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Article

Characterization of Architecture Bounding Surfaces in Fluvial Tight Sandstone Reservoirs and Their Influence on Remaining Gas: A Case Study from the Suzhong Block, Sulige Gas Field

by
Xinqiang Liu
1,2,3,
Jinbu Li
2,
Yuming Liu
1,*,
Qi Chen
1,
Yuqi Bai
2,
Fuping Li
2,
Lei Jin
1 and
Bingbing Zhang
1
1
College of Geoscience, China University of Petroleum (Beijing), Beijing 102249, China
2
Exploration and Development Research Institute, PetroChina Changqing Oilfield Company, Xi’an 710018, China
3
National Elite Institute of Engineering, CNPC, Beijing 100096, China
*
Author to whom correspondence should be addressed.
Energies 2024, 17(17), 4262; https://doi.org/10.3390/en17174262
Submission received: 27 June 2024 / Revised: 14 August 2024 / Accepted: 23 August 2024 / Published: 26 August 2024
(This article belongs to the Section H: Geo-Energy)
Browse Figures
Versions Notes

Abstract

:
The H8 and S1 reservoirs in the lower Shihezi Formation and Shanxi Formation of the central block in the Sulige Gas Field are typical fluvial tight sandstone reservoirs. Due to frequent river channel migrations during deposition, the reservoirs exhibit complex spatial structures with developed intra-sand mudstone interlayers. As the field has entered the middle and late stages of development, the distribution of remaining gas is intricately controlled by these interlayers, necessitating research on their distribution to understand the remaining gas patterns and types for effective extraction enhancement. However, the thinness of interlayers presents a challenge for precise prediction. Addressing this, this study delineates different interlayer types and their origins, applies reservoir architecture theory, and utilizes bounding surfaces characterization, planar and sectional distribution studies, unit scale analysis, horizontal well data, and quantitative characterization methods to investigate the internal reservoir architecture bounding surfaces. The study finely portrays the interlayer distribution, analyzes the control of reservoir architecture bounding surfaces on remaining gas, and establishes a multi-tiered reservoir architecture model in the study area. Numerical simulation of the gas reservoir clarifies the types of remaining gas enrichment. This study also identifies and quantitatively characterizes the 5–3 level architecture bounding surfaces within the sandbody, categorizing the remaining gas into bounding surfaces-controlled, well-network uncontrolled, and single-layer unperforated types, proposing targeted enhancement measures for each type. Based on the findings, four vertical wells and three horizontal wells were deployed, improving the well network density to three wells per square kilometer. The first completed horizontal well encountered an effective drilling rate of 61.7%, marking significant implications for the exploitation and recovery enhancement of similar tight sandstone gas reservoirs.

1. Introduction

The fluvial tight sandstone reservoirs within the Sulige Gas Field demonstrate robust north–south connectivity and extensive sandbody distribution, positioning them as a significant production region for tight gas in China [1,2]. Nevertheless, the frequent channel migrations and turbulent depositional conditions have engendered the formation of interlayers within the sandbodies [3], leading to rapid lateral variations in reservoir properties and resulting in highly heterogeneous internal spatial structures [4]. As the gas field progresses into its middle and late development stages, these interlayers emerge as pivotal factors in controlling the distribution of remaining gas [5]. Consequently, comprehending the distribution characteristics of interlayers within fluvial tight sandstone reservoirs is paramount for precise remaining gas extraction and enhanced recovery during these stages [6]. Various methodologies have been proposed by researchers, both domestically and internationally, to predict interlayer distribution, encompassing geostatistical methods, field outcrop studies, core observations, and seismic sedimentology. However, research focusing on the impact of interlayer distribution on remaining gas distribution in tight sandstone reservoirs remains limited. Predominantly, existing studies have centered on the control exerted by composite channels or single sandbodies on remaining gas distribution [6]. Bu Tao et al. [7] investigated the origin types of remaining gas through structural analysis, sedimentary microfacies distribution analysis, and numerical simulation. He Faqi et al. [8] developed 3D geological models based on single sandbody descriptions to classify remaining gas. Shi Yaodong et al. [9] explored the influence of fifth- and fourth-order architectural elements on remaining gas distribution via reservoir architecture characterization. Despite these efforts, there remains a paucity of research on the quantitative characterization of interlayers within fluvial tight sandstone reservoirs and the control exerted by various architecture bounding surfaces on remaining gas distribution, with most studies constrained to the influence of fifth- and fourth-order elements. During the early development stages of the central block of the Sulige Gas Field, the prediction of muddy interlayers within the reservoir was hindered by development costs and the limited availability of seismic and coring data, posing a significant technical bottleneck for efficient remaining gas distribution and overall gas field development. There is an urgent imperative to investigate the control of interlayer distribution on remaining gas distribution and to formulate development strategies that would facilitate breakthroughs in the efficient exploitation of such tight reservoirs.
As gas field development progresses, reservoir architecture analysis, which characterizes the internal spatial structure of the reservoir, has emerged as a pivotal tool for studying remaining gas distribution [10]. Research indicates that the architecture bounding surfaces developed between internal architectural elements within the reservoir significantly impede and control the flow of natural gas. This study focuses on the H8 unit of the lower Shihezi Formation and the S1 unit of the Shanxi Formation within the central block of the Sulige Gas Field. Guided by the classification and genetic patterns of reservoir architectural levels, we meticulously describe the “bounding surfaces” (“interlayer”) characteristics between different genetic units at each hierarchical level. We have identified and summarized three distinct distribution patterns of remaining gas and proposed corresponding strategies for their exploitation. These strategies are geared towards enhancing the development efficacy of the gas reservoir and providing technical guidance aimed at improving the recovery rate of the gas field. By understanding and addressing the influence of various architecture bounding surfaces on remaining gas distribution, we aim to optimize extraction processes and maximize resource recovery, thereby advancing the technical and economic outcomes of gas field development.

2. Geological Overview

The Suzhong block, situated centrally within the Sulige Gas Field(Figure 1a), spans an area of 60 km² [10] (Figure 1b). The structure exhibits a gentle rise from south to north at a gradient of 1.5 m per kilometer, with a formation dip of approximately 0.1° [10], resulting in relatively flat topography [11]. This region predominantly features low-amplitude anticlines and nose structures [11], which are favorable for natural gas accumulation and preservation [12]. The sediment source direction is oriented north–south, with the primary gas-producing strata being the H8 member of the Lower Shihezi Formation and the S1 member of the Shanxi Formation (Figure 1c), located at depths of approximately 3200 to 3500 m. Common paleontological fossils within the reservoir include plant remains, such as carbonized plant stems and leaf imprints [13]. Geological studies have further subdivided the H8 member into upper and lower sub-members [13]. The upper sub-member is characterized by deposits from a meandering river delta plain, while the lower sub-member features braided river delta plain deposits. Similarly, the S1 member consists of meandering river delta plain deposits, with channel lengths extending up to 4000 to 7000 m. The reservoir exhibits significant heterogeneity and is predominantly composed of coarse to medium sandstone. The H8 member reservoir displays a variety of pore types, including dissolution pores, intercrystalline pores, and localized fractures. Porosity generally ranges from 10% to 20%, with permeability typically between 0.1 and 10 mD, indicating favorable reservoir properties and high-quality natural gas storage. In contrast, the S1 member sandstone reservoir has porosity ranging from 8% to 18% and lower permeability, usually between 0.01 and 1 mD, reflecting higher tightness [11,12,13].

3. Materials and Methods

Identifying and quantitatively characterizing reservoir architecture bounding surfaces through logging data is crucial for understanding remaining gas distribution features and formulating development strategies. In this study, we analyzed core photographs, grain size data, and thin section samples from core wells. We focused on establishing lateral boundary combinations for braided and meandering river systems by examining the natural gamma and gas measurement curves from horizontal wells, which guided the delineation of four levels of architecture unit boundaries. Based on variations in natural gamma and resistivity curves from vertical wells, and guided by sedimentary models of braided and meandering river delta plains, we categorized the vertical boundaries of different architecture units. Finally, we employed 3D geological modeling and numerical simulation techniques to classify the types of remaining gas in the study area, proposed corresponding potential exploitation measures, and predicted the remaining reserves, providing guidance for future gas field development and production.

4. Results

4.1. Analysis of Reservoir Architecture Bounding Surfaces

4.1.1. Classification of Architectural Elements

The mudstone in the study area is primarily gray and brownish, indicating a terrestrial oxidizing to weakly reducing depositional environment at the time. The lower sub-member of the H8 formation mainly consists of quartz sandstone and lithic quartz sandstone, followed by lithic sandstone. The upper sub-member of the H8 formation and the S1 formation predominantly comprise lithic quartz sandstone, with quartz sandstone and lithic sandstone also present. These formations exhibit trough cross-bedding, tabular cross-bedding, and parallel bedding. As shown in Figure 2, grain size analysis using image data and core samples reveals that the grain size distribution is concentrated, with cumulative peaks between 0.8 and 1.8 mm, predominantly medium to fine sandstone, with less coarse sandstone and siltstone. Additionally, as observed under a microscope (Figure 3), the grains are mostly sub-angular to sub-rounded, with moderate to good sorting, indicating complex hydrodynamic conditions at the time.
Based on meticulous core observations [13], detailed petrographic thin section identification, and comprehensive grain size analyses, this study delineates that the area is predominantly characterized by six distinct reservoir architectural units: braided channels, active channels, channel bars, point bars, crevasse splays, and floodplains.
Braided and Active Channels: These units are typified by silty mudstone and mudstone, all of which exhibit suboptimal physical properties. The natural gamma ray log profiles of these units present bell-shaped or finger-shaped patterns with a positive rhythm, characterized by small-scale cross-bedding and horizontal bedding. In plan view, they manifest as narrowly ribbon-like features and are associated with poor gas content (Figure 4a).
Channel Bars (Heart Bars): These units are composed of medium to fine sandstone interbedded with silty mudstone and calcareous (argillaceous) cemented fine sandstone. The natural gamma ray log profiles of channel bars exhibit box-shaped patterns with medium to high amplitude and slight serrations, demonstrating a homogeneous or indistinct positive rhythm. These bars develop cross-bedding and parallel bedding, and in plan view, they appear rhombic or elliptical. In cross-section, they present a convex top and flat bottom, indicative of favorable gas content (Figure 4b).
Point Bars: These units consist of medium to fine sandstone, characterized by bell-shaped natural gamma ray log profiles with a positive rhythm, and exhibit cross-bedding. In plan view, point bars display a tongue-shaped geometry, and in cross-section, they feature a flat top and convex bottom, suggesting good gas content (Figure 4c).
Crevasse Splays: Composed of siltstone and fine sandstone, crevasse splays exhibit finger-shaped natural gamma ray log profiles with an inverse rhythm, and develop cross-bedding. They present a tongue-shaped or lenticular appearance in plan view and have moderate gas content (Figure 4d).
Floodplains: These units are characterized by mudstone, silty mudstone, and argillaceous silt, with medium to low amplitude funnel-shaped natural gamma ray log profiles, lacking a distinct rhythm. They develop horizontal and massive bedding and do not exhibit distinctive geometric features in plan view (Figure 4e).

4.1.2. Division of Reservoir Architecture Bounding Surfaces

A.D. Miall posits that stratigraphic architecture consists of continuous architectural elements and their bounding surfaces, which correspond to interlayers within the strata, implying a hierarchical nature of interlayer types [14,15,16]. Drawing from Miall’s classification of architecture bounding surfaces in fluvial facies reservoirs and previous research on the classification of tight sandstone reservoir architecture in the Sulige area [17,18,19,20], we combined core, logging, and laboratory analysis data. Employing methods such as bounding surfaces feature identification, planar and sectional distribution studies, architectural element scale analysis, and horizontal well data, we classified the architecture bounding surfaces of the target layers in the study area into five levels: Level 5 bounding surfaces, Level 4 bounding surfaces, and Level 3 bounding surfaces(Table 1, Figure 5).
(1) Level 5 architecture bounding surfaces demarcate individual channels (braided or meandering zones) and are defined by the boundary surfaces (overbank argillaceous interlayers). These are primarily composed of gray to dark gray mudstone, with no gas logging response. The natural gamma ray log values exceed 120 API, exhibiting low-amplitude serrated profiles.
(2) Level 4 architecture bounding surfaces delineate the boundaries of heart bar sandbodies or braided channels/point bars or active channel fills. These bounding surfaces are typically dominated by fine-grained sediments, primarily consisting of gray siltstone and silty mudstone. The gas logging values are less than 0.1, and the logging curves exhibit characteristics of shale interbeds. The natural gamma ray log values range from 80 to 120 API, presenting low-amplitude serrated profiles that are slightly higher than those of Level 5 bounding surfaces.
(3) Level 3 architecture bounding surfaces primarily consist of depositional layers and lateral accumulation layers within the central bars/point bars, often manifested as low-permeability zones with poor physical properties. The dominant lithology includes light gray and gray siltstones and mudstones, with the natural gamma curve exhibiting a reversal phenomenon. Spatially, these layers are distributed horizontally and in a domal shape.

4.2. Lateral Boundary Combination Patterns for Horizontal Wells

The gas reservoir in the study area vertically exhibits multiple overlapping thin tight gas layers in a relatively flat stratigraphy. Identifying reservoir architecture bounding surfaces using only vertical well data is challenging and has low accuracy, especially without high-resolution seismic data. However, horizontal well data can provide abundant subsurface reservoir information under large well spacing conditions [15,16,21,22]. Based on horizontal well logging, cuttings logging, and gas logging data, and guided by fluvial sedimentary models, we have developed a lateral boundary combination model for braided and meandering river horizontal wells in the study area (Figure 6).
Braided River Horizontal Well Lateral Boundary Combination Model:
(1)
Sandbar–Braided Channel–Sandbar: The lithology fines, dominated by light gray fine sandstone. The natural gamma ray curve shows small fluctuations, rising and then falling, with a decrease in gas logging values followed by a rapid increase.
(2)
Sandbar–Muddy Channel–Sandbar: The lithology abruptly fines, featuring sandy mudstone. The natural gamma ray curve spikes and exhibits unstable high values, with a sudden drop in gas logging values, occasionally showing small spikes.
(3)
Sandbar–Braided Channel–Floodplain: The lithology gradually fines, transitioning to dark gray mudstone. The natural gamma curve gradually rises and sustains high values, while gas logging values gradually decrease, abruptly transitioning to no gas indication.
Meandering River Horizontal Well Lateral Boundary Combination Patterns:
(1)
Point Bar–Active Channel–Point Bar: The lithology abruptly transitions to gray mudstone, occasionally containing some sandy material. The natural gamma ray sharply increases and maintains stable high values, while gas logging abruptly drops from high values to no gas indication.
(2)
Point Bar–Active Channel: The lithology transitions to gray mudstone, occasionally including sandy components. The natural gamma ray curve gradually increases and sustains high values, with gas logging gradually decreasing and abruptly dropping to no gas indication.
(3)
Point Bar–Floodplain: The lithology abruptly changes to dark gray mudstone, relatively pure, with the natural gamma ray curve sharply transitioning to high and stable values, and gas logging abruptly dropping to no gas indication.

4.3. Identification and Quantitative Characterization of Tight Sandstone Reservoir Architecture Bounding Surfaces

4.3.1. Identification and Quantitative Characterization of 4th-Order Reservoir Architecture Bounding Surfaces

1. Architecture Bounding Surfaces Identification
(1) Vertical Boundary Identification Based on Vertical Well Information
Identification of Vertical 4th-Order Architectural Surfaces in Fluvial Facies Tight Sandstone Reservoirs: In these reservoirs, different-stage architectural units of reservoir architecture overlap vertically, often separated by intercalated argillaceous layers and abrupt physical property bounding surfaces [23,24,25,26]. These 4th-order architecture bounding surfaces are identified vertically in two aspects: Firstly, the end of each sedimentation cycle of the heart-shoal/point-bar sand bodies, due to weakened hydrodynamic strength, often leads to the deposition of fine-grained material with high clay content, which is characterized by argillaceous intercalations in well logging, such as the clayey intercalations formed between the two stages of single sand bars in wells Z1 and Z2 (Figure 7a,b). Secondly, due to frequent channel meandering, the sand bodies deposited in the previous stage are eroded by the subsequent stage, forming a poorly permeable sandstone transition zone. For example, the bounding surfaces with logging curve reversals between wells Z3 and Z4 represents a poorly permeable sandstone transition zone (Figure 7c,d).
(2) Lateral Boundary Identification Based on Horizontal Well Information
Lateral Boundary Identification of Reservoir Architectural Units in the Study Area: During the same geological period, the lateral splicing of different reservoir architectural units manifests as the coexistence of multiple sand bars or the lateral movement of a single sand bar, leading to the interleaving, superposition, and connection of these units laterally [27,28,29,30]. Based on the lateral boundary combination patterns of horizontal wells, the results of single-well logging interpretations, and the reservoir prototype model (geometric shape + spatial contact), supplemented by sand body thickness constraints, the lateral boundaries of reservoir architectural units in the study area were comprehensively determined. This approach was used to delineate the lateral bounding surfaces of single sand bodies in the study area. For example, in horizontal well H1, at an inclined depth of 3368–3368 m, it encountered light gray mudstone and sandy mudstone, indicating a fining of lithology. Combined with the lateral boundary combination pattern 2 of braided river horizontal wells, it is predicted that at this depth range, the well drilled through the transition bounding surfaces between the muddy channel, heart-shoal, and braided channel (Figure 8).
2. Quantitative Characterization
Development characteristics and spatial distribution of 4th-order a architecture bounding surfaces in fluvial facies tight sandstone beach bar (heart-shoal, point bar) Reservoirs: A comprehensive investigation of the development characteristics of beach bar (heart-shoal, point bar) reservoirs in fluvial facies tight sandstones, both domestically and internationally, combined with core observations [31,32,33], logging response characteristics, and lateral boundary combination patterns of horizontal wells [34,35,36,37], indicates that the distribution of 4th-order architecture bounding surfaces in the study area is controlled by the spatial arrangement of beach bar (heart-shoal, point bar) sand bodies. The lateral extent of inter-bar mudstone intercalations ranges from 200 to 350 m, with a longitudinal extension of 300 to 600 m, and a thickness of 1 to 2 m, locally reaching up to 5 m. The lateral extent of inter-point bar mudstone intercalations ranges from 150 to 500 m, with a longitudinal extension of 1000 to 2000 m, and a thickness of 0.8 to 3 m, locally reaching up to 5 m.

4.3.2. Identification and Quantitative Characterization of the 3rd-Level Architecture Bounding Surfaces

1. Identification of the 3rd-level Architecture Bounding Surfaces
The genesis of the 3rd-level architecture bounding surfaces determines the unstable distribution of this type of interlayer, which exhibits similar characteristics to argillaceous or calcareous interlayers on logging curves but with pronounced curve reversals. Based on the 4th-order architectural units, this study identified the 3rd-order architecture bounding surfaces using core data, logging information, lateral boundary combination patterns of horizontal wells, and guidance from depositional models. Specific identification methods include, for example, when two wells encounter the same channel bar, if the depth of the Z5 accretionary layer is greater than that of the Z6 accretionary layer, conforming to the “gentle progradation” model of accretionary layers in fluvial facies deposition, it can be judged that both wells have encountered the same accretionary layer (Figure 9).
2. Quantitative Characterization of the 3rd-Level Architecture Bounding Surfaces
In the vertical flow direction, the aggradation layers are approximately horizontal and extend laterally no more than the point bar boundaries. Lateral accretion layers exhibit a shingled pattern, tilting away from the active channel. In the downstream direction, the aggradation layers slope downstream, with some extending beyond a well spacing. Lateral accretion layers also display a shingled pattern, tilting away from the active channel, with some appearing dome-shaped [38,39]. Studies indicate that the aggradation layer width ranges from 300 to 450 m, with an average of 380 m; the length varies from 400 to 600 m, averaging 580 m; thickness ranges from 0.3 to 0.7 m, with a dip of 0–0.4°; and lateral accretion layer thickness ranges from 0.3 to 0.7 m, with a dip of 3–6°.

4.4. The Controlling Role of Architecture Bounding Surfaces on Remaining Gas and Its Enrichment Types

Study on the control of architecture bounding surfaces (partitioning layers) on remaining gas distribution in tight sandstone reservoirs: as gas reservoir development progresses into the middle to late stages, the distribution of remaining gas is influenced by multiple factors [40]. In this particular region, the fluvial facies tight sandstone reservoirs are characterized by well-developed interlayers, which play a pivotal role in controlling the distribution of remaining gas. Consequently, this study concentrates on the reservoir architecture bounding surfaces, specifically the interlayers, and their influence on remaining gas distribution, reflecting real-world gas field development scenarios. These interlayers, categorized by different orders, comprise varying proportions of sandstone and mudstone, each with distinct distributional patterns and thicknesses. Such variations result in differing levels of gas impedance and enrichment. Previous research on the Sulige Gas Field has identified the presence of 5th- to 3rd-order interlayers, with the 4th- and 3rd-order interlayers—particularly within smaller stratigraphic layers—exerting the most pronounced impact on late-stage production.

The Role of Reservoir Architecture Bounding Surfaces on Remaining Gas

1. The controlling effect of the 4th-level architecture bounding surfaces on remaining gas.
The fourth-order boundary mudstone interlayers and sandstone transition zones play a pivotal role in governing gas migration between individual sand bars, effectively preventing both upward flow and lateral escape (Figure 10). In the studied region, characterized by its low-porosity, ultra-low permeability tight sandstone reservoirs, gas encountering these low-permeability or impermeable interlayers during ascension is compelled to migrate laterally beneath such barriers. Additionally, lateral boundary obstructions further impede the efficient extraction of gas trapped beneath these interlayers. The thickness and lateral continuity of these interlayers underscore their capacity as barriers, significantly diminishing gas-phase permeability and obstructing gas seepage. In the study area, the fourth-order boundary interlayers are notably thick and extensive, leading to considerable remaining gas accumulation beneath them (Figure 11).
2. The control effect of the 3rd architecture bounding surfaces on the remaining gas.
Braided river channel bars serve as exceptional reservoirs, distinguished by the extensive horizontal distribution of silt layers (Figure 10). These fine-grained and unstable layers act as formidable barriers to vertical gas flow, complicating gas extraction efforts in certain regions and leading to the accumulation of remaining gas. Furthermore, the presence of these silt layers can elevate gas concentrations in specific areas, forming localized enrichment zones. The vertical control imposed by the silt layers forces gas to migrate horizontally along these barriers, culminating in an enrichment zone on the left side of the channel bar.
Point bar deposits in meandering rivers, shaped by periodic flood events, are inclined and exhibit suboptimal physical properties. These deposits exert significant control over lateral gas migration, with the presence of lateral barriers impeding gas flow and causing partial obstruction. As a result, remaining gas tends to accumulate near these bounding surfaces (Figure 11).

4.5. Types and Exploitation Measures of Remaining Gas Enrichment

Based on the understanding of reservoir architecture bounding surfaces discussed above, this paper utilizes the Petrel 2018 software platform to establish a three-dimensional geological model of the multi-level architectural units in the study area using a hierarchical embedding method [40] (Figure 10). Numerical reservoir simulation studies [41,42,43] were also conducted. The remaining gas in the area is classified into three types: bounding surfaces-controlled remaining gas influenced by reservoir architecture bounding surfaces, remaining gas not controlled by the well pattern, and remaining gas in unperforated single layers (Table 2).

4.5.1. Bounding Surfaces-Controlled Remaining Gas

Bounding Surfaces-controlled remaining gas, influenced by reservoir architecture bounding surfaces, accounts for 60% of the remaining gas volume in the study area, making it the largest proportion. This type of remaining gas is primarily exploited through techniques such as refracturing, infill drilling of vertical wells, and sidetracking of existing wells (Figure 12①,②).

4.5.2. Well Pattern Uncontrolled Remaining Gas

Well pattern uncontrolled remaining gas is due to the limitations in the distribution scale of effective sand bodies, making it difficult for the basic well pattern to effectively control the gas. Considering the well spacing of horizontal and vertical wells in the study area, this type of remaining gas can be divided into two scenarios: Firstly, the remaining effective sand bodies between wells that are not controlled by the vertical well pattern spacing (500 × 650 m). Considering economic factors, the primary exploitation method is sidetracking of vertical wells. Secondly, due to the multi-layered gas presence in the study area, earlier horizontal wells were mainly deployed in the H8 section, with fewer horizontal wells in the S1 section. Moreover, horizontal wells only control 1–2 individual layers. For this situation, future horizontal wells will primarily be deployed in the Shan1 section to exploit the remaining gas (Figure 12③).

4.5.3. Unperforated Single-Layer Remaining Gas

During the early development phase of the area, due to considerations of development costs, perforation was not conducted in the poorer gas-bearing formations. However, as the production capacity of older wells continuously declines, this type of remaining gas has become a primary method for increasing production in older wells. It is primarily exploited through the method of formation evaluation and reperforation (Figure 12④).

4.6. Prediction of Development Effectiveness in the Study Area

Based on our comprehensive research findings, we have forecasted the recoverable reserves within the study area. The analysis reveals a notably high well control density of 3.3 wells per square kilometer. Over time, the formation pressure has exhibited a gradual decline, descending from an initial 29.8 MPa to the current 20.2 MPa (Figure 13a), which equates to a 32.2% reduction. The average annual rate of pressure decline is calculated at 0.6 MPa per year, with a corresponding gas production rate of 220 million cubic meters per MPa of pressure drop.
The actual cumulative gas production from the wells has reached 2.15 billion cubic meters, aligning closely with the fitted cumulative production figure of 2.12 billion cubic meters. Presently, the daily production rate stands at 600,000 cubic meters per day. Should this production rate be sustained until the year 2039 (Figure 13b), the projected final cumulative production is anticipated to be 3.13 billion cubic meters, corresponding to a recovery factor of 40.7%. This high recovery rate underscores the effective development and management of the gas reservoir.

4.7. Application Examples

In 2024, based on the research findings, four vertical wells and three horizontal wells in the S1 section were deployed (Figure 13c). The density of the vertical well pattern was improved to 3.0 wells/km², with one vertical well drilled. It is predicted to control geological reserves of 0.38 billion cubic meters, with an estimated ultimate recovery (EUR) of 21.1 million cubic meters. The well encountered a gas-bearing layer of 14.8 m, with a gas-bearing layer thickness of 6.2 m, and a non-restricted gas flow rate during testing of 89,000 cubic meters per day. Currently, one horizontal well has been drilled, with an average horizontal section length of 1075 m, a reservoir penetration rate of 96.6%, and an effective penetration rate of 61.7%. The non-restricted gas flow rate during testing was 811,000 cubic meters per day, confirming the presence of substantial remaining gas in the S1 section.

5. Discussion

Currently, the quantitative characterization of architecture bounding surfaces in fluvial tight sandstone reservoirs and their control on remaining gas is still in the exploratory stage. Previous research has mostly focused on the quantitative characterization of fourth-order architectural units and their control on remaining gas [7]. Building on this, we further conducted quantitative studies on third-order architecture bounding surfaces to investigate their control on remaining gas. However, given the complex spatial structure of tight sandstone reservoirs influenced by geological and development factors, several issues must be considered in quantitative studies of architecture bounding surfaces and their control on remaining gas: (i) When dissecting the architecture of fluvial tight sandstone reservoirs, the depiction of architecture bounding surfaces is highly speculative in areas without horizontal well drilling, especially given the varying geological data across different blocks and the large well spacing. (ii) In multilayer thin interbedded deposits of tight sandstone reservoirs at mid- to late development stages, the presence of third-order architectural units within sand bodies is crucial for obstructing gas flow [8]. Therefore, the three-dimensional characterization of third-order bounding surfaces is particularly important. However, the stochastic nature of three-dimensional geological modeling introduces significant uncertainty in the characterization of third-order architecture bounding surfaces. (iii) For tight sandstone gas reservoirs at mid- to late development stages, the distribution of remaining gas is extremely complex with numerous controlling factors. Formulating precise exploitation strategies is key to enhancing recovery [38]. Nonetheless, under different depositional settings, strategies for remaining gas exploitation based on architectural bounding surfaces studies still require further exploration and practice.
Therefore, future work should focus on utilizing geological data from the study area to conduct quantitative research on reservoir architecture bounding surfaces, improving modeling accuracy. Exploring the control of reservoir architecture bounding surfaces on remaining gas under different depositional settings and formulating tight gas reservoir exploitation strategies based on these bounding surfaces are essential for enhancing recovery rates. This represents one of the key future development directions.

6. Conclusions

(1) Research and application in the H8 and S1 sections of the fluvial tight sandstone reservoirs in the Central Sulige Block indicate that when gas field development enters the middle to later stages, conducting studies on reservoir architecture bounding surfaces within sand bodies can effectively delineate the distribution of shale intercalations. This lays the foundation for studying the characteristics of remaining gas distribution and enhancing recovery rates.
(2) In the H8 and S1 sections of the Central Sulige Block, fluvial tight sandstone reservoirs primarily develop six types of reservoir architectural elements: braided channels, active channels, channel bars, point bars, crevasse splay, and floodplain. Based on Miall’s architectural theory and research on remaining gas, the architecture bounding surfaces in the study area are classified into three levels: Level 5 bounding surfaces, which are the boundaries of individual channels (braided/meandering zones); Level 4 bounding surfaces, which are the boundaries of channel bar or braided channel/point bar or active channel fills; and Level 3 bounding surfaces, which are the individual accretionary bodies within channel bars or lateral accretion bodies within point bars.
(3) Through comprehensive analysis of horizontal well logging, cuttings logging, and gas logging data, three lateral boundary combination patterns for braided river horizontal wells were established: channel bar–braided channel–channel bar, channel bar–shale channel–channel bar, and channel bar–braided channel–floodplain. Additionally, three lateral boundary combination patterns for meandering river horizontal wells were identified: point bar–active channel–point bar, point bar–active channel, and point bar–floodplain.
(4) Research on the architecture bounding surfaces of fluvial tight sandstone reservoirs and their control over remaining gas has shown that Level 4 and Level 3 architecture bounding surfaces significantly impede gas migration. By employing three-dimensional architectural modeling and numerical simulation methods, based on well network control and technological maturity, remaining gas is classified into three types: bounding surfaces-controlled remaining gas, well network uncontrolled remaining gas, and unperforated single layer remaining gas. Based on the understanding of remaining gas distribution, corresponding exploitation measures have been proposed, laying the foundation for further exploitation of remaining reserves and development decision-making in gas fields.

Author Contributions

Conceptualization and methodology, X.L. and Q.C.; investigation, J.L. and F.L.; data curation, Y.L. and L.J.; writing—original draft preparation, B.Z.; writing—review and editing, X.L. and Y.B. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by National Natural Science Foundation of China (No. 42172154) and the Applied Scientific and Technological Research Project of China National Petroleum Corporation (2023ZZ25-001).

Data Availability Statement

For confidentiality reasons, some of the data in the article cannot be publicly displayed. If you have data-related questions, you are welcome to contact the authors via email.

Conflicts of Interest

Authors Jinbu Li, Yuqi Bai and Fuping Li were employed by the company PetroChina Changqing Oilfield.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Geographic location and stratigraphic division of the study area. (a) Location map of the study area. (b) Well placement map of the study area. (c) Stratigraphic synthesis map.
Figure 1. Geographic location and stratigraphic division of the study area. (a) Location map of the study area. (b) Well placement map of the study area. (c) Stratigraphic synthesis map.
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Figure 2. Grain size frequency curve and probability cumulative curve of rocks in the study area.
Figure 2. Grain size frequency curve and probability cumulative curve of rocks in the study area.
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Figure 3. Thin sections under microscope in the study area; (a) Subangular grains, 3347.92 m, XPL; (b) Subrounded grains, 3350.5 m, XPL.
Figure 3. Thin sections under microscope in the study area; (a) Subangular grains, 3347.92 m, XPL; (b) Subrounded grains, 3350.5 m, XPL.
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Figure 4. Logging interpretation charts of various architectural units in the study area. (a) Braided channel, active channel, siltstone, horizontal bedding, 3355.5 m. (b) Channel bar, coarse sandstone, cross-bedding, 3333.8 m. (c) Point bar, medium-fine sandstone, cross-bedding, 3364.8 m. (d) Crevasse splay, siltstone, cross-bedding, 3351.8 m. (e) Floodplain, mudstone, horizontal bedding, 3331.8 m.
Figure 4. Logging interpretation charts of various architectural units in the study area. (a) Braided channel, active channel, siltstone, horizontal bedding, 3355.5 m. (b) Channel bar, coarse sandstone, cross-bedding, 3333.8 m. (c) Point bar, medium-fine sandstone, cross-bedding, 3364.8 m. (d) Crevasse splay, siltstone, cross-bedding, 3351.8 m. (e) Floodplain, mudstone, horizontal bedding, 3331.8 m.
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Figure 5. Reservoir architecture models for H8 and S1 in the study area. (a) Depositional model of reservoir architecture for the lower H8 braided river. (b) Depositional model of reservoir architecture for the upper H8 and S1 meandering river.
Figure 5. Reservoir architecture models for H8 and S1 in the study area. (a) Depositional model of reservoir architecture for the lower H8 braided river. (b) Depositional model of reservoir architecture for the upper H8 and S1 meandering river.
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Figure 6. Lateral boundary assemblage model for horizontal wells in the study area. (a) Braided river assemblage model. (b) Meandering river assemblage model.
Figure 6. Lateral boundary assemblage model for horizontal wells in the study area. (a) Braided river assemblage model. (b) Meandering river assemblage model.
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Figure 7. Architecture patterns of vertical wells in the study area. (a) Development of shale intercalations between single sandbars. (b) Plan view of Z1 and Z2 well architecture. (c) Slight reversal of curves between single sandbars. (d) Plan view of Z3 and Z4 well architecture.
Figure 7. Architecture patterns of vertical wells in the study area. (a) Development of shale intercalations between single sandbars. (b) Plan view of Z1 and Z2 well architecture. (c) Slight reversal of curves between single sandbars. (d) Plan view of Z3 and Z4 well architecture.
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Figure 8. Identification patterns of lateral boundaries for horizontal wells in the study area. (a) Interpretation of H1 horizontal well profile. (b) Single well interpretation of H1 horizontal well horizontal section.
Figure 8. Identification patterns of lateral boundaries for horizontal wells in the study area. (a) Interpretation of H1 horizontal well profile. (b) Single well interpretation of H1 horizontal well horizontal section.
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Figure 9. Identification patterns of level 3 intercalations in the study area. (a) Development of depositional layers within single sandbars. (b) Plan view of Z5 and Z6 well architecture.
Figure 9. Identification patterns of level 3 intercalations in the study area. (a) Development of depositional layers within single sandbars. (b) Plan view of Z5 and Z6 well architecture.
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Figure 10. Depositional facies model cross-section of the study area (along the source).
Figure 10. Depositional facies model cross-section of the study area (along the source).
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Figure 11. Gas saturation profile in the study area (along the source).
Figure 11. Gas saturation profile in the study area (along the source).
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Figure 12. Types of remaining gas enrichment (along the source). ①. Controlled by level 4 architecture bounding surfaces. ②. Controlled by level 3 architecture bounding surfaces. ③. Uncovered by well pattern. ④. Unperforated single layer.
Figure 12. Types of remaining gas enrichment (along the source). ①. Controlled by level 4 architecture bounding surfaces. ②. Controlled by level 3 architecture bounding surfaces. ③. Uncovered by well pattern. ④. Unperforated single layer.
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Figure 13. Reserves prediction maps of the study area. (a) Daily and cumulative gas production forecast; (b) Formation pressure forecast; (c) Production forecast for a newly deployed horizontal well.
Figure 13. Reserves prediction maps of the study area. (a) Daily and cumulative gas production forecast; (b) Formation pressure forecast; (c) Production forecast for a newly deployed horizontal well.
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Table 1. Stratigraphic division of fluvial facies sandbody structures in the study area.
Table 1. Stratigraphic division of fluvial facies sandbody structures in the study area.
Bounding Surfaces HierarchyArchitecture Bounding Surfaces TypeArchitecture Units
Level 5Floodplain Muddy BarrierSingle Channel
Level 4Dam Interlayer, Abandoned FillingCentral Bar, Marginal Bar, Braided Channel, Active Channel
Level 3Depositional Layer, Lateral Accumulation LayerCentral Bar Internal Accretion, Marginal Bar Inner Accumulation
Table 2. Types of remaining gas and exploitation measures.
Table 2. Types of remaining gas and exploitation measures.
Types of Remaining GasFormation CauseExploitation StrategyResearch Area Scale Prediction (%)
Bounding Surfaces-Controlled TypeLevel 4 and Level 3 Architectural Bounding Surfaces ControlOptimize Well Network, Conduct Refrac, Sidetrack Old Wells60%
Uncontrolled Well PatternUncontrolled by Vertical Well Network, Untapped in Multi-Layered SystemsIntensify Well Network, Deploy Various Horizontal Wells, Sidetrack Existing Wells30%
Unperforated Single LayerPreviously Poor Gas Logging Results, UnperforatedPerforation Enhancement10%
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Liu, X.; Li, J.; Liu, Y.; Chen, Q.; Bai, Y.; Li, F.; Jin, L.; Zhang, B. Characterization of Architecture Bounding Surfaces in Fluvial Tight Sandstone Reservoirs and Their Influence on Remaining Gas: A Case Study from the Suzhong Block, Sulige Gas Field. Energies 2024, 17, 4262. https://doi.org/10.3390/en17174262

AMA Style

Liu X, Li J, Liu Y, Chen Q, Bai Y, Li F, Jin L, Zhang B. Characterization of Architecture Bounding Surfaces in Fluvial Tight Sandstone Reservoirs and Their Influence on Remaining Gas: A Case Study from the Suzhong Block, Sulige Gas Field. Energies. 2024; 17(17):4262. https://doi.org/10.3390/en17174262

Chicago/Turabian Style

Liu, Xinqiang, Jinbu Li, Yuming Liu, Qi Chen, Yuqi Bai, Fuping Li, Lei Jin, and Bingbing Zhang. 2024. "Characterization of Architecture Bounding Surfaces in Fluvial Tight Sandstone Reservoirs and Their Influence on Remaining Gas: A Case Study from the Suzhong Block, Sulige Gas Field" Energies 17, no. 17: 4262. https://doi.org/10.3390/en17174262

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