution and, in the case of underground fire, also the spread of combustion gasses. The new method facilitates assessment by mine ventilation services of the stability of ventilation systems in exploitation areas and determine of the sensitivity of the main subnetwork air flow directions to changes of aerodynamic resistance and air density. Recently in some Polish collieries new longwalls are developed in seams located deeper then the bottom of the intake shaft. Such solution is called “exploitation below the level of access” or “sublevel”. The new approach may be applied to such developments to assess the potential of changes of direction and air flow rates. In addition, interpretation of the developed sensitivity indicator is presented. While analyzing air distributions for sublevel exploitation, application of current numerical models for calculations of the distribution results in tangible benefits, such as the evaluation of the safety or risk levels for such exploitation. Application of the VentGraph computer program, and particularly the module POŻAR (fire) with the newly developed options, enables an additional approach to the sensitivity indicator in evaluating air flow safety levels for the risks present during exploitation below the level of the intake shaft. The analyses performed and examples presented enabled useful conclusions in mining practice to be drawn.

Mycobacterium ulcerans is the causative agent of the Buruli ulcer, also known, in Australia, as Daintree ulcer or Bairnsdale ulcer. This destructive skin disease is characterized by extensive and painless necrosis of the skin and soft tissue with the formation of large ulcers, commonly on the leg or arm. To date, 33 countries with tropical, subtropical and temperate climates in Africa, the Americas, Asia and the Western Pacific have reported cases of Buruli Ulcer. The disease is rarely fatal, although it may lead to permanent disability and/ or disfigurement if not treated appropriately or in time. It is the third most common mycobacterial infection in the world after tuberculosis and leprosy. The precise mode of transmission of M. ulcerans is yet to be elucidated. Nevertheless, it is possible that the mode of transmission varies with different geographical areas and epidemiological settings. The knowledge about the possible route of transmission and potential animal reservoir of M. ulcerans is poorly understood and still remains patchy. We conducted a systematic review with selected key words on PubMed and INFORMIT databases to aggregate available published data on animal reservoirs of M. ulcerans. After certain inclusion and exclusion criteria, a total of 17 studies were included in the review. A variety of animals, e.g rodents, shrews, possums (ringtail and brush tail), horses, dogs, alpacas, koalas and Indian flap-shelled turtles have been recorded as being infected with M. ulcerans around the world. The majority of studies included in this review identified animal reservoirs, either aquatic or terrestrial, as predisposing for the emergence and reemergence of M. ulcerans infection. Taken together, the selected studies in this systematic review and discussed so far, it is clear that exotic wildlife, aquatic animals and native mammals play a significant role as reservoirs for M. ulcerans.

An analysis of workplace accidents in the mining sector has been done using the database from the Spanish administration between the period 2005-2015 and applying data mining techniques. Data has been processed by means of the software Weka. Two scenarios were chosen regarding the accidents database, surface and underground mining. The most important variables involved in occupation accidents and their association rules have been determined. These rules are formed by several predictor variables that cause an accident, defining its characteristics and context. This study exposes the 20 most important association rules of the sector, either surface or underground mining, based on statistical confidence levels of each rule obtained by Weka. The outcomes display the most typical immediate causes with the percentage of accident basis of each association rule. The most typical immediate cause is body movement with physical effort or overexertion and type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident change in both scenarios. Data mining techniques have been proved as a very powerful tool to find out the root of the accidents, apply corrective measures and verify their effectiveness, either for public or private companies.

Keywords: underground engineering; numerical simulation; excavation length effect, major principal stress; displacement; damage initiation; CPU time

Enhanced oil recovery (EOR) refers to the various techniques used to increase the amount of crude oil that can be extracted from an oil field. These techniques are used after the primary and secondary recovery methods have been depleted. There are three main types of EOR: thermal, gas injection, and chemical. EOR techniques can be expensive and complex, but they can help to recover additional oil that would otherwise be left in the reservoir. EOR can also extend the life of an oil field and increase the overall production from a given field. The parameters affecting oil recovery are a major concern in EOR systems, and these parameters need more consideration with the factors affecting them. In this study, the influence of permeability variations on fluid flow in a sandstone reservoir was explored, as well as an up-to-date description of three states of EOR with thorough explanations of the methods utilized and the mechanisms driving their oil recovery application. The difficulties encountered in the use of the different standard EOR Mechanisms were noted, and solutions to these difficulties were proposed. Furthermore, the contemporary trend of adding nanotechnology and its synergistic effects on the stability and efficiency of traditional chemicals for EOR were examined and analysed. Finally, laboratory findings and field initiatives were discussed. The review went into detail about the transport of nanoparticles across reservoirs, as well as the evaluation of EOR, mobility ratio, and fluid displacement efficiency. This review provides thorough information on the uses of improved oil recovery mechanisms for sustainable energy production.

A study of the water quality of the Adolfo López Mateos Reservoir (ALMD) was developed through different indicators from a spatial and seasonal perspective. Variables related to the general characteristics of water quality, trophic level and ecological risk were assessed through the water Quality Index (WQI_NSF-BROWN), Trophic State Index (TSI_CARLSON) and the Ecological Risk Index (RI_HAKANSON). Using data from physical, chemical and biological parameters obtained from four sampling points in the ALMD, the water quality was assessed in each model used. The results indicated that the reservoir presents a water quality classified as “medium” (WQI_NSF-BROWN = 70), where significant variations in the concentrations of some parameters are observed. The reservoir showed a general trophic state classified as “Mesotrophic” (TSI_{GENERAL-AVERAGE} = 43.04). The ecological risk analysis achieved the best classification of the methodology, discarding contamination by heavy metals in surface waters. Through this type of applied methodologies will help as decision making tools in the dam, as well as for application in other dams in the region.

Due to production space and operating environment requirements, mine production equipment often breaks down, which seriously affects the mine’s production schedule. To ensure the smooth completion of the haulage operation plan under abnormal conditions, a model of the haulage equipment rescheduling plan based on the random simulation of equipment breakdowns is established in this paper. The model aims to accomplish both the maximum completion rate of the original mining plan and the minimum fluctuation of the ore grade during the rescheduling period. This model is optimized by improving the wolf colony algorithm and changing the location update formula of the individuals in the wolf colony. Then, the optimal model solution can be used to optimize the rescheduling of the haulage plan by considering equipment breakdowns. The application of the proposed method in an underground mine revealed that the completion rate of the mine’s daily mining plan reached 83.40% without increasing the number of the equipment, while and the ore quality was stable. Moreover, the improved optimization algorithm converged fast and was characterized by high robustness.

The management and proper use of the Urban Public Transport Systems (UPTS) constitutes a critical field that has not been investigated in accordance to its relevance and urgent idiosyncrasy within smart cities realm. Swarm Intelligence is a very promising paradigm to deal with such complex and dynamic systems. It presents robust, scalable and self-organized behaviour to deal with dynamic and fast changing systems. The intelligence of cities can be modelled as a swarm of digital telecommunication networks (the nerves), ubiquitously embedded intelligence, sensors and tags, and software. In this paper, a new approach based on the use of the Natural Computing paradigm and Collective Computation is shown, more concretely taking advantage of an Ant Colony Optimization algorithm variation and Fireworks algorithms in order to build a system that makes the complete control of the UPTS a tangible reality.

The deformation of underground gateroads tends to be asymmetric and complex. Traditional instrumentation fails to accurately and conveniently monitor the full cross-sectional deformation of underground gateroads. Here, a full cross-sectional laser scanner was developed together with a visualization software package. The developed system used polar coordinate measuring method and the full cross-sectional measurement was realized by 360° rotation of laser sensor driven by an electrical motor. Later on, the potential impact of gateroad wall flatness, roughness and geometrical profile as well as coal dust environment on the performance of the developed laser scanner were evaluated. The studies show that a high-level flatness is favorable in application of the developed full cross-sectional deformation monitoring system. For a smooth surface of gateroad, the sensor cannot receive reflected light when the incidence angle of laser beam is large, causing data loss. Conversely, the roughness surface shows its priority as the diffuse reflection light can be received by the sensor. With regards to the coal dust in measurement environment, the fine particles of floating coal dust in the air can lead to the loss of measurement data to some certain due to scattering of laser beam.

Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle’s range of functions and considerably reducing the distance the vehicle can travel on a single charge. Next-generation onboard AI systems need an even higher power since they collect and process even larger amounts of data in real time. This problem cannot be solved using the traditional computing devices since they become more and more power-consuming. In this review article, we discuss the perspectives of development of onboard neuromorphic computers that mimic the operation of a biological brain using nonlinear-dynamical properties of natural physical environments surrounding autonomous vehicles. Previous research also demonstrated that quantum neuromorphic processors (QNPs) can conduct computations with the efficiency of a standard computer while consuming less than 1% of the onboard battery power. Since QNPs is a semi-classical technology, their technical simplicity and low, compared with quantum computers, cost make them ideally suitable for application in autonomous AI system. Providing a perspective view on the future progress in unconventional physical reservoir computing and surveying the outcomes of more than 200 interdisciplinary research works, this article will be of interest to a broad readership, including both students and experts in the fields of physics, engineering, quantum technologies and computing.

Designing high-voltage underground transmission lines poses complex challenges in heat management, trench optimization, and determining cable ampacity. This article introduces an innovative proposal that focuses on adjusting the dimensions of the thermal backfill as a primary strategy to enhance ampacity compared to the traditional approach of increasing the cross-sectional area of the cable core. The methodology employs a particle swarm optimization (PSO) technique with adaptive penalization, restart strategies, and parameter self-adaptation implemented in MATLAB. The objective of this approach is to provide more efficient solutions than traditional MATLAB PSO, demonstrating improved convergence and more accurate results with a success probability of 66.1\%. Although traditional PSO is 81\% faster, the proposed PSO stands out for its precision. Additionally, the incorporation of thermal backfill results in an 18.45\% increase in cable ampacity. Variations in the thermal resistivity of the soil, backfill, and ambient temperature are highlighted as sensitive factors affecting ampacity and backfill dimensions. This method is presented as a crucial tool in the early stages of the project and underground installation in operation with maximum ampacity, contributing to the continuous improvement of energy efficiency.

The purpose of this study was to recommend to the government about the appropriate land use based on geoelectric and hydrochemical works. The results were supposed to be used as models for effective land use. During the study, a groundwater survey using a geoelectrical method was conducted and was used to map an aquifer flow. In general, Solok groundwater mapping was meant to provide information necessary to optimize follow-up activities for the use of clean water. It was also intended to minimize the negative impacts of exploitation and utilization of groundwater. This research aimed to provide information on groundwater conditions in Solok. It focused on the survey of groundwater sources, the inversion of measurement data on Sclumberger electrode configuration geoelectric in thirteen districts, and chemical analysis of pH, Fe, Nitrite, and DHL. The results show there was a great potential for groundwater-unconfined aquifers.

This study examines geothermal energy extraction potential from the basement rock within the Denver-Julesburg (DJ) Basin, focusing on flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-Shaped, V-Shaped, Inclined V-Shaped, and Pipe-in-Pipe configurations against Enhanced Geothermal Systems (EGS) setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. Results suggest that while closed-loop systems offer moderate temperature increases, EGS configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings like the DJ Basin. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations.

In 2021 the total world cement production was estimated at 4.1 billion tonnes and the annual CO2 emissions from cement plants reached almost 2.8 billion metric tonnes. In the last years many ef-forts have been made for manufacturing low-CO2 cements. In this regard, a great attention has been paid towards calcium sulfoaluminate (CSA) cements for both their peculiar technical prop-erties and the environmentally friendly features mainly related to their manufacturing process. Moreover, the use of blended cements composed by CSA binders and supplementary cementitious materials (SCMs) could represents a powerful tool for both reducing the CO2 footprint and pro-ducing more durable environmentally friendly materials. In this paper, the possibility of using reservoir sediments (RS), calcined at 830°C, as SCMs in blended-CSA cements was investigated. Four binders were submitted to hydration and physico-mechanical tests for curing periods com-prised in the interval 4 hours-56 days. X-ray fluorescence, X-ray diffraction and differential thermal–thermogravimetric analyses were employed as main characterization techniques. It was found that thermally treated RS are very interesting inasmuch as their utilization allows a CSA clinker dilution, thus implying both a decrease of CO2 emissions and a reduction of costs related to CSA cement production.

Dams design and their operation cause strong environmental alteration and therefore a long-term debate is ongoing for the scale of these projects. At the same time, the concept of Environmental Flow Assessment (EFA) is a crucial element of modified ecosystems featuring large infrastructure such as dams and reservoirs for mitigating potential environmental degradation while they operate. Nowadays, integrated scientific frameworks are required to quantify the risks caused by large infrastructure. Through the use of stochastic analysis, it is possible to quantify these uncertainties, and present a solution that incorporates long-term persistence and environmental sustainability into a balanced reservoir simulation model. In this work, an attempt is made to determine a benchmark reservoir size incorporating hydrological and ecological criteria though stochastic analysis. The primary goal is to ensure the best possible conditions for the ecosystem, and then secondarily to allow a steady supply of water for other uses. Using a synthetic timeseries based on historical inputs, it is possible to determine and preserve essential statistical characteristics of a river’s streamflow, and use these to detect the optimal reservoir capacity that maximizes environmental and local water demand reliability.

As a major coal country, China faces the issue of significant gas emissions during the coal mining process. This study aims to improve the utilization efficiency of mine gas, reduce greenhouse gas emissions, and promote the low-carbon and green transformation of the coal industry. A 10kW gas regenerative thermal oxidation (RTO) experimental system was constructed. The effects of initial methane concentration, low-temperature flue gas proportion, and operating load on combustion temperature, methane oxidation rate, high-temperature flue gas energy, and system thermal efficiency were studied. The results show that when the combustion temperature is below 600°C, the CH4 combustion reaction cannot proceed effectively, and the system temperature continuously decreases and cannot be maintained stable. The experiment determines the stable operating methane concentration range of RTO. In this experimental system, the lower limit of the initial methane concentration is 0.28%, corresponding to an 86% methane oxidation rate. As the initial methane concentration decreases, the combustion temperature also decreases, and the methane oxidation rate follows suit. The higher the low-temperature flue gas proportion, the higher the combustion temperature, and the system thermal efficiency and output heat decrease with the increase of the low-temperature flue gas proportion. This experiment explores multiple factors affecting regenerative thermal oxidation, providing an basis for ensuring the safe and stable operation of the system and optimization. Improving the thermal insulation and heat exchange performance of the storage body can expand the lower limit of the initial methane concentration, thereby increasing the stability and thermal efficiency of the system.

The development of subterranean non-motorized traffic infrastructure, commonly referred to as the underground pedestrian system (UPS), has become increasingly necessary in densely populated megacities worldwide as a means of advancing the Sustainable Development Goal 11, which aims to promote sustainable cities and communities. To improve the overall spatial performance, it is imperative to decipher the fundamental formation mechanism of sustainable underground pedestrian systems (SUPS) that is simultaneously influenced by spatial morphology and pedestrian behaviors. Thereby, two representative case studies, namely Wujiaochang UPS and Loushanguanlu UPS located in Shanghai, were selected for an in-depth investigation. This study employed correlation and regression analysis to examine the impact of spatial configuration variables and spatial attribute factors on pedestrian flow distributions in distinct SUPSs. The findings indicate that the variables of Betweenness, as measured by both Euclidean and Angular metrics, along with the presence of metro station locations and commercial space connected by UPS, are the three most significant factors influencing pedestrian behaviors in both scenarios. The disclosure has been made that Wujiaochang UPS is seamlessly integrated into a comprehensive three-dimensional pedestrian network both above and below ground. On the other hand, it appears that Loushanguanlu UPS exhibits a greater degree of self-sufficiency as an underground system. This study aims to elucidate the mechanism underlying the development of SUPSs, thus offering effective guidance for the implementation of three-dimensional walking systems in cities that prioritize sustainability.

Microgrids can be used for securing power supply during network outages. Underground cabling of distribution networks is another effective, but conventional and expensive alternative to enhance reliability of power supply. This paper presents firstly an analysis method for the determination of microgrid power supply adequacy during islanded operation, and secondly, a comparison method for overall cost calculation of microgrids vs. underground cabling. The microgrid power adequacy during a rather long network outage is required in order to indicate high level of reliability of supply. The overall cost calculations consider the economic benefits and costs incurred combined for both the distribution network company and the consumer. Whereas the microgrid setup determines the islanded operation power adequacy and thus the reliability of supply, the economic feasibility results from the normal operations and services. The methods are illustrated by two typical, and even critical, case studies in rural distribution networks: an electric-heated detached house and a dairy farm. These case studies show that even in case of a single consumer, a microgrid option could be more economical than network renovation by underground cabling of a branch in order to increase reliability.

Deterministic simulations using the SWAN model were conducted along a stretch of the Tietê-Paraná waterway in the Ilha Solteira dam reservoir, São Paulo, Brazil, to assess the water waves generated by winds. Simultaneously employs a probabilistic metamodeling approach (PCE) and Sobol indices, to quantify uncertainty of the five involved physical parameters (wind velocity and direction, bottom friction (JONSWAP), whitecapping and depth-induced breaking index). In the deterministic part, Janssen’s formulation yielded the most successful and accurate estimations of wave heights. Probabilistic analysis underscored the importance of wind data and the whitecapping parameter in model calibration, with a significant influence of wind speed indicated by Sobol indices. The results not only refined the model calibration process, but also allowed the creation of contour maps for wave height and period that offer practical pre-project applications. This work advances understanding of wind wave hydrodynamics deterministically and probabilistically, with good concordance and performance indices compared to field data, despite being scarce.

In this study, a new empirical equation was established to predict the sedimentation volume resulting from the construction of a multipurpose weir or low-head dam. The study employed a one-dimensional numerical model (STAFF) to investigate the key parameters affecting sedimentation volume. Short-term predictions were conducted through laboratory experiments with movable bed, and the results indicated that dimensionless unit stream power and the Shields parameter exhibited the most significant correlation with dimensionless deposition volume. Using a multiple regression approach, an empirical equation was formulated and validated for predicting sedimentation in the upstream reservoir of the weir.

Wastes from social economic activities had great impact on water quality thereby limiting water usability for domestic purposes. Sewages discharge from people activities, usually consist of undesirable concentrations of soluble chemicals that infiltrate into the surrounding surface and underground water, and then constitute health risk to the populace. In order to investigate the concentration characteristics and health risk for the local residents in Nandong Underground River Watershed (NURW), eleven common heavy metals in the water body analysis were conducted. Health risk assessment (HRA) was taken to analyze eleven heavy metals of 84 water samples from surface and underground waters in NURW: 36 samples underground water and 48 samples surface water. Our results showed that the heavy metals concentration order is that of Fe > Al > Mn > Zn > As > Cd > Pb > Cr > Ni > Cu > Hg. Correlation analysis indicates that these eleven metal elements have certain similarity on material source and migration transformation. The health risks for local residents exposed to metal elements in the water of NURW mainly from carcinogenic risk (10−6～10−4 a−1) through drinking way, and the health risk of heavy metals exposed to children through drinking way was much higher than adults. The maximum exposing health risks of Cr in both underground and surface water were higher than the recommendation standard (5.0×10-5 a-1) from ICRP, and all the values over the standard (5.0×10-6 a-1) recommended by the Swedish Environmental Protection Agency and the Dutch Ministry of Construction and Environment and the British Royal Society. The results of health risk assessment shows that Cr in the water of NURW was the mainly source of carcinogenic risk for the local residents, following by Cd and As. Consequently, it is necessary to control the three carcinogenic metals when the water was used as drinking water source.

Focusing geophysics to improve recovery factor of hydrocarbon reservoirs adds value and contributes toward ZERO carbon footprint by increasing the recovery factor by of 30-40 % and thus reducing the cost/carbon emission per produced barrel. Thus, the Enhanced Oil Recovery (EOR) market is expected to grow more than 3.5% annually. This will be even more fueled by the Green-House-Gas (GHG) reduction and subsequent CO2 injection into the reservoirs as they are being produced. Presently, geophysics only ac-counts for a small percentage of this market, thus its growth is inevitable since more deterministic observation lead higher operating efficiency. Imaging the fluids (hydro-carbon, water, and CO2) is a key component to optimized production and injection. We designed a novel electromagnetic (EM) acquisition system that combines mul-ti-physics fluid imaging and acquires surface and borehole data with high fidelity. Borehole calibration is needed to upscale reservoir data and parameters to measurement scale. Multiple electromagnetic methods are used as well as microseismics in one layout for Exploration and Production (E & P) problems. Multi-components in electromagnetics allows resolving oil and water-bearing zones equally well while achieving the best ac-curacy suitable for repeat measurements. Because sedimentary basins are intrinsically anisotropic, considering 3-dimensional anisotropy is essential from measurement and 3D modeling viewpoint. Thus, the results have the better subsurface images. Here, we combine hardware design, methodology, 3D modeling, processing, and interpretations into an integrated technology and demonstrate the success with verifiable case histories.

The Brazilian water legislation advocates that some uses have priority over others, but this aspect has never been clearly addressed, generating conflicts. Water authorities usually refer to hydrological models to justify their decisions on water allocation. However, a significant group of stakeholders does not feel qualified to discuss these models and is, therefore, excluded from the decision process. We hereby propose a hydrologically robust method to correlate water uses with their respective reservoir alert volumes, which should empower the less formally educated stakeholders. The method consists of: (i) generating the water discharge versus reliability curve, using a stochastic approach; (ii) generating the withdrawal discharge versus alert volume family of curves, using a water-balance approach; (iii) calibrating the key parameter T using field data; and (iv) associating each water use with its alert volume. We have applied the method to four of the largest reservoirs (2.10³ - 2.10² hm³) in the semi-arid Ceará State. The results indicate that low-priority water uses should be rationalized when the reservoir volume is below 20%; whereas uses with very high priority should start rationalization when it is below 11%. These hydrological guidelines should help enhance water governance among non-specialist stakeholders in water-scarce and reservoir-dependent regions.

Deep underground laboratories offer advantages for conducting high-precision observations of weak geophysical signals, benefitting from a low background noise level. It is both valuable and feasible to enhance strong, noisy ground electromagnetic (EM) field data using synchronously recorded underground EM signals, which typically exhibit a high signal-to-noise ratio. In this study, we propose an EM field reconstruction method employing a Long Short-Term Memory (LSTM) recurrent neural network with referenced deep underground EM observations. Initially, a deep learning model was developed to capture the time-varying features of underground multi-component EM fields using the LSTM recurrent neural network. Subsequently, this model was applied to process synchronously observed strong, noisy data from other conventional observation systems, such as those at surface, to achieve noise suppression through signal reconstructions. Both theoretical analysis and practical observational data suggest that the proposed method effectively suppresses noise and reconstructs clean EM signals. This method is efficient and time-saving, representing an effective approach to fully utilizing the advantages of deep underground observation data. Furthermore, this method could be extended to the processing and analysis of other geophysical data.

The shear factor of ore drawing is one of the important factors affecting the formation of underground debris flow, and it has an important contribution to the formation of underground debris flow. The purpose of this paper is to study the effect of mining shear factor on underground debris flow in natural caving method. Based on the research background of the underground debris flow in Plan copper mine, this paper analyzes the characteristics of the slurry material structure of the underground debris flow, the influence of drawing shear factor on formation mechanism of underground debris flow is analyzed. The results show that the slurry of the underground debris flow in Plan mine is not only a pseudoplastic fluid but also a thixotropic fluid. It is indicated that once there is shearing force in drawing, it will deform, and its viscosity will decrease with the increase of shear rate and time. It is considered that the shear force produced by the flow of ore particles first produces shear action on the paste in the shear boundary region of ore drawing, it is reduced in viscosity and increased in fluidity, so that its “Activation” and then become a flowable paste, along with the bulk ore flow through the mouth. The continuous ore drawing process will continuously shear the new moraine slurry in the ore drawing channel and continuously “Activate” the moraine slurry in the ore drawing channel, finally, a certain scale and destructive down-hole debris flow accident. This paper is the first to study the effect of ore drawing shear factor on the formation mechanism of underground debris flow. It not only broadens the research field of debris flow, but also fills up the deficiency of systematic research on underground debris flow, and provides theoretical guidance for the prevention and control of underground debris flow.

The availability rating of any system is the probability that it will be able to operate for a given time in other words, to restore the system in the case of a system failure, or during the failure it is a measure of the availability index of resource system. We aimed to complete the study for the reasons as below. The rating and upgrading of underground mine radio communication system availability is to ensure operation reliability of the underground mine and to establish reliable radio communication system for miner’s safety during failure. Therefore, our study is contributed to reveal system availability rating of single resource (with two parallel connections) system and two resources (with three parallel connections) system. The study is related to not only practical contribution but also reliability engineering theory. To achieve this result, we have used Exponential, Weibull, and Poisson distributions. The readiness rating of single resource (with two parallel connections) and two resources (with three parallel connections) systems were calculated using Matlab software and the simulation results were introduced. This result confirms that any system has a resource system, which increases its readiness rating. The study was in examples of single resource radio communication system on the two shafts of the underground mine and two resource radio communication system for three shafts. During the initial system reliability enhancement study, the readiness of the dual resource system was assessed. The rating shows a 99 percent result, which is very meaningless for systems with more than two n-resources and we have revealed that it can show more than 100 percent result. In the process of the study on system reliability improvement the rating availability of system which has two resources was 99 % result. It is very meaningless for systems with more than two n-resources or more than 100% result.

Reservoir computing (RC) systems can efficiently forecast chaotic time series using nonlinear dynamical properties of an artificial neural network of random connections. The versatility of RC systems has motivated further research on both hardware counterparts of traditional RC algorithms and more efficient RC-like schemes. Inspired by the nonlinear processes in a living biological brain and using solitary waves excited on the surface of a flowing liquid film, in this paper we experimentally validate a physical RC system that substitutes the effect of randomness for a nonlinear transformation of input data. Carrying out all operations using a microcontroller with a minimal computational power, we demonstrate that the so-designed RC system serves as a technically simple hardware counterpart to the `next-generation’ improvement of the traditional RC algorithm.

The physical properties of coal reservoirs are the main restrictions to exploration and development of CBM. The study of the physical characteristics of coal reservoirs and their controlling factors is of great significance to the safe and efficient development and utilization of CBM resources in the mining area. The Pingdingshan No. 10 coal mine was chosen for this study because of its better gas production effect at the test wells. The reservoir properties of the main coal seams of the No. 10 coal mine were tested and analyzed to comprehensively evaluate the reservoir properties. The results indicate that (1) The gas content and methane purity of the No. 4 coal seam are significantly higher than the No. 2 seam, and therefore they have better development potential than the No. 2 seam; (2) The average adsorption time of the No. 2 coal seam is less than that of the No. 4 seam, making it easier to reach the peak production capacity of CBM wells in the short term, but is not conducive to long-term stable production of CBM. The Langmuir volume of the No. 2 coal seam samples was significantly greater than for the No. 4 coal seam; however, the No. 4 coal seam contains about three times the amount of gas in the No. 2 seam; (3) All three coal seams have high porosity, which is favorable for large amounts of CBM adsorption and storage. Micropores predominate, transitional pores are less frequent, and a few mesopores occur; macropores are the least common. Samples from the No. 4 seam contained the highest proportion of micropores; (4) Organic pores were common in the all coal samples, with pore diameters not more than 30 µm, mainly concentrated between 50.5 and 1000 nm. Microfractures with aperture less than 70 nm were relatively frequent, mainly in the 50–65 nm range. A large number of the nanoscale microfractures were curved or jagged; (5) Fractures in the No. 2 and No. 4 coal seam samples with widths of 50 nm to 20 µm were more developed, and many were filled with kaolinite, quartz and other minerals; (6) The samples contained mostly layered silicate minerals (kaolinite), with hard granular minerals (quartz) next, and a very small quantity of iron-type minerals such as siderite and pyrite in dendritic form. The results of this study can provide a reference basis for the large-scale development and utilization of subsequent CBM wells.

Aquathermolysis is a promising method to upgrade heavy oil in reservoir conditions. However, application of catalysts can significantly promote transformation of the heavy fragments (resins and asphaltenes) and heteroatom-containing compounds of crude oil mixture into low-molecular-weight hydrocarbons. In this paper, the comparison study of the catalytic performance of the water-soluble metal salts such as NiSO4 and FeSO4 on the aquathermolytic upgrading of heavy oil samples produced from Ashal’cha reservoir was carried out at a temperature of 300 °C for 24 hours. Iron nanoparticles contributed to the highest viscosity reduction degree - 60% in contrast to the viscosity of the native crude oil sample. The viscosity alteration is reasoned by the changes in the group composition of heavy oil after catalytic (FeSO4) aquathermolysis, where the content of resins and asphaltenes were reduced by 17% and 7%, respectively. Moreover, the aquathermolytic upgrading of heavy oil in the presence of FeSO4 led to an increase in the yield of gasoline fraction by 13% and diesel fraction by 53%. The H/C ratio, which represents the hydrogenation of crude oil, increased from 1.52 (before catalytic upgrading) to 1.99 (after catalytic upgrading). The results of Chromatomass (GC-MS) and Fourier-infrared (FT-IR) spectroscopies confirmed the intensification of destructive hydrogenation of resins and asphaltenes in the presence of the water-soluble catalysts. According to XRD and SEM-EDX results, the metal salts are thermally decomposed during the aquathermolysis process into the oxides of corresponding metals and particularly sulfided by the sulfur-containing aquathermolysis products.

Reservoir computers (RCs) are a biology inspired computational framework for signal processing typically implemented using recurrent neural networks. Recent work has shown that Boolean networks (BN) can also be used as reservoirs. We analyze the performance of BN RCs, measuring their flexibility and identifying factors that determine effective approximation of Boolean functions that are applied in a sliding-window fashion over a binary signal, either non-recursively or recursively. We train and test BN RCs of different sizes, signal connectivity, and in-degree to approximate 3-bit, 5-bit and 3-bit recursive binary functions. We analyze how BN RC parameters and function average sensitivity, a measure of function smoothness, affect approximation accuracy as well as the spread of accuracies for a single reservoir. We found that approximation accuracy and reservoir flexibility are highly dependent on RC parameters. Overall, our results indicate that not all reservoirs are equally flexible and RC instantiation and training can be more efficient if this is taken into account. The optimum range of RC parameters opens up an angle of exploration for understanding how biological systems might be tuned to balance system restraints with processing capacity.

Uncertainties in initial water saturation and early water breakthroughs of un-known sources and paths, which occurred in the low resistivity Lower Haushi sand-stone (LHS) reservoir at the beginning of oil production, imply that the bypassed oil can yet remain in the reservoir. In addition, the upper part of LHS is a tight oil reser-voir, which can still contain a significant amount of unrecovered oil. This opens the opportunity to produce the remaining oil instead of abandoning this reservoir. Low resistivity can exaggerate water saturation, leading to misinterpretation and premature water flooding due to inadequate oil-water contrast. Our analysis revealed a correlation between low resistivity and robust porous network connectivity, along-side elevated formation water salinity in highly porous layers. In regions of high po-rosity, sufficient oil-water contrast facilitates precise water saturation determination, affirming oil presence in all wells. However, within tight oil zones, near-complete wa-ter saturation contradicts actual oil presence. Factors contributing to saturation un-certainty and water breakthroughs were reassessed. Utilizing a 1:1 verti-cal-to-horizontal permeability ratio derived from core data enhanced simulation alignment with water production rates. Investigation into the impact of relative per-meabilities on water production was conducted. Water saturation maps were gener-ated to pinpoint remaining oil reserves. Depletion around wells is evident in lower po-rous regions, while oil persists across the entire tight reservoir, notably in two unex-plored sections.

Recurrent neural networks (RNNs) transmit information over time through recurrent connections. In contrast, biological neural networks use many other temporal processing mechanisms. One of these mechanisms is the inter-neuron delays caused by varying axon properties. Recently, this feature was implemented in echo state networks (ESNs), a type of RNN, by assigning spatial locations to neurons and introducing distance-dependent inter-neuron delays. These delays were shown to significantly improve ESN task performance. However, thus far it is still unclear why distance-based delay networks (DDNs) perform bettern than ESNs. In this paper, we show that by optimizing inter-node delays, the memory capacity of the network matches the memory requirements of the task. As such, networks concentrate their memory capabilities to the points in the past which contain the most information for the task at hand. Moreover, we show that DDNs have more total linear memory capacity, with the same amount of non-linear processing power.

Aquatic ecosystems are often subject to degradation due to various environmental stressors. The accumulation of an organic sediment layer causes shallowing, algal blooms, and hypertrophy in water reservoirs. The processes of overgrowth and shallowing lead to a reduction in the ecosystem services provided by the reservoir as well as may potentially cause the disappearance of the water body. To address these challenges and restore the ecological balance of water reservoirs, effective and sustainable revitalisation methods are essential. In recent years, biotechnological approaches, particularly utilizing microbiological interventions, have emerged as promising strategies for water reservoir revitalization. Microorganisms, with their remarkable ability to degrade pollutants and enhance nutrient cycling, offer great potential in remediating environmental issues in a natural and eco-friendly manner. The article presents the results of a study of 34 Polish reservoirs subjected to reclamation with microbial biopreparations from 2014 to 2023. The results of changes in bottom sediment reduction, water transparency, dissolved oxygen concentration, and water turbidity are presented. Reduction of and morphological changes in the fraction of soft organic sediments, an improvement in the oxygen profile of the bottom and surface water layers, and an increase of water transparency were observed after the reclamation with the use of biopreparations.

There is currently no cure for HIV infection although adherence to effective antiretroviral therapy (ART) suppresses replication of the virus in blood, increases CD4+ T-cell counts, reverses immunodeficiency, and increases life expectancy. Despite these substantial advances, ART is a lifelong treatment for people with HIV (PWH) and upon cessation or interruption, the virus quickly rebounds in plasma and anatomic sites including the central nervous system (CNS), resulting in disease progression. With recent advances in quantifying viral burden, detection of genetically intact viral genomes, and isolation of replication-competent virus from brain tissues of PWH receiving ART, it has become apparent that the CNS viral reservoir (largely comprised of macrophage type cells) poses a substantial challenge for HIV cure strategies. Other obstacles impacting the cure of HIV include ageing populations, substance use, comorbidities, limited antiretroviral drug efficacy in CNS cells and ART-associated neurotoxicity. Herein, we review recent findings including studies of the proviral integration sites, reservoir decay rates, and new treatment/prevention strategies in the context of the CNS, together with highlighting the next steps for investigations of the CNS as a viral reservoir.

In recent years, Machine Learning (ML) has become a buzzword in the petroleum industry with numerous applications which guide engineers in better decision-making. The most powerful tool that most production development decisions rely on is reservoir simulation with applications in numerous modeling procedures, such as individual simulation runs, history matching and production forecast and optimization. However, all these applications lead to considerable computational time and computer resources associated costs, rendering reservoir simulators as not fast and robust enough, thus introducing the need for more time-efficient and smart tools, like ML models which are able to adapt and provide fast and competent results that mimic the simulator’s performance within an acceptable error margin. The first part of the present study (Part I) offers a detailed review of ML techniques in the petroleum industry, specifically in subsurface reservoir simulation, for the cases of individual simulation runs and history matching, whereas the ML-based Production Forecast Optimization applications will be presented in Part II. This review can assist engineers as a complete source for applied ML techniques since, with the generation of large-scale data in everyday activities, ML is becoming a necessity for future and more efficient applications.

Hydraulic fracturing for oil-gas and geothermal reservoir stimulation is closely related to the generation and propagation of Mode I crack. Nonlinear deformation due to rock heterogeneity occurs at such crack tip, which causes the fracture process zone (FPZ) to form before the crack propagates unsteadily. However, the relationship between the FPZ characteristics and rock heterogeneity still remain elusive. We used three rock types common in reservoir for experimental investigation, and each of them includes two subtypes with different heterogeneity due to grain size or microstructural characteristics. Drawing on the experiment results, we calculated the FPZ size in each cracked chevron notched Brazilian disk, and we reproduced the formation process of the FPZ in marble by discrete element method. We showed that strong heterogeneity is favorable to large FPZ size, can enhance the ability of crack generation and complicate crack morphology. Coupling the Weibull distribution with fracture mechanics, the dependence of the FPZ size on heterogeneity degree can be theoretically explained, which suggests that inherent heterogeneity of rocks set physical foundation for formation of FPZ. These findings can improve our recognition to formation mechanism of the Mode I crack and provide useful guidelines for evaluating reservoir fracability.

Electro-mechanical braking(EMB) which represents development direction of autonomous and intelligent braking plays very useful role on enhancing the braking response performance and intelligence level for mine underground electric trackless rubber-tired vehicle (ETRV). However,there is no Electro-Mechanical Brake system applied practically in coal mine UTRV until now.The accurate control of braking clamping force can determine the length and precision of braking distance of mine ETRV.In addition,because of poor working conditions in underground coal mine tunnel ,braking clamping force sensor may be easy to occur failure,which may cause vital accident.Therefore,A cascaded three-closed-loop EMB system with a positive clamping force sensor or force estimator built for ETRV is established to achieve autonomous elimination and reset of braking clearance and reliable braking force tracking ability via utilizing the electro motor rotor angle displacement and hysteresis effect of mechanical components in this EMB.The results of simulation and experiment indicate that clamping force response is faster than traditional hydraulic disk braking system and proposed force estimator presents good fault-tolerant ability when sensor is fault.This EMB can replace the current hydraulic brake system to enhance automation level of braking control for ETRVs and braking force response performance, reduce oil pollution and cost of maintenance, which is also key technology support for really precise motion control of mine autonomous driving vehicles.

The quality of underground space information has become a major problem that endangers the safety of underground spaces. Currently, the main methods for the high-precision and long-distance transmission of detection information are radar and optical methods. However, in practical applications, we found that the radar method has the shortcomings of large energy loss and poor anti-jamming ability, which limit the accuracy of information data transmission and distance. The optical method has the shortcomings that the weather has a great impact on its accuracy and can only be applied to static objects above ground; therefore, it has the limitation of application objects and use environment. More importantly, the current high-precision information remote detection methods are limited to the detection of overground space objects and are not applicable to the detection of various information data in underground space. In this study, we analyze the spectral properties of the fractional differential operator and find that it is suitable for studying non-linear, non-causal, and non-stationary signals. The theory of fractional calculus is applied to the field of data processing, and a mathematical model of remote transmission and high-precision detection of information based on fractional difference is established, which realizes the functions of high-precision and remote detection of information. By fusing the information data to detect the mathematical model over a long distance and with high accuracy, a mathematical model for stratum data processing used to provide long-distance and high-accuracy data was established. Through application in engineering practice, the effectiveness of this method for underground space information data detection was verified.

Water inrush from coal floor constitutes one of the main disasters in mine construction and mine production, which always brings high risks and losses to the coal mine safe production. As the mining depth of coal fields in North China gradually increased, especially in the complicated structural region, the threat posed by limestone karstic water of coal floor to the safe stoping of mines has become increasingly prominent. In this paper, the Taoyuan coalmine was taken as an example, for which, the directional borehole grouting technology was utilized to reinforce the coal seam floor prior to mining. Also, the factors affecting the grouting effect were analyzed. These were the geological structure, the crustal stress and the range of slurry diffusion. The layout principle of grouting drilling was put forward and the directional drilling structure was designed. The water level observations in the end hole indicated that the target stratum was accurate and reliable. The effect of grouting was validated through the audio frequency electric perspective method and the holedrilling in the track trough. The results demonstrated that the effect of grouting in third limestone and the rock stratum above the third limestone of coal seam floor was apparent. Simultaneously, no water inrush occurred following the actual mining of the working face, which further demonstrated that the grouting reinforcement effect was apparent. The research findings were of high significance for the prevention and control of floor water disaster and water conservation in deep complex structural areas.

Chemical flooding methods are used to recover the remaining oil after water flooding, and surfactant-polymer (SP) flooding is an important chemical flooding technology. It is of great significance to design and screen high-performance oil displacement agents in order to overcome the increasingly challenging high temperature (>70 ℃) and high salinity (>10,000 mg/L) reservoirs. Based on the characteristics of high temperature (70 ℃) and high salinity (151,000 mg/L) in the Qinghai Gasi reservoir, the performance of the SP flooding system was studied. This study considered interfacial tension, emulsification, viscosity, compatibility, and oil displacement efficiency. The selected formula demonstrated high resistance to both salinity (151,000 mg/L) and temperature (70 ℃), characterized by a low oil-water interfacial tension (10-2 mN/m) and high viscosity (18.13 mPa.s). After water flooding achieved an oil recovery rate of 64.64%, the subsequent replacement rate of crude oil increased by 26.95%, confirming that SP flooding can be used as a technology for enhancing oil recovery in high-temperature, high-salinity reservoirs represented by Qinghai Gasi reservoirs.

This research examines how rainfall and mining affect the slope damage resulting from the transition from open-pit mining to underground mining. Using unmanned aerial vehicle (UAV), the Huangniu slope of Dexing Copper Mine was fully characterized, and experiments were conducted on rock samples from appropriate sites. First, the mechanical properties of the samples were measured. Then, the parameters of the similarity simulation experiments were derived based on the similarity theory. Subsequently, the rainfall, rock slope, data acquisition and monitoring systems were designed. Finally, the rock mass failure with different slope angles was analyzed, and the deformation and damage patterns under the coupling effect were obtained. The results show that rainfall increases pore water pressure and moisture content. Rainfall and slope-slip water have more impact on the open-pit platform. The pore water pressure values on the upper rock mass rise faster than inside. In the open-pit mining stage, the rock mass shifts slightly to the upper left. In the room mining stage, vertical fractures and goaf sinking occur. The fractures above the mine room form a semi-ellipse. In the pillar mining stage, the overlying rock displacement is evident, and fractures persist. In the continuous pillar mining stage, the overlying rock collapses massively. The 65° slope model is the most damaged, while the 55° slope model is the least damaged. The results also suggest that the UAV guides sample selection.

With the continuous development of Artificial Intelligence technology and Internet of Things engineering, more and more driver-less vehicles have been developed and put into the industrial production. The birth of driver-less vehicles undoubtedly brings new vitality to a large amount of industries, particularly in transportation. For the mining industry, transportation is undoubtedly an extremely important link in the whole production process. If the driver-less vehicles can be applied to the underground mines, it can not only improve the production and transportation capacity of the whole mine, but also can reduce the occurrence of many mine safety accidents. ZigBee WSN technology can play a greater role in the narrow environment like underground mines according to the relevant literature, this concept paper just like a engineering project plan mainly tries to integrate the ZigBee WSN technology and the communication-based train control (CBTC) system to explore the possibility of the driver-less vehicles to be used in the underground mines, which aims to solve practical engineering problems for the engineering projects. As the mining engineers, we put forward the concept of this integrated system in this concept paper, but we need to continue to work hard for the future of the underground mines. This concept paper serves just as a guide to the Tossing out a brick to get a jade gem, has a few implications for the development of underground mine transportation.

Chronic exposure of workers to powder containing crystalline silica (SiO₂) can lead to chronic lung diseases (lung cancer, silicosis, etc.). The aim of the study was to evaluate the exposure of Greek construction workers to SiO₂ and describe their pulmonary function. The study involved 86 outdoor and underground workers. Medical and professional history was obtained, and breath samples were collected at morning hours through a mask for the determination of SiO₂ levels. Pulmonary function tests, radiological examination and evaluation of radiographs were, also performed. During the examination of the pulmonary function, the majority of the workers were within normal range (61.4%) while the rest were diagnosed with mild (26.5%) and more severe impairment (7.2%). Working conditions (underground-outdoor) were statistically significantly related to the categorization of pulmonary function (p = 0.038). During radiological examination, the type of working conditions (underground-outdoor) were statistically significantly related to the categorization of these findings (p = 0.044). Of the 69 employees, 52 did not present findings (75.4%) and five (5) were diagnosed with findings specific to occupational diseases (7.2%). The environmental exposure to RCS (Respirable crystalline silica) was detected at 0,0125 mg/ m³ in the workplace, which is not beyond the legal limits. Underground workers with more than 15 years of exposure to SiO₂ are more likely to present chronic silicosis compared to the workers of outdoor activities.

A proper transmission of the orientation between surface and underground workings, by means of vertical shafts, is an important challenge in the mining industry, especially when the mine exceeds 200 meters deep. In fact, this study is developed in a mine located to 700 meters deep. Likewise, this paper assesses the accuracy of this operation, in a case study, using the two shafts plumbing and gyroscope methods in order to compare and analyse the planimetric displacement of the base line due to different source of errors in each one. Upsides and downsides of both methods are analysed in the paper. Some disadvantages in each method have been reduced thanks to the technological progress, especially in the two shaft plumbing method. The different sources of error that affect the measures are thoroughly analysed in the study with the aim to compensate them and achieve the required precision for an underground infrastructure. Mine ventilation has been found as one of the most important sources of error in the plumbing method due to intake and return airflow. In this direction, the paper unfolds some measures to reduce the ventilation influence and details a compensation method to reduce ventilation errors.

Monitoring water supply requires, among other quality indicators, the identification of the cyanobacte-ria community taking into account their potential impact in terms of water quality. In this work, cya-nobacteria strains were isolated from Cheffia reservoir and identified based on morphological features, 16S rRNA gene, phylogenetic analysis, and toxin production by PCR screening of the genes involved in the biosynthesis of cyanotoxins (mcyA, mcyE, sxtA, sxtG, sxtI, cyrJ, and anaC). Thirteen strains repre-senting six different genera: Aphanothece, Microcystis, Geitlerinema, Lyngbya, Microcoleus, and Pseudanabaena were obtained. The results demonstrated the importance of morphological features in determining the genus or the species when incongruence between the morphological and phylogenetic analysis occurs and only the utility of the 16S rRNA gene on determining higher taxonomic levels. The phylogenetic analysis confirmed the polyphyly of cyanobacteria for the Microcystis and Oscillatoriales genera. Unexpectedly, Aphanothece sp. CR 11 had the genetic potential to produce microcystins. Our study gives new insight instead of picocyanobacteria toxic genotype in this ecosystem. Thus, conven-tional water treatment methods in this ecosystem have to be adapted.

Recently, torrential rain and drought have occurred in close temporal proximity and for similar durations due to changes in the spatiotemporal patterns of rainfall owing to climate change. In particular, when a drought occurs, it tends to be prolonged, making it necessary to improve the operation of multi-purpose dams that not only control flooding but also serve as water supplies. In this study, standard water volume lines and action plans by response stage were improved so that water could be stored in advance of a drought instead of reservoir operation criteria set based on data from the past. The minimum water demand by use (domestic water, industrial water, and agricultural water) was also calculated. The improved reservoir operation criteria were applied to multi-purpose dams in the Nakdong River Basin, and their effects were analyzed by calculating additionally secured water volumes. In the future, in case of lowered water volumes in multi-purpose dams owing to a drought, the application of these improved reservoir operation criteria is expected to contribute to water supply stability by delaying entry into the drought stage, and minimizing the damages caused by limited water supplies.

During blooms, cyanobacteria produce diverse modified peptides. Among these are the microginins, which inhibit zinc-containing metalloproteases. Ten microginins, microginins KR767 (1), KR801(2), KR835 (3), KR785 (4), KR604 (5), KR638 (6), KR781 (7), KR815 (8), FR3 (9), and FR4 (10) were isolated from the extract of a bloom material of Microcystis sp. (IL-405) collected from the Kishon Reservoir, Israel in the fall of 2009. The structures of the pure compounds were elucidated using 1D and 2D NMR techniques and high-resolution mass spectrometry. The absolute configuration of the chiral centers of the amino acids were determined by Marfey’s and advance Marfey’s methods and by comparison of ¹H and ¹³C NMR chemical shifts of the Ahda derivatives with those of known microginins. These microginins differ in sequence and absolute configuration of the chiral centers of the Ahda moieties and by N-methylation of Ahda amine group and extent of chlorination of Ahda terminal methyl group. The compounds were evaluated for inhibition of the zinc metalloprotease aminopeptidase M and exhibited low- to sub-nanomolar IC₅₀ values.

Developing and utilising of underground space is an vital direction for urban growth. Underground commercial streets, as a significant component of underground space accommodating extensive human social activities, and consequently necessitate the creation of human-scale spaces. In the evolution of urban design development towards greater refinement, applying architectural theories and excessively subjective designs has resulted in a deficiency of human-centered design and a disordered spatial environment. This study merges environmental psychology and architectural theory to determine the appropriate length of spatial scale. Two experiments focusing on spatial perception evaluation were conducted using a virtual experimental platform that featured varying dimensions of spatial scale combinations. These quantified combinations were correlated with perception evaluation, and regression analysis was employed to identify appropriate scale ranges, which were superimposed on the range of length selection. Finally, the optimal length and scale combination for underground commercial street spaces were established, providing a reference for the human-centered design of these environments.

There is a potential for synergy effects in utilizing CO2 for both enhanced gas recovery (EGR) and geothermal energy extraction (CO2-plume geothermal, CPG) from natural gas reservoirs. This “combined CO2-EGR–CPG system” has been introduced as a feasible approach that constitutes a CO2 Capture double-Utilization and Storage (CCUUS) system. In this study, we carry out reservoir simulations, using TOUGH2, to evaluate the sensitivity of the natural gas recovery, pressure buildup, and geothermal power generation performance of the combined system to various key reservoir and operational parameters. The reservoir parameters include horizontal permeability, permeability anisotropy, reservoir temperature, and pore-size-distribution index; while the operational parameters include wellbore diameter and ambient surface temperature. Using an example of a natural gas reservoir model, we also investigate the effects of different strategies of transitioning from the CO2-EGR stage to the CPG stage on the energy-recovery performance metrics and on the two-phase fluid-flow regime in the production well. The simulation results show that overlapping the CO2-EGR and CPG stages and having a relatively brief period of CO2 injection but no production (which we call the CO2-plume establishment stage) achieves the best overall energy (natural gas and geothermal) recovery performance. Permeability anisotropy and reservoir temperature are the parameters the natural gas recovery performance of the combined system is most sensitive to. The geothermal power generation performance is most sensitive to the reservoir temperature and the production wellbore diameter. The results of this study pave the way for future CPG-based geothermal power-generation optimization studies. For a CO2-EGR–CPG project, the results can be a guide regarding the required accuracy of the reservoir parameters during exploration and data acquisition.

This study investigated the spatial variability of soil organic carbon (SOC), total nitrogen (TN), soil microbial biomass carbon (SMBC) and soil microbial biomass nitrogen (SMBN) in Hongqipao reservoir dominated by different vegetation types and the possible relationships with other soil properties. Top 0–50cm soil samples were collected in sites dominated by different vegetation types within the reservoir littoral zone. There was high spatial variability for SOC, TN, SMBC and SMBN in the Hongqipao reservoir. In addition, the SOC, TN, SMBC and SMBN contents decreased with increasing soil depth. This could be attributed by the fact that when plants detritus decompose, most of their organic matter is mineralized and a new soil layer which contains a greater amount of organic carbon is formed at the top. According to Pearson's correlation values and redundancy analysis (RDA) results, SOC was significantly and positively correlated with TN likely because the vegetation organic matter and liter could be the main nitrogen sources. Similarly, soil moisture content (MC) was significant positive correlated with SOC and TN. Conversely, BD was significant negative correlated with SOC and TN contents in the 0-50 cm soil profiles. However, no significant correlations were observed between SOC, TN, SMBC and SMBN contents and soil pH values. SMBN was significantly and positive correlated with C:N ratio and BD and negative related with MC. Multiple linear regression model revealed that all measures soil properties in this study could explain higher significant variability of the response variables (SOC, TN, SMBC and SMBN contents). This implies that all the measured soil variables within the different vegetation types in the reservoir played a crucial role in determining the contents of SOC, TN, SMBC and SMBN. This study further suggests that vegetation types play a major role in determining the spatial characteristics of SOC and TN. Any changes in the vegetation types in the reservoir may influence the distribution of SOC and TN. This may affect the global carbon budget and the atmospheric greenhouse gas concentration significantly.

The controls of depositional environments on reservoir quality have been evaluated in terms of porosity and permeability of the Gabo Field, Niger Delta, Nigeria. Data used in this research include Well logs, Core data and photos, and grain size analysis for Wells 51 and 52 in the study area. Standard methods as applicable in petrophysical and sedimentological analysis has been adopted. Thirteen reservoir units have been identified in wells 51 and 52 which had 5 reservoirs cored each. The lithofacies units of the identified reservoirs across the study area, comprise pebbly sands, coarse -, medium -, fine- and very fine-grained sands, sandy mud, silty sands and heteroliths. The heteroliths – very fine-grained silty muds are highly bioturbated. Ophiomorpha and skolithos are the major trace fossils with sedimentary structures (ripple lamination, wavy lenticular and planar beds, cross bedded sands, coarsening and fining upward). The facies associations interpreted for the study area are Channel and Coastal barrier systems and the environment of deposition as distributary channel, upper and lower shoreface. The sedimentary processes that deposited facies ranged from high energy regimes, reworking by waves to low energy with periodic influx of silts and muds. The average porosity and permeability for reservoirs in Well 51 is 16.7% and 1317 Md, reservoirs in Well 52 is 28.2% and 2330Md whereas porosity range for the study area is 2% - 32% and permeability is 1.2 – 10600 Md. The reservoir quality reservoir of the sand units in Well 51 (7, 9 and 13) and Well 52 (5, 7, 9, 11 and 13) is excellent - good, this is because of the dynamics environments of deposition (upper shoreface and distributary channel) as well as the mechanisms that play out during deposition such as bioturbation, sorting, sedimentary structures formed. Whereas the poor quality across the reservoirs especially the lower shoreface and prodelta facies is as result of lack bioturbation, connectivity, multiplicity of burrows that may have been plugged by clay and intercalation of shale and sand (heteroliths). This research has shown that environments of deposition have direct influence the reservoir quality in terms of porosity and permeability.

The development of mineral resources in China has gradually entered the stage of deep mining. Rock burst, collapse and other ground pressure disasters caused by deep high stress have become major hidden dangers restricting mine safety production. Microseismic monitoring technology is an important means of ground pressure risk prediction. In this paper, the wavelet coefficient threshold denoising method in time-frequency domain, STA/LTA method, AIC method, Skew and Kurtosis method are studied, and the automatic P-phase onset time picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized. the reliability of the P-phase onset time picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity underground mine, Which is of great significance to the data processing and analysis of microseismic monitoring.

The scope of this work was part of our previous research on Pulsed Power Plasma Stimulation Technique. Electromagnetic fields generated during a pulsed power plasma discharge were simulated using a finite element method in the COMSOL RF module. The field distributions were calculated during and after the pulse. The current paper takes advantage of prior work measuring and modeling the current distribution in the plasma arc. Agreement with laboratory experimental measurements provides support for extension of the model to reservoir scale. The validated model was used to quantify the signal attenuation level in different medium environment.

Tight gas, a category of Deep Green Energy Resources, rely on advanced intelligent monitoring methods for their extraction. Conventional logging for reservoir evaluation relies on logging data and the manual setting of evaluation criteria to classify reservoirs. However, the complexity and heterogeneity of tight reservoirs pose challenges in accurately identifying target layers by using traditional well-logging techniques. Machine learning may hold the key to solving this problem, as it enables computers to learn without being explicitly programmed and manually added rules. Therefore, it is possible to make reservoir evaluation via using machine learning methods. In this paper, the reservoir quality index (RQI) and porous geometric parameters obtained from the optimized inversion of the spherical-tubular model are adopted to evaluate the reservoir. Then, three different machine learning approaches, the random forest (RF) algorithm, support vector machine (SVM) algorithm, and extreme gradient boosting (XGB) algorithm, are utilized for reservoir classification. The selected dataset covers more than 7,000 samples from five wells. The data from four wells are arranged as the training dataset, and the data of the remaining one well is designed as the testing dataset to calculate the prediction accuracies of different machine learning algorithms. Among them, accuracies of RF, SVM, and XGB are all higher than 90%, and XGB owns the highest result by reaching 97%. Machine learning based approaches can greatly assist reservoir prediction by implementing the well-logging data. The research highlights the application of reservoir classification with a higher prediction accuracy by combining machine learning algorithms with NMR logging based pore structure characterization, which can provide a guideline for sweet spot identification within the tight formation. This not only optimizes resource extraction but also aligns with the global shift towards clean and renewable energy sources, promoting sustainability and reducing the carbon footprint associated with conventional energy production. In summary, the fusion of machine learning and NMR logging based reservoir evaluation plays a crucial role in advancing both energy efficiency and the transition to cleaner energy sources.

Continuous water resources monitoring is needed for sustainable urban water supply. Remote sensing techniques have proven useful for monitoring some water qualitative parameters with optical characteristics. The study area was the Marateca reservoir in central inland Portugal. The aims were the following: (1) to explore the water quality parameters at the monitoring points of the Marateca reservoir that may explain the event; (2) to validate optical water quality parameters with the monitoring points data; and (3) to model the reservoir water characteristics regarding its deepness, trophic state, and turbidity. The parameters total phosphorus, total nitrogen, and chlorophyll-a were used to compute a trophic level index. The Sentinel-2 imagery was used to compute spectral indices and bands image ratio; to obtain spectral signatures for the monitoring points, and to model water characteristics. The water parameters were above the recommended values at the reservoir entry point from the Ocreza River. The reservoir trophic level was Hypereutrophic and Eutrophic. The spectral signatures confirmed a Hypereutrophic pattern in the entry point. The Marateca reservoir’s water characteristics modeling forecasted problematic zones by contamination. The methodological approach developed can be easily applied to other reservoirs and is a key support tool for decision-makers.

The energy potential of long-period oscillations is estimated by comparing it with watercourse power. The relaxation time of long-period waves is chosen for the estimation time interval, during which their amplitude decreases e (Euler's number) times from the initial one. According to calculations, the amount of energy produced during this time by the watercourse is 9.35–18.71 million kW×h, while the amount of energy of long-period oscillations is 3–6 times less – 1.60–5.48 million kW×h. The components of the economic factor of using long-period waves and currents for electricity production are the predictability of their magnitudes and location of maxima, long-term availability, concentration.

Chemical flooding is one of the effective methods to recover large volumes of oil from sandstone formations after primary depletion. However, silica dissolution often occurs during Alkaline-Surfactant-Polymer (ASP) flooding, affecting the petro-physical properties of the formation. To address this issue, samples from Berea sandstone formations were treated with various brine solutions, through static tube tests and core flooding experiments. Analytical tests such as DR/2800 spectrophotometer and scanning electron microscope were used to evaluate the silica solubility and the alteration in mineral content. The results indicated that the silicate contents decreased after the saturation due to silica solubility in the solution. Increasing brine salinity to 40,000ppm and introducing Magnesium and Calcium ions to the solution, reduces the silicate contents by 5.03 % and 7.32 %. Moreover, saturating the samples with ASP solution, further reduced the silicate contents by 14.86 %. This reduction is associated with a relative increase in silica solubility and pH of the solution. Silica dissolution affects the pore microstructure, which resulted in increasing the porosity and pore volume after the core flooding. The injection of the ASP solution increased the porosity by 5.83%, thus the pore volume increased from 17.72 to 18.76cc. This is associated with the high silica solubility and the increase of solution pH in the ASP solution. The permeability of the samples generally reduced after the core flooding, due to the silica solubility. However, injecting the ASP solution, resulted in a major reduction of the permeability by more than 75%. These changes in the petro-physical properties can lead to severe formation damage, and affect hydrocarbon production. This study assists in understanding the impact of silica dissolution during ASP treatment and addresses the factors involved. Efficient utilization of chemical flooding can help mitigating silicate scaling within the formation, and extend field productivity.

Bacterial cellulose (BC) is receiving great attention due to its unique properties such as high purity, water retention capacity, high mechanical strength, and biocompatibility. However, the production of BC has been limited because of high cost and low productivity. In this light, the isolation of new BC producing bacteria and selection of high productive strains became a promising issue. Kombucha tea is a fermented beverage in which the bacteria fraction of the microbial community is composed mostly by strains belonging to the genus Komagataeibacter. In this study Kombucha tea production trials were performed starting from a previous batch, and bacterial isolation was conducted along cultivation time. From the whole microbial pool, 46 isolates were tested for their ability in producing BC. The obtained BC yield ranged from 0.59 g/L, for the isolate K2G36, to 23 g/L for K2G30 used as the reference strain. The genetic intraspecific diversity of the 46 isolates was investigated using two repetitive-sequence-based PCR typing methods, which are the enterobacterial repetitive intergenic consensus (ERIC) elements and the (GTG)5 sequences, respectively. The results obtained using two different approaches revealed the suitability of the fingerprints techniques, showing a discrimination power, calculated as D index, of 0.94 for (GTG)5 rep-PCR and 0.95 for ERIC rep-PCR. In order to improve the sensitivity of the applied method, a combined model from the two genotyping experiments was performed, allowing to discriminate among strains.

In view of increasing concerns over non-renewable resource depletion and waste management, this study aimed to apply the Taguchi optimization technique to determine the process conditions for producing bricks by incorporating thin film transition liquid crystal displays (TFT-LCD) waste glass powder with reservoir sediments. An orthogonal array L₁₆(4⁵) was adopted, which consisted of five controllable four-level factors (i.e., cullet content, drying method, preheat time, sintering temperature, and error). Moreover, the analysis of variance method was used to explore the effects of the experimental factors on the density, water absorption, shrinkage ratio, loss of ignition, porosity, and compressive strength of the fired bricks. The microstructures of the fired specimens were investigated by scanning electron microscopy. Then, the large-scale production techniques for fired bricks containing recycled TFT-LCD glass cullet and reservoir sediments was developed in a commercially available tunnel kiln. The test results showed that the structure of fired specimen was loose at a sintering temperature ranged from 900–950 °C. However, the fired specimen showed a significant densification at the sintering temperature of 1050 °C. In addition, Taguchi method is a feasible approach for optimizing process condition of brick using recycled TFT-LCD glass cullet and reservoir sediments and it significantly reduces the number of tests. On the other hand, the characteristics of fired bricks developed in the tunnel kiln were in compliance with Chinese National Standards class Ι building bricks criteria.

Based on the geologic conditions of natural gas hydrate (NGH) accumulations in the Shenhu area, northern slope of the South China Sea, this paper used a method of combining reservoir stimulation technique (RST) with depressurization to investigate the conversion efficiency of marine NGH reservoirs in different intrinsic permeability and initial NGH saturation conditions, and analyze the influence of variably-stimulation effect on marine NGH conversion efficiency in different accumulation conditions, provided a reference scheme for improving the NGH conversion efficiency in the Shenhu area. In this work, we performed calculations for the variations in CH4 production rate and cumulative volume of CH4 in different initial NGH saturation, intrinsic permeability and stimulation effect conditions, variance analysis and range analysis methods were used to analyze the significance of these key factors and their interaction, and investigated the sensitivity of stimulation effect on NGH conversion efficiency, respectively. The simulation results showed that stimulation effect have a significant influence on NGH conversion efficiency, and the influence of interaction between these three factors were not obvious. Possibly most important, we clarified an optimum stimulation effect for higher NGH conversion efficiency under different accumulation conditions, especially in low-permeability and high-saturation, which corresponding stimulation effect were different.

Background: Leishmaniasis is a neglected disease with a global spread that affects both domestic and wild animals in addition to people. Leishmania donovani is the suspected anthroponotic cause of VL in India, where it is an endemic disease. The reservoir hosts play a crucial role in the life cycle of the Leishmania parasite. The complicated connection between the pathogen, vector, and reservoir exhibits geographical and temporal diversity. Human-to-human and, to a lesser extent, human-to-animal transmission is the principal mechanism for the maintenance of anthroponotic diseases. Scope and approach: A deliberate, systematic search was conducted on PubMed, Science Direct, and Google Scholar using keywords such as "Leishmania donovani," "zoonotic visceral leishmaniasis," and "wild animal reservoir for leishmania donovani." 530 potentially significant references were obtained from these 507 were disallowed due to copy avoidance, irrelevant titles, research publications from nations other than India, or modified compositions. The remaining 20 investigations were later rejected because they did not meet the criteria for inclusion. Finally 3 research papers with 867 goats, 161 cattles, 106 chickens, 26 sheep, 3 buffaloes, 406 dogs and 309 rats were reported. Conclusion: According to the review, goats are the epidemic's primary host and possible reservoir in several regions of India. In the endemic regions of the disease, some species of rodents along with the canines appear to be maintaining the L. donovani transmission cycle.

In reservoir operations rule curves, it is necessary to apply rule curves to guide long-term reservoir management. This paper proposes an approach to optimize the reservoir operation rule curves (RORC) using intelligent optimization techniques from the Firefly Algorithm (FA) and a unique combination method utilizing the Artificial Bees Colony and Cultural Algorithm (ABC-CA). The aim is to establish a connection with the simulation model to determine the optimal RORC for flood control. The proposed model was used to determine the Nam-Oon Reservoir (NOR) is optimal flood control RORC in Northeastern Thailand. The minimum frequency and a minimum average of ex-cess water were given as an objective function for assessing the efficiency of the search process. The evaluation of the effectiveness of flood control RORC involved expressing water scarcity and excess water situations in terms of frequency, magnitude, and duration using historical inflow data syn-thesized from 1000 events. The results demonstrate that when using the obtained RORC to simulate the NOR system for reducing flooding in long-term operations, situations of excess water were smaller than those using the current RORC. The results indicated that situations of excess water using the obtained RORC from the proposed model were smaller than those using the current RORC situations. In decreasing flood situations, the newly acquired RORC from the suggested FA and ABC-CA models performed better than the current RORC.

Carbonate reservoirs, influenced by depositional and diagenetic processes and characterized by features like faults and vugs that impact storage capacity, require more than traditional Borehole Imaging logs (BHI) for accurate porosity data. This data is essential for geological assessments, production forecasting, and reservoir simulations. This work aims to address this limitation by developing methods to measure and monitor the sustainability of carbonate reservoirs and exploring the application of sustainability principles to their management. The study integrates BHI and conventional logs from two wells to classify porosity-based facies within the Barra Velha Formation (BVF) in the Santos Basin. The methodology involves four steps: (i) analyzing conventional logs; (ii) segmenting BHI logs; (iii) integrating conventional and segmented BHI logs using Self-Organizing Maps (SOM); and (iv) interpreting the resulting classes. Matrix porosity values and non-matrix pore sizes categorize the porosity into four facies (A to D). Facies A has high non-matrix porosity with 14,560 small megapores, 5,419 large megapores, and 271 gigapores (71.9%, 26.76%, and 1.34% of the 20,250 pores, respectively). Facies B shows moderate non-matrix porosity with 8,669 small megapores, 2,642 large megapores, and 33 gigapores (76.42%, 23.29%, and 0.29% of the 11,344 pores, respectively) and medium matrix porosity. Facies C exhibits low non-matrix porosity with 7,749 small megapores, 2,132 large megapores, and 20 gigapores (78.27%, 21.53%, and 0.20% of the 9,901 pores, respectively) and medium matrix porosity. Facies D has low non-matrix porosity with 9,355 small megapores, 2,346 large megapores, and 19 gigapores (79.82%, 20.02%, and 0.16% of the 11,720 pores, respectively) and low matrix porosity. The novelty of this work lies in integrating data from two sources to classify porosity across the Pre-Salt reservoir interval, serving as a proxy for preliminary litho-facies identification without core data. This study advances our understanding of carbonate reservoir sustainability and heterogeneity, offering valuable insights for robust, sustainable reservoir characterization and management in the context of global environmental and geological changes.

The hydrochemical composition of the Upper Jurassic groundwaters in the South German Mo-lasse Basin (SGMB) indicates a heterogeneous and varying hydrogeochemical evolution, which contradicts previous flow model concepts. For this study, the data of 88 Tertiary, Cretaceous and Upper Jurassic groundwater samples were investigated for hydrochemical elements, 2H/18O-H2O isotopes, 87Sr/86Sr ratios as well as δ11B values. In addition, the geochemical composition, 87Sr/86Sr and δ11B values were analysed from depth-oriented Upper Jurassic rock samples to delineate water-rock interactions in the aquifer systems. Slightly elevated 87Sr/86Sr ratios of the carbonates compared to the typical signatures of marine Upper Jurassic carbonates indicate a synsedimentary radiogenic influence due to the erosion of the adjacent Bohemian Massif. However, these values cannot explain the significant higher Sr-isotope fingerprint of the groundwaters in the central SGMB. Different water types occur in the Upper Jurassic aquifer, primarily distinguished by the dominant cations, calcium or sodium with subclasses of the major anions. The calcium-dominated groundwaters occur mainly at the western and northern margins of the SGMB. The sodi-um-dominated ion exchange groundwaters instead dominate in the central and eastern SGMB. With increasing strontium content, the 87Sr/86Sr ratios of the Upper Jurassic groundwater samples either indicate a strontium uptake by carbonate of the host rocks, or a prevailing radiogenic sig-nature. This implies a basic interaction with terrestrial or marine Tertiary sediments. The results illustrate a downward transformational fluid flow systematic via the thick Tertiary sediment cover into the Upper Jurassic carbonate formation in the SGMB, highlighting a new understanding on the evolution of the Upper Jurassic groundwaters and a basin-wide recharge mechanism.

Numerous fractured hydrocarbon reservoirs exist in the metamorphic basement of the Pannonian Basin in Hungary. Many decades of experience in production have proven that these reservoirs are highly compartmentalised, resulting in a complex mosaic of permeable and impermeable domains situated next to each other. Consequently, in most fields, only a small amount of the total hydrocarbon reserve can be extracted. This paper aims to locate the potential migration pathways inside the most productive basement reservoir of the Pannonian Basin, using a multiscale approach. To achieve this, evaluation well-log data, DFN modelling and a composition analysis of fluid trapped in a vein-filling zeolite phase are combined. Data on a single well are presented as an example. The results of the three approaches indicate the presence of two highly fractured intervals separated by a barely fractured amphibolite. The two zones are probably part of the communicating fracture system inside the single metamorphic mass. The gas analysis further specifies the migrated fluids and indicates hydrocarbons of a composition similar to that of the recently produced oil. Consequently, we conclude that the two zones do not only form an ancient migration pathway but are also members of a more recent hydrocarbon system.

The underground injection and geological sequestration of carbon dioxide (CO₂) is a promising approach for reducing the levels of CO₂ in the atmosphere. To mitigate the leakage of CO₂ resulting from natural fracture networks in rock masses, the sequestration process is commonly accompanied by the injection of reactive Portland cement representing a coupled hydro-chemo-mechanical process. In this work, a numerical approach based on the unified pipe network method (UPM) is presented that considers the coupled permeation and diffusion processes with chemical precipitation. Most input parameters are derived from the published literature. The proposed approach is validated through a comparison with analytical solutions, which are applied to simulate the CO₂ sequestration process in a fractured rock mass. The results indicate that the long-term sequestration effect, which is highly influenced by the fracture distribution, can be captured effectively by the model. Consequently, the presented approach can assist engineers in properly designing the arrangement of boreholes and determining the concentration of the grouting material.

Impact of Nitrogen Foamed Stimulation Fluids Stabilized by Nanoadditives on Reservoir Rocks of Hydrocarbon Deposits

The benthic matrix acts as a key natural archive where the memory of long-term timescale environmental changes is recorded. Some ecological and chemical features of fjord sediments were explored during the AREX cruise carried out in the Svalbard archipelago in summer 2021. The activity rates of the enzymes leucine aminopeptidase (LAP), beta-glucosidase (GLU) and alkaline phosphatase (AP) and community-level physiological profiles (CLPP) were studied with the aim of determining the functional diversity of the benthic microbial community, while bacterial isolates were screened for their susceptibility to antibiotic molecules in order to explore the role of these extreme environments as potential reservoirs of antibiotic resistance. Enzyme activity rates were obtained by fluorogenic substrates, CLPP by Biolog Ecoplates; antibiotic susceptibility assays were performed through the standard disk diffusion method. Spatial trends observed in the functional profiles of the microbial community suggested the variability in the microbial community composition, presumably related to the patchy distribution of organic substrates. Complex Carbon sources, carbohydrates and amino acids were the organic polymers preferentially metabolized by the microbial community. Multiple resistance to ampicillin, clindamycin and gentamycin was detected in all the sampled sediments, excepting in the southern Hornsund area, stressing the role of sediments as a potential reservoir of chemical wastes ascribable to antibiotic residuals. This study provides new insights on the health status of fjord sediments of West Spitsbergen applying a dual ecological and biochemical approach. Microbial communities in the fjord sediments showed globally a good functional diversity, suggesting their versatility to rapidly react to changing conditions.

This paper presents a new implementation of a 2-box absolute flow model, enabling the calculation of CO₂ transfer between the atmosphere and a mixing reservoir representing the combined effect of the terrestrial and ocean regions. The model uses published values of anthropogenic CO₂ fossil fuel emissions (CO2ff), atmospheric CO₂ mixing ratio and nuclear weapons bomb yields, to compute atmospheric d¹³C and Δ¹⁴C time-series. The level of agreement between the calculated values and the accepted values for d¹³C is within ± 0.05 ‰, and for Δ¹⁴C is within ± 3‰, spanning 200 years. The model contains only seven internal parameters; these are varied to optimize the fit, leading to reasonable parameter values, indicating the validity of the method. In addition, the model shows how a rising CO₂ exchange influx fluctuating with surface temperature is compatible with a nett atmospheric CO₂ sink. The study demonstrates that a single CO₂ residence time applies to both the ¹⁴C bomb pulse and the anthropogenic flux, contrary to the conventional view that "bomb radiocarbon and anthropogenic CO₂ do not behave identically." [Joos 1994 Nature 370, 181–182]. It is shown that the difference in behaviour, claimed to be due to seawater chemistry, is not significant in practice since fluctuating bulk carbon dominates fluctuating isotopic ratio. A new analysis of the airborne fraction indicates that the assumption of a time-dependent exchange influx results in a similar residence time for bulk CO₂ as for ¹⁴C in the nuclear bomb pulse, reinforcing the view that the ¹²C, ¹³C and ¹⁴C carbon isotopic forms of CO₂ behave similarly in the carbon cycle.

The paper presents the results of modeling the problem of injecting liquid sulfur dioxide into a porous reservoir initially saturated with methane and ice. The model presented in the paper assumes the formation of three different regions, namely, the near one, saturated with liquid SO2 and its hydrate; the far one, containing methane and ice, and the intermediate one, saturated with methane and water. The effects of various parameters of the porous medium and injected SO2 on the nature of the course of the hydrate formation process have been studied. It is shown that with a decrease in reservoir permeability or injection pressure, the length of the intermediate region decreases, which in the limiting case means the formation of SO2 hydrate in the mode without the formation of an extended region saturated with methane and water. It is shown that such a regime is also typical for the case of high initial injection pressures, as well as low values of the initial reservoir temperature and injection temperature.

Reservoirs are recognized as one of the most efficient infrastructure components in integrated water resources management and development. At present, with the ongoing advancement of social economy and requirement of water, the water resources shortage problem has worsened, and the operation of reservoirs, in terms of consumption of flood water, has become significantly important. Reservoirs perform both regulation of flood and integrated water resources management, in which the flood limited water level is considered as the most important parameter for trade-off between regulation of flood and conservation. To achieve optimal operating policies for reservoirs, large numbers of simulation and optimization models have been developed in the course of recent decades, which vary notably in their applications and working. Since each model has their own limitations, the determination of fitting model for derivation of reservoir operating policies is challenging and most often there is always a scope for further improvement as the selection of model depends on availability of data. Subsequently, assessment and evaluation associated with the operation of reservoir stays conventional. In the present study, the Soil and Water Assessment Tool (SWAT) models and a Genetic Algorithm model has been developed and applied to two reservoirs in Ganga River basin, India to derive the optimal operational policies. The objective function is set to minimize the annual sum of squared deviation form desired irrigation release and desired storage volume. The decision variables are release for irrigation and other demands (industrial and municipal demands), from the reservoir. As a result, a simulation-based optimization model was recommended for optimal reservoir operation, such as allocation of water, flood regulation, hydropower generation, irrigation demands and navigation and e-flows using a definite combination of decision variables. Since the rule curves are derived through random search it is found that the releases are same as that of demand requirements. Hence based on simulated result, in the present case study it is concluded that GA-derived policies are promising and competitive and can be effectively used operation of the reservoir.

The Chiltan Formation is a potential hydrocarbon-producing reservoir in the Indus Basin, Pakistan. However, its diagenetic alterations and heterogeneous behavior lead to significant challenges in accurately characterizing the reservoir and production performance. This manuscript aims to utilize Chiltan Limestone core samples to conduct a detailed analysis of the diagenetic impacts on reservoir quality. The formation evaluation was carried out through thin section analysis, SEM-EDS and FTIR investigation, as well as plug porosity and permeability measurements under different stress conditions. In results, Petrography revealed three microfacies with distinct diagenetic features and micro-nano fossil assemblages, including intraclasts, pelloids, bioclasts, and stylolites. Diagenesis has a significant impact on petrophysical properties, leading to increased reservoir heterogeneity. The specified depositional environment exposed the alteration of the Chiltan formation during distinct diagenetic phases in marine, meteoric, and burial settings. Pore morphology and mineralogy reveals complex micro-pore structure with various carbonate mineral phases and cement types in the formation samples. The average porosity and permeability of the core samples were found to be 3.4% and 0.449 mD respectively, indicating poor reservoir quality. Stress sensitivity was determined using Klinkenberg corrected permeability, which indicated a reduction in measured and absolute permeability due to increasing confining stress, further reducing the pore throat structure of the formation. In conclusion, the Chiltan formation possesses intricate reservoir heterogeneity and varied micro-pore structure caused by diagenesis and depositional settings. The formation is classified as a low-quality reservoir due to its non-uniform pore geometry, which exhibits low petrophysical properties resulting from overburden stress. The results of this study provide solid foundation in reservoir characterization and quality assessment which has implications for exploring and exploitation of indigenous resources.

Rapid draw-down in an earthfill dam has serious implications for dam safety regarding slope stability. The evaluation of reservoir draw-down impact on slope stability was carried out considering the case study of 8 hours of rapid draw-down of the Middle Marsyangdi Hydroelectric Power Project (MMHPP) rock-fill dam using the Limit Equilibrium Method (LEM) and stress-based Finite Element Method (FEM). The time-dependent factor of safety (FOS) was evaluated and found that the 8 hours of rapid draw-down undertaken in October 2012 for reservoir flushing was unsafe with a draw-down rate of 1.91m/h. The resulting FOS of 1.28 and 1.27 using LEM and FEM was classified as unsafe as per the US Army Corps of Engineers’ guideline, the minimum required factors of safety should be greater than 1.3. The minimum safe allowable draw-down rate of 0.76m/h for 20 hours was identified. Applying three layers of horizontal filter materials and increasing the upstream dam’s permeability provided adequate FOS results for all cases by increasing seepage discharge to reduce the destabilizing excess pore water pressure. Several gradual draw-down rates were also tested and found that FOS increases with decreased draw-down rates, as it reduces the excess pore water pressure controlled with stabilizing existing water load.

Faced with difficulties stemming from the complex interactions between tight gas sand bodies and fractures when describing and identifying reservoirs, a composite reservoir model was established. By setting the supply boundary to characterize the superposition characteristics of sand bodies, a mathematical model of unstable seepage in fractured vertical wells in tight sandstone gas reservoirs was constructed considering the factors such as stress sensitivity, fracture density and fracture symmetry. The seepage law and pressure response characteristics of gas well in tight sandstone discontinuous reservoir with stress sensitivity, semi-permeable supply boundary and complex fracture topology were determined, and the reliability of the model was verified. The research results more accurately depict the pressure characteristic curve of the superposed sand body complex fracture vertical well, and provide a more comprehensive model for tight gas production dynamic analysis and well test data analysis, which can more accurately guide the dynamic inversion of reservoir and fracture parameters.

Sediment accumulation in a dam reservoir is a common happening environmental problem throughout the world. Topographic conditions, land use land cover change, the intensity of rainfall, and the soil characteristics are the major driving factors for sedimentation to occur. The effect of sedimentation in a dam reservoir is very visible in the watershed as a result of hilly topographic conditions, high rainfall intensity, thin land cover, and less soil infiltration capacity. In this paper, an integrated RUSLE and GIS technique was implemented to estimate a mean annual sediment yield based on spatial and temporal variations in Nashe dam reservoir situated in Fincha catchment, Abaya River basin, Ethiopia. Spatial and temporal estimation of mean annual sediment yield was estimated using the Revised Universal Soil Loss Equation (RUSLE) model and GIS. Historical 6-year (2014-2019) rainfall for the temporal variations and other physical factors such as soil erodibility, slope and length steepness, management and land used land cover, and support practice for spatial variations were used as sediment driving factors. The mean annual sediment yield ranges from 0 to 2712.65 t ha-1 year-1 was seen. Spatially, Very high, high, moderate, low, and very low sediment yield severity with total area coverage with 25%, 10%, 30%, 15%, and 20% in 2017, 2015, 2019, 2014, and 2018 respectively. The information about the spatial and temporal variations of the severity of sediment yield in RUSLE model has a paramount role to control the entry of sediment into the dam reservoir in this watershed. The results of the RUSLE model can also be further considered along with the watershed for planning strategies for dam reservoirs in the catchment.

The aim of this research was to analyze the impact of implemented erosion control works (ECW) on soil erosion intensity in the watershed of the Ćelije reservoir (Rasina River) in the period between 1968 and 2022. The Erosion Potential Method was used to calculate the annual gross erosion (W), sediment transport (G), and erosion coefficient (Z) in the study area. As a result of the performed ECW there was a general decreasing trend in the intensity of soil erosion processes in the last 54 years. The specific annual gross erosion was 1189.12 m3/km-2/year-1 in 1968, while in 2022 it was 554.20 m3/km-2/year-1. The specific sediment transport was 540.18 m3/km-2/year-1 in 1968 and 253.55 m3/km-2/year-1 in 2022. Due to the changes in the intensity of erosion processes the specific annual gross erosion decreased by 634.92 m3/km-2/year-1, and the specific sediment transport by 286.63 m3/km-2/year-1. The erosion coefficient was reduced from Z=0.62 to Z= 0.35. A dependence between the slope of siltation and the natural bed slope was defined. The results show a significant correlation between erosion intensity and performed ECW, providing a basis for future watershed management and defining a strategy for soil erosion control in the Ćelije reservoir watershed.

Time series ground deformation monitoring and reservoir parameter inversion are crucial for the dynamic assessment of oilfield resources and sustainable exploitation in an oilfield. As one of the regions with the richest oil reserves in China, the oilfield areas in the western Qaidam Basin are selected as a typical study area. Firstly, we used SAR images collected by the Sentinel-1A satellite from January 2021 to December 2022 and applied the Multidimensional Small Baseline Subset (MSBAS) method to obtain vertical and east-west deformation measurements. On this basis, a nonlinear Bayesian inversion method was applied to model the shallow reservoir in a series of complex deformation areas, based on a single-source model and a multi-source model, respectively. As a result, the ground deformation monitoring results obtained by long time series InSAR clearly reflect the uneven ground deformation caused by the oil extraction and water injection operation process. There is slight subsidence in the Huatugou oilfield, while significant uplift deformation occurred in the Ganchaigou oilfield and the Youshashan oilfield, with a maximum uplift rate of 48 mm/year. Further analysis indicates that the introduction of the 2D deformation field helps to improve the robustness of oilfield reservoir parameter inversion. Moreover, the dual-source model is more suitable than the single-source model for inverting complex deformation reservoir parameters. This study not only fills the blank of InSAR deformation monitoring for the oilfields in the western Qaidam Basin but also provides a theoretical reference for model and method selection of reservoir parameter inversion in other oilfields.

Water management systems help allocate water resources effectively, considering various demands such as agriculture, industry, domestic use, and environmental needs. They optimise water distribution and ensure equitable access, minimising water scarcity and conflicts. Critical elements of this system are often the target of various attacks. Depending on the target of the attack, different scenarios based on physical, cyber, or combined forms of attacks can be used. Requirements for the protection of water objects forming part of the critical infrastructure system are determined primarily by generally binding legal regulations, technical standards, or other requirements of third parties. These requirements imply the need to adopt certain protective measures. Physical protection system (PPS), as a convenient way of organising protective measures, makes it possible to prevent an unauthorised person from achieving his goal. Current procedures aimed at protecting objects use a qualitative or quantitative approach. The article presents the use case of a possible way to protect a selected water reservoir that has been identified as a national element of critical infrastructure in the subsector Drinking Water Provision. The use case is based on the analysis of safety requirements and subsequent design of the PPS water reservoir. To verify the functionality of the proposed PPS, a quantitative PPS model was created using a software tool, and four possible attack scenarios were simulated.

(1) The article is devoted to the development of a theoretical and algorithmic basis for numerical modeling of the spontaneous potential method (SP) as applied to the study of sandy-argillaceous reservoirs. (2) In terms of coupled flows, we consider a physical-mathematical model of SP signals from an electrochemical source, with regard to the case of fluid-saturated shaly sandstone. (3) An algorithm for 2D finite-element modeling of SP signals was developed and implemented in software, along with its internal and external testing with analytical solutions. The numerical SP modeling was carried out, with determining the dependences on the reservoir thickness and porosity, the amount of argillaceous material and the type of minerals. We performed a comparative analysis of the simulated and field SP data, using the results of laboratory core examinations taken from wells in a number of fields in the Latitudinal Ob Region of Western Siberia. (4) The results of the study may be used either for the development of the existing SP techniques, by providing them with a consistent computational model, or for the design of new experimental approaches.

The traditional sequent peak algorithm (SPA) was used to assess the reservoir volume (VR) for comparison with deficit volume, DT, (subscript T representing the return period) obtained from the drought magnitude (DM) based method with draft level set at the mean annual flow on 15 rivers across Canada. At an annual scale, the SPA based estimates were found to be larger with an average of nearly 70% compared to DM based estimates. To ramp up DM based estimates to be in parity with SPA based values, the analysis was carried out through the counting and the analytical procedures involving only the annual SHI (standardized hydrological index, i.e. standardized values of annual flows) sequences. It was found that MA2 or MA3 (moving average of 2 or 3 consecutive values) of SHI sequences were required to match the counted values of DT to VR. Further, the inclusion of mean, as well as the variance of the drought intensity in the analytical procedure, with aforesaid smoothing led DT comparable to VR. The distinctive point in the DM based method is that no assumption is necessary such as the reservoir being full at the beginning of the analysis - as is the case with SPA.

This work investigates the utility of the National Oceanic and Atmospheric Administration’s National Water Model (NWM) for water management operations by assessing the total inflow into a select number of reservoirs across the Central and Western U.S. Total inflow is generally an unmeasured quantity, though critically important for anticipating both floods and shortages in supply over a short-term (hourly) to sub-seasonal (monthly) time horizon. The NWM offers such information at over 5,000 reservoirs across the U.S., however, its skill at representing inflow processes is largely unknown. The goal of this work is to understand the drivers for both well performing and poor performing NWM inflows such that managers can get a sense of the capability of NWM to capture natural hydrologic processes and in some cases, the effects of upstream management. We analyzed the inflows for a subset of Bureau of Reclamation (BoR) reservoirs within the NWM over the long-term simulations (retrospectively, seven years) and for short, medium and long-range operational forecast cycles over a one-year period. We utilize ancillary reservoir characteristics (e.g. physical and operational) to explain variation in inflow performance across the selected reservoirs. In general, we find that NWM inflows in snow-driven basins outperform those in rain-driven, and that assimilated basin area, upstream management, and calibrated basin area all influence the NWM’s ability to reproduce daily reservoir inflows. The final outcome of this work proposes a framework for how the NWM reservoir inflows can be useful for reservoir management, linking reservoir purposes with the forecast cycles and retrospective simulations.

With the continuous development of the mining industry, the world's major mines have gradually entered the intelligent stage. In the intelligent underground mine, the operation road of the underground transportation equipment is very complicated, and the monitoring and control of the underground traffic has become a problem to be solved in the intelligent underground mine. Therefore, on the basis of solving the practical problems of underground mines, the concept paper discusses the possibility of the rail transit monitoring system being applied to underground mines through the summary and induction of the related literature and propose the design for the CBTC system to solve the problems in the underground mine rail transportation. As the mining engineers, we put forward the concept of this design for the CBTC system in this concept paper, but we need to continue to work hard for the future development of the underground mines. And the concept paper serves as a guide to the Tossing out a brick to get a jade gem, has implications for the development and the future of the underground mine transportation.

The PB Sudirman hydroelectric power plant, built in 1988, has fewer than 50 years of operational life. In contrast, the planned operating life for this dam is 50 years. This dam is experiencing intensive sedimentation, which results in siltation. Dredging efforts and catchment area management are conducted to extend the operational life of the dam. Therefore, technical and economic analysis of dredging activities and the potential benefits of dredged sediment is needed to determine the solution's effectiveness. We use the site survey method to conduct an environmental impact analysis and interviews with dam managers. The identification of the extent and distribution of erosion-sedimentation was carried out as part of the technical assessment. In the economic study, we calculate the dredging costs and profits from selling dredged sediments, mainly sand. The analysis results show that the dredging of deposits in the foreset slope area is not profitable. There are 17 areas of bank spoil that have economic benefits. This study concludes that the need for dredging costs on foreset slopes is higher than the profit from selling dredging sediments.

The log interpretation and evaluation of Chang 8 tight sandstone reservoir in Longdong West area, Ordos Basin, is facing great challenges due to the existence of low resistivity contrast oil pays. To better guide the exploration of oil resources in this area, the characteristics and control mechanism of low resistivity contrast oil pays were studied in this research. Firstly, according to the relative value of apparent resistivity increase rate of the target formation, the reservoir was divided into two types: low resistivity contrast oil pay (LRCP) and high resistivity oil pay (HRP). Then, the reservoir characteristics were studied by comparing and analyzing the experimental data, formation water data and logging data collected from the two reservoir types. On this basis, the control mechanism of LRCP was studied and summarized into reservoir micro factors and regional macro factors, respectively. It is found that the reservoir rock composition between LRCP and HRP is basically the same. Compared with HRP reservoir, the average porosity and permeability of LRCP reservoir are relatively better, but the pore structure is relatively poorer because of the high content of micro pores. When the filling pressure of crude oil is sufficient enough, the high oil saturation can be formed in LRCP reservoir. The high irreducible water saturation and high formation water salinity are the main micro factors reduced the reservoir resistivity. Besides, the difference of hydrocarbon expulsion capacity of source rock and the regional difference of formation water salinity are the macro factors influenced the distribution of LRCP and HRP from vertical and horizontal of the region. The formation of LRCP is controlled by the comprehensive influence of reservoir micro factors and regional macro factors. And the comprehensive consideration of the influence of micro factors and macro factors on LRCP is suggested during the log interpretation and evaluation.