Method for selecting optimal reservoir layer for building underground gas storage in multi-layer water-bearing gas reservoir

Abstract

The application discloses a kind of best construction layer position selection methods of multilayer water-containing gas reservoir underground gas storage, including the reservoir characteristics evaluation of each layer in target gas reservoir;The relationship between the lithology configuration relationship of the two sides of fault and fault mud ratio is used to analyze reservoir and cap system, and the change of three-dimensional stress field under injection-production pressure disturbance is evaluated;From the angle of production dynamics, the historical data of target gas reservoir are studied to analyze productivity, calculate water influx and gas-water ratio layer by layer, and finely depict and quantitatively characterize water influx dynamics, clear gas-water distribution and migration situation;Finally, comprehensive evaluation is carried out, and the best construction layer position is selected. From the aspects of reservoir geological characteristics and production dynamics, the target gas reservoir and its small layer are quantitatively analyzed and evaluated, and then the best target layer position can be relatively accurately selected, the operation effect of construction is better, the damage degree of oil ring is small, and the bottom water intrusion can be effectively blocked.

Description

Technical Field

[0001] This invention belongs to the field of gas storage construction technology, specifically relating to a method for selecting the optimal construction layer for an underground gas storage facility in a multi-layered water-bearing gas reservoir. Background Technology

[0002] Gas storage facilities are artificial gas fields or reservoirs formed by re-injecting commercial natural gas transported through long-distance pipelines into underground space. The site selection directly affects the quality of the gas storage facility, requiring comprehensive consideration of geological conditions, geographical location, and surrounding environment. Water-bearing gas reservoirs account for approximately 30% of all underground gas storage (UGS) types globally, playing a crucial role in natural gas storage and balancing natural gas supply and demand. Therefore, the site selection for water-bearing gas reservoirs is particularly important.

[0003] The applicant discovered in its research that existing technologies for selecting sites for underground gas storage facilities focus more on the general location of the storage facility. For example, patent application number "2023100328621," entitled "A Method for Screening and Evaluating Sites for Underground Gas Storage Facilities in Aquifers," mainly involves screening and evaluating indicators, classifying and registering these indicators, and finally conducting a comprehensive evaluation and selection. However, after a long history of production, multi-layered aquifer gas reservoirs exhibit complex and unclear horizontal and vertical gas and water distribution patterns, making existing site selection methods unsuitable for them. Therefore, this application proposes a method for selecting the optimal site location for underground gas storage facilities in multi-layered aquifer gas reservoirs, aiming to solve the problem of selecting the optimal site location within multi-layered aquifer gas reservoirs and fill a gap in this field. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the technical problem to be solved by the present invention is: how to provide a method for selecting the optimal construction layer of an underground gas storage facility in a multi-layered water-bearing gas reservoir, so as to solve the problem that the existing technology cannot quickly, standardly and accurately select the optimal construction layer in a multi-layered water-bearing gas reservoir.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] A method for selecting the optimal site location for underground gas storage in multi-layered water-bearing gas reservoirs, the key of which includes the following steps:

[0007] S1, evaluate the reservoir characteristics of each layer in the target gas reservoir, and compare and assess the connectivity and permeability of each layer;

[0008] S2, using the relationship between the lithological configuration on both sides of the fault and the fault gouge ratio to analyze the reservoir-capsule system and evaluate the changes in the three-dimensional stress field under injection-production pressure disturbance;

[0009] S3, from the perspective of production dynamics, studies the historical data of the target gas reservoir to analyze its production capacity, calculates the water intrusion and gas-water ratio layer by layer, and provides a detailed characterization and quantitative representation of the water intrusion dynamics to clarify the gas-water distribution and migration.

[0010] S4. Based on steps S1 to S3, a comprehensive evaluation is conducted to select the optimal database construction layer, and the feasibility of construction and operation of the selected optimal database construction layer is analyzed through numerical simulation.

[0011] Using the above approach, considering both reservoir geological characteristics and production dynamics, quantitative analysis and evaluation are conducted on each layer and sublayer of the target gas reservoir to ensure a clear understanding of each layer, thereby enabling the relatively accurate selection of the optimal target layer.

[0012] Preferably, the reservoir characteristics in step S1 include sedimentary characteristics, sand body distribution, interlayer distribution, lithology, and reservoir physical properties.

[0013] As a preferred option, step S2 assesses the sealing integrity of the target gas reservoir based on the static sealing integrity of the caprock, the static sealing integrity of the fault, and the dynamic sealing integrity of the trap.

[0014] As a preferred option, the static sealing integrity of the cap layer is evaluated by combining dynamic breakthrough pressure tests with fatigue tests.

[0015] Based on the geological information of the target gas reservoir, structural modeling, sedimentary facies modeling, and reservoir property modeling are performed to predict the distribution of well perimeter physical parameters and establish a comprehensive three-dimensional geological model of reservoir physical properties. The static sealing capacity of faults within the gas reservoir is evaluated by utilizing the lithological contact relationship between two fault blocks and the distribution of fault gouge ratio.

[0016] As a preferred option, the evaluation process for the dynamic closure integrity of a trap includes the following steps:

[0017] First, using the rock mechanics parameters obtained from experiments and the geostress data obtained from micro-fracture tests, combined with the three-dimensional geological model of reservoir properties, a three-dimensional geomechanical model is constructed.

[0018] Secondly, simulate gas reservoir development and injection-production operations to simulate fluid pressure changes;

[0019] Secondly, a dynamic geomechanical model is formed by analyzing the dynamic geostress field under injection-production disturbance through fluid-structure interaction simulation.

[0020] Finally, the ultimate bearing capacity of geological structures was assessed by combining dynamic stress fields with rock mechanics parameters.

[0021] As a preferred method: in step S3, the water drive index WEDI is calculated based on production dynamic data.

[0022] .

[0023] In the formula:

[0024] WEDI – Water Drive Index, a quantity with a dimension of 1;

[0025] W e - The cumulative water inundation volume, in ten thousand cubic meters;

[0026] G p - Cumulative gas production figures, in ten thousand cubic meters;

[0027] W p - Cumulative water production, in ten thousand cubic meters;

[0028] B g - Natural gas volume factor, a dimensionless quantity;

[0029] B w - Formation water volume factor, dimensionless.

[0030] As a preferred option, step S3 includes the evaluation of water energy in each layer of each block of the target gas reservoir, the detailed characterization of water intrusion dynamics, and the quantitative characterization of water intrusion dynamics.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] The optimal site selection method for multi-layered water-bearing gas reservoirs provided by this invention starts from two aspects: reservoir geological characteristics and production dynamics. It quantitatively analyzes and evaluates each layer and sublayer of the target gas reservoir to ensure that the conditions of each layer are clear and understandable. This allows for the relatively accurate selection of the optimal target layer, resulting in better reservoir construction and operation, less damage to the oil ring, and effective prevention of bottom water intrusion. This method has good guiding reference value for reservoir construction. Attached Figure Description

[0033] Figure 1 A schematic diagram of the planar and longitudinal distribution of the M oil and gas reservoir (where (a) is a planar structural diagram; (b) is a longitudinal sectional view).

[0034] Figure 2 The effective thickness of each sand body and gas layer within the block;

[0035] Figure 3 A statistical analysis chart of the average core porosity of each sand group within the block;

[0036] Figure 4 A statistical analysis chart of the average core permeability of each sand group within the block;

[0037] Figure 5 A statistical analysis chart of the average core porosity of each sublayer;

[0038] Figure 6A statistical analysis chart of the average core permeability of each sub-layer;

[0039] Figure 7 A statistical chart showing the compressive strength test results of caprock mudstone at different fatigue cycles;

[0040] Figure 8 A schematic diagram simulating the SGR values ​​of faults within the reservoir area to be constructed (where (a) is the SGR distribution map of the fault at boundary A; (b) is the SGR distribution map of the fault at boundary B; and (c) is the SGR distribution map of the fault at boundary C).

[0041] Figure 9 A three-dimensional geomechanical model of rock mechanical parameters - showing compressive strength;

[0042] Figure 10 A three-dimensional geomechanical model of rock mechanical parameters - showing tensile strength;

[0043] Figure 11 Four rock samples were taken from well MB121;

[0044] Figure 12 Schematic diagram of the compressive strength of light gray fine sandstone and gray medium sandstone under different fatigue cycles;

[0045] Figure 13 Diagram showing the equilibrium zone division of layer I-2;

[0046] Figure 14 Diagram showing the equilibrium zone division of layer I-6;

[0047] Figure 15 This is a cross-sectional view comparing the I-2 sublayer of the M8 block before and after water intrusion.

[0048] Figure 16 Comparative cross-sectional views of sublayers I-6 and II-1 in block M14 before and after water intrusion;

[0049] Figure 17 A profile of gas saturation at the end of steam injection and gas production in Block M8.

[0050] Figure 18 A profile of gas saturation at the end of steam injection and gas production in Block M14.

[0051] Figure 19 A diagram showing the gas storage injection and extraction cycle;

[0052] Figure 20 The diagram shows the changes in the gas-water interface in the I-2 and I-6 sublayers, where (a) corresponds to the original gas-water distribution; (b) corresponds to the gas-bearing distribution during water-bearing gas production; and (c) corresponds to the gas-bearing distribution during drainage gas production.

[0053] Figure 21This is a schematic diagram of fluid transport in the II-1 sublayer. Detailed Implementation

[0054] The present invention will now be described in further detail with reference to the accompanying drawings.

[0055] refer to Figures 1 to 21 The optimal site selection method for underground gas storage in multi-layered water-bearing gas reservoirs, as shown, mainly includes the following steps:

[0056] The first step is to evaluate the reservoir characteristics of each layer in the target gas reservoir, and compare and assess the connectivity and permeability of each layer.

[0057] The second step involves analyzing the reservoir-capsule system by utilizing the relationship between the lithological configuration on both sides of the fault and the fault gouge ratio, and assessing the changes in the three-dimensional stress field under injection-production pressure disturbances.

[0058] The third step involves analyzing the production capacity of the target gas reservoir from a production dynamics perspective by studying historical data, calculating water intrusion and gas-water ratio layer by layer, and finely characterizing and quantitatively representing the water intrusion dynamics to clarify the gas-water distribution and migration.

[0059] The fourth step is to conduct a comprehensive evaluation based on the first three steps, select the optimal database layer, and analyze the feasibility of constructing and operating the selected optimal database layer through numerical simulation.

[0060] Specifically, the first step mainly focuses on the geological characteristics, paying particular attention to the sedimentary features in different regions. It comprehensively utilizes logging, well testing, analytical testing, and core observation data to identify the source, transport, and depositional processes of sediments. It analyzes the sedimentary features, sand body distribution, interlayers, lithology, and reservoir properties of each layer, and then compares and evaluates the connectivity and permeability of each layer to assess the development and storage capacity of the reservoir. It identifies the potential impact of interlayers on vertical and lateral connectivity and compares the reservoir properties in different regions, especially porosity and permeability, to directly assess the gas storage capacity of the reservoir.

[0061] In the second step, based primarily on the results of triaxial fatigue tests on the caprock shale, the reservoir-caprock system is analyzed using the relationship between the lithological configuration on both sides of the fault and the fault gouge ratio. The changes in the three-dimensional stress field under injection-production pressure disturbance are assessed, and then the sealing integrity of the target gas reservoir is comprehensively evaluated from three aspects: the static sealing integrity of the caprock, the static sealing integrity of the fault, and the dynamic sealing integrity of the trap.

[0062] In practical implementation, the main evaluation objects of sealing integrity include caprock, faults, and spillway points. This method primarily employs microscopic quantitative assessment to evaluate the sealing capacity of the caprock under cyclic loading to determine its durability. Specifically, the static sealing integrity of the caprock is evaluated mainly through dynamic breakthrough pressure tests combined with fatigue tests. That is, after the rock undergoes fatigue testing, its breakthrough pressure is measured, and the rock's mechanical parameters are calculated. The main rock mechanical parameters involved in this embodiment include elastic parameters and strength parameters. The elastic parameters mainly consist of the elastic modulus and Poisson's ratio, while the strength parameter is tensile strength.

[0063] Among them, dynamic elastic modulus (E) d The calculation method for ) is as follows:

[0064]

[0065] In the formula, E d ρ is the dynamic elastic modulus, MPa; ρ is the rock density, kg / m³. 3 Δtp and Δts are the P-wave time difference and S-wave time difference, respectively, in μs / ft. By establishing the relationship between P-wave and S-wave, the S-wave time difference data of all wells are calculated.

[0066] For all isotropic materials, the value of Poisson's ratio is between 0 and 0.5. The formula for interpreting Poisson's ratio in well logging is as follows:

[0067]

[0068] Uniaxial compressive strength (UCS) and elastic modulus of sandstone and mudstone, as well as mud content (V) of the rocks. sh The relationship between them can be described as follows:

[0069]

[0070] Furthermore, in the Coulomb-Moore criterion, cohesion (ἐ) is a constant related to the material's shear strength (Ἇ). Its calculation formula is as follows:

[0071]

[0072] In the formula It is the internal friction angle in the Coulomb-Moore model. It is the normal stress measured during the experiment.

[0073] The Mohr circle method is a commonly used technique for calculating the internal friction angle. It is based on the shear stress and normal stress data obtained from different shear tests to draw the Mohr circle.

[0074]

[0075] σ1 and σ2 are the minimum and maximum normal stresses measured during the experiment.

[0076] Fault sealing performance is directly related to the risk of leakage in the later stage of gas storage. In this embodiment, the assessment of fault static sealing performance is mainly based on the geological information of the target gas reservoir. It utilizes sedimentary microfacies knowledge, geostatistical principles and reservoir modeling technology to perform structural modeling, sedimentary facies modeling and reservoir property modeling to predict the distribution of well perimeter physical parameters and establish a comprehensive three-dimensional geological model of reservoir physical properties. Secondly, the lithological contact relationship between the two fault blocks and the distribution of fault gouge ratio (SGR) are used to assess the static sealing capacity of faults within the gas reservoir.

[0077] At each point on the fault, the SGR is calculated by determining the mud content of the rock that slipped across that point on the fault. The calculation formula is as follows:

[0078]

[0079] In the formula, △Z and V sh D and D represent the thickness of the stratigraphic zone (m), the percentage of clay content in the stratigraphic zone (%), and the fault displacement (m), respectively.

[0080] The critical value of SGR, representing fault sealing or non-sealing, is 15% to 20%. When SGR < 15% to 20%, it corresponds to typical breccia or rock disintegration zones, which do not have a sealing effect on oil and gas. When SGR > 50%, it is mudstone smear, and the intermediate components refer to mudstone framework fault gouge or layered silicate framework fault gouge, which indicates that its sealing performance is relatively good.

[0081] In this embodiment, the assessment of the dynamic sealing integrity of the trap mainly includes the following steps: First, a three-dimensional geomechanical model is constructed using rock mechanics parameters obtained from experiments and geostress data obtained from micro-fracture tests, combined with a three-dimensional geological model of reservoir properties; second, gas reservoir development and injection-production operations are simulated to simulate fluid pressure changes; third, the dynamic geostress field under injection-production disturbances is analyzed through fluid-structure interaction simulation to form a dynamic geomechanical model; finally, by combining the dynamic stress field with rock mechanics parameters, the ultimate bearing capacity of key geological structures (caprock, fault, and spillway) is assessed, thereby providing accurate insights into structural integrity and sealing capacity under reservoir operation conditions.

[0082] In the third step, the water drive index (WEDI) is calculated primarily based on production dynamic data. Combining the WEDI with the water drive index allows for the assessment of water energy in each layer of each block within the target gas reservoir, a detailed characterization of water intrusion dynamics, and a quantitative representation of water intrusion dynamics. Among these steps...

[0083] (1)

[0084] In the formula:

[0085] WEDI – Water Drive Index, a dimensionless quantity; W e - The cumulative water inundation volume, in ten thousand cubic meters; G p - Cumulative gas production, in tens of thousands of cubic meters; W p - Cumulative water production, in tens of thousands of cubic meters; B g - Natural gas volume factor, a dimensionless quantity; B w - Formation water volume factor, dimensionless.

[0086] In the third step, when calculating water intrusion and gas-water ratio layer by layer in the numerical simulation, based on the results of refined 3D geological modeling, the grid and attribute data are systematically coarsened to generate a 3D structural and attribute model suitable for numerical simulation. Furthermore, equilibrium zones and historical data fitting are specifically defined to facilitate accurate characterization of gas-water distribution and water intrusion dynamics in each sub-layer. During gas reservoir development, a production method of single-well layer-by-layer development, prioritizing oil production, followed by gas production, top-return wells, water injection for oil recovery, and drainage for gas production is adopted, leading to significant challenges in historical data fitting. To address these characteristics, production control methods are used in combination during oil production, gas production, and water production, with fitting performed by well area, layer system, and well stage to ensure the model accurately represents reservoir dynamics.

[0087] Then, the aquifer characteristics are simulated and characterized using a historically fitted numerical simulation model, the water-drive energy is comprehensively evaluated, and the water intrusion dynamics are quantitatively analyzed. This includes identifying the water intrusion direction, calculating the current average gas-water interface, determining key parameters such as the water intrusion area, volume, and rate of each sublayer, and further optimizing favorable reservoir sites by assessing the flooding degree and bottom water energy of each sublayer.

[0088] The fourth step of this application is essentially to conduct a comprehensive assessment based on reservoir characteristics, sealing integrity, and gas-water flow characteristics to select the optimal reservoir site. Then, the feasibility of construction and operation of the selected optimal reservoir site is analyzed through numerical simulation. In practice, this process mainly includes scheme design, capacity and production analysis, and water production prediction. Finally, based on the analysis and prediction, relevant conclusions on the feasibility of reservoir site selection are obtained.

[0089] refer to Figures 1 to 21 The optimal site selection method for underground gas storage in multi-layered water-bearing gas reservoirs, as shown, is applied to the site selection of underground gas storage in the M oil and gas reservoir. The specific process is as follows:

[0090] The M oil and gas reservoir belongs to Haixi Prefecture, Qinghai Province. The block as a whole belongs to a braided fluvial sedimentary system, with reservoir depths ranging from 1270 to 1380 m. The reservoir structure is as follows: Figure 1 As shown, according to the statistical analysis data of core physical properties, the porosity of the reservoir is mainly between 15% and 25%, and the permeability is mainly between 5 and 500 × 10⁻⁶. -3 μm 2Overall, it belongs to the medium-porosity, high-permeability reservoir category. The block comprises four well areas: M8, M14, M15, and M3. The reservoir conditions are shown in Table 1. As the table shows, blocks M8 and M14 have good reservoir properties, large thickness, and account for 98% of the reserves. M15 and M3 have smaller reserves and are geographically distant, so they are not considered for now. Therefore, the evaluation will primarily focus on blocks M8 and M14.

[0091] Table 1. Reservoir Condition Evaluation for Each Well Area

[0092]

[0093] The oil and gas reservoir exhibits the characteristic of each layer being a separate sandstone group, a separate oil-gas-water interface, and a separate gas reservoir in the vertical direction. Therefore, it is divided into three sand groups: Sand Group I, Sand Group II, and Sand Group III. Sand Group I is further subdivided into 7 sub-layers, Sand Group II into 2 sub-layers, and Sand Group III into 3 sub-layers. The specific petrophysical conditions of each layer group are shown in Table 2. At the same time, according to calculations, the average porosity of sub-layers I-2 and I-6 and sub-layer II-1 are 23.4%, 23.6%, and 21.6%, respectively, and the average permeability are 168.5×10-3μm2, 437.3×10-3μm2, and 476.9×10-3μm2, respectively.

[0094] Table 2. Physical conditions of rocks in each layer

[0095]

[0096] Since blocks M8 and M14 contain the same stratigraphic units, their reservoir characteristics are basically the same, and the specific evaluation is as follows:

[0097] 1) Regarding sedimentary characteristics

[0098] Within the corresponding block, from north to south, the interbedded layers of channels and point bars result in poor vertical continuity of the sand bodies, while lateral superposition forms continuous sand sheets. Layer III is mainly characterized by channels and floodplains, with poorly developed point bars, narrow channels, and predominantly lenticular sand bodies interbedded with sand and mud layers, exhibiting poor lateral continuity. Layer II is dominated by point bars and channel deposits, with wide channels, well-developed point bars, and thick, box-shaped sand bodies exhibiting good lateral continuity. Layer I is characterized by interbedded layers of channels and floodplain deposits interbedded with sand and mud layers. During the deposition of layers 2 and 6, well-developed point bars and shoals ensured good connectivity of the sand bodies.

[0099] 2) Sand body distribution

[0100] Effective thickness of sand bodies and gas layers, such as Figure 2As shown, the sand bodies in layers I-2, I-6, II-1, and II-2 are horizontally continuous, covering the entire reservoir area, and are relatively thick; the other sand bodies are horizontally discontinuous and relatively thin. In oil group I, the sand bodies in each layer are of medium thickness, few in number, and have poor connectivity; oil group II consists of a thick sand body with good horizontal connectivity; oil group III has thin sand bodies in each layer, a large number of layers, and poor horizontal connectivity.

[0101] 3) Distribution of interlayers

[0102] The interlayers between layers 1-2 and I-6 in the two well areas are stably distributed, with sandstone lenses developed locally, with an average thickness of 40.8m; the interlayer between layers 1-2 and I-6 in well M8-1 is 33.3m thick, slightly less than that of the adjacent well.

[0103] 4) Rock physical properties

[0104] Statistical analysis based on porosity and permeability ( Figures 3-6 The reservoir properties of layers I and II are significantly better than those of layer III. Specifically, layers I-2, I-6, and II-1 have higher porosity and permeability values ​​than other layers, indicating that these layers have the highest reservoir quality. This distribution highlights the variability of reservoir properties among different layers and underscores the importance of optimizing reservoir development and utilization for these layers with better properties.

[0105] The geological sealing (sealing integrity) assessment and analysis process for the target gas reservoir (M oil and gas reservoir) is as follows:

[0106] 1) Assessment of the static sealing integrity of the cap layer

[0107] The M gas reservoir is overlain by a thick layer of mudstone, serving as the main caprock in the area. Interlayer physical property analysis using lithology similar to the reservoir section revealed that the permeability of the brown mudstone is less than 0.05 mD, confirming its effectiveness as a sealing unit.

[0108] Breakthrough pressure tests on mudstone interlayer samples showed that, before fatigue, the breakthrough pressure ranged from 5.0 MPa to 11.1 MPa, indicating high breakthrough pressure and strong sealing ability. Triaxial fatigue tests on the M8 caprock mudstone showed that after 1000 fatigue cycles under pressures of 8–12.8 MPa, the mechanical properties of the caprock were unaffected (Table 3 and...). Figure 7 In summary, the cover layer in the reservoir area is horizontally continuous, thick, has poor permeability, high fatigue strength, and good sealing performance.

[0109] Table 1. Triaxial fatigue test results of caprock mudstone

[0110]

[0111] 2) Assessment of the static sealing integrity of the cap fault

[0112] Based on the actual conditions of the reservoir construction area, a three-dimensional geological model was established using designed grid units and scales (see Table 4). The geological static sealing performance of faults within the reservoir construction area was evaluated using the lithological connection relationship between the two sides of the fault and the distribution of fault gouge ratio (SGR). Evaluation results based on existing data indicate that the boundary faults generally have higher SGR values ​​in the reservoir construction section. Figure 8 The internal fault displacement is small, the sand body is not completely broken, the SGR value of the reservoir section is low, the sealing performance is poor, and the internal connectivity is not affected.

[0113] Table 4. Grid Units and Scales of 3D Geological Model

[0114]

[0115] 3) Assessment of the dynamic closure integrity of the trap

[0116] The main steps include: ① Establishment of a three-dimensional geomechanical model

[0117] Using rock mechanics parameters obtained from laboratory experiments and geostress parameters obtained from micro-fracture tests as references, and based on existing three-dimensional geological models, a three-dimensional geomechanical model of the M8 block was established, such as... Figure 9 and Figure 10 As shown in the simulation results, the direction of the minimum horizontal principal stress is along the northwest-southeast direction, and the magnitude ranges from 23.1 to 25.8 MPa.

[0118] ② Assessment of ultimate pressure bearing capacity

[0119] According to the Coulomb-Moore criterion, the ultimate shear failure bearing capacity of the caprock was calculated to be 25.3 MPa. After applying a safety factor of 80%, the safe bearing capacity was determined to be 20.4 MPa. The results of the fault stability analysis are shown in Table 5.

[0120] Table 5. Stability Analysis Results of Faults in the Reservoir Area

[0121]

[0122] The results show that after multiple injection and production cycles, the safe bearing capacity of the A boundary fault is 16.6 MPa, the B boundary fault is 14.6 MPa, the C boundary fault is 17.3 MPa, and the internal faults range from 18.9 to 22.9 MPa. In summary, the minimum safe bearing capacity of the fault is 14.6 MPa.

[0123] ③ Rock mechanics experiments

[0124] The experiment was conducted using a triaxial compression testing system. The experimental temperature was maintained between 20.3 and 21.5°C. The sample was taken from well MB121 and was a natural, intact core without structural surfaces or weathering. Figure 11 The sample had a diameter of 25.93 mm and a height of 52.53 mm, with the loading direction perpendicular to the rock sample. During the experiment, an initial axial load of 1 kN was applied, followed by axial loading up to 30 kN at a rate of 10 kN / min. Subsequently, circumferential strain was applied at a rate of 0.03 mm / min until failure occurred.

[0125] The experimental structure is shown in Table 6. The cohesion of sample 1 is 6.53 MPa, and the internal friction angle is 43°. ° The cohesive strength of sample 2 was 22.36 MPa, and the internal friction angle was 24°. ° The cohesive strength of sample 3 is 2.21 MPa, and the internal friction angle is 42°. ° The cohesive strength of sample 4 is 6.58 MPa, and the internal friction angle is 35°. ° .

[0126] Table 2 Results of triaxial compression experiments

[0127]

[0128] Furthermore, comparing the compressive strength of light gray fine sandstone and gray medium sandstone under different fatigue cycle numbers, the experimental results are as follows: Figure 12 As shown, the results indicate that the rock mechanical properties of the reservoir sandstone remained almost unchanged after 1000 fatigue cycles within a pressure range of 8 to 12.8 MPa. This demonstrates that the sandstone maintains its structural integrity and mechanical properties even after extensive cyclic loading.

[0129] The process of evaluating and analyzing the gas and water distribution and migration of the initially screened blocks (M8 and M14) is as follows:

[0130] Based on on-site geological data, fault blocks are well-developed in the plane of blocks M8 and M14, with slight differences in the oil, gas, and water interfaces between different fault blocks and different strata. In light of these characteristics, the blocks are divided into 24 equilibrium zones. Figure 13 and Figure 14 As shown in the figure), assign values ​​respectively.

[0131] Meanwhile, considering the numerous fault blocks and stratigraphic layers in blocks M8 and M14, and the complex distribution of oil, gas, and water phases in the reservoirs, and given the production process employing a single-well, layer-by-layer development approach—oil first, then gas, with top-level refilling, water injection for oil recovery, and drainage for gas production—fitting the historical data is challenging. To address these structural and production characteristics, a combination of oil control during the oil recovery period, gas control during the gas recovery period, and liquid control during the water production period was used, with fitting performed by well area, stratigraphic layer, and well stage. Block M8 is a gas reservoir, with most production wells producing both gas and water simultaneously; therefore, based on the differences in the main fluid types in the main wells, a control method combining constant gas production and constant liquid production was adopted to fit the full-cycle production history of each gas well. In some producing formations (I-5, II-1) of Block M14, oil, gas and water coexist. Therefore, the production wells in this area adopt a well-by-well and stage-by-stage approach in the fitting process. According to the different types of main fluids in different production stages of each production well, the production history is fitted by reasonably selecting the fixed gas production, fixed oil production and fixed liquid production methods throughout the entire production stage.

[0132] Specifically as follows:

[0133] (1) M8 block

[0134] 1) Water body energy assessment

[0135] The aquifer volume of Block M8 was calculated using a numerical model fitted with historical full-lifecycle production data. The water drive index was calculated using formula (1). The water drive indices of the main producing layers in Block M8 were 0.02, 0.10, and 0.28, respectively. From top to bottom, the water drive index gradually increased, ranging from weak water drive to moderate water drive. The evaluation results are basically consistent with the current flooding status of each layer.

[0136] Table 7 Comprehensive Evaluation of Water Drive Energy in Block M8 Gas Reservoir

[0137]

[0138] 2) Detailed depiction of water intrusion dynamics

[0139] The overall production history of the area shows that the gas production capacity and extraction efficiency of water-bearing gas wells have significantly decreased. In Block M8, daily gas production decreases with a stepwise increase in water production. The direction of edge and bottom water intrusion is related to reservoir property distribution, pressure drop direction, and well structural location, such as... Figure 15 As a medium-porosity, high-permeability reservoir, the M8 block has good porosity and permeability, and water intrusion is mainly controlled by the direction of pressure drop.

[0140] 3) Quantitative characterization of water intrusion dynamics

[0141] Quantitative calculations were performed on the flooding of each sublayer in block M8, and the results are shown in Table 8. Layer I-2 exhibited the least flooding, with an average edge water intrusion distance of 75 m and an intrusion rate of 0.12 m / d in the eastern block, compared to 81 m and 0.90 m / d in the western block. Layer I-6 showed moderate flooding, with an average edge water intrusion distance of 130 m and an intrusion rate of 0.17 m / d. Layer II-1 showed significant flooding, with an average bottom water rise height of 28 m and a rise rate of 3.03 m / a. Based on the analysis of flooding degree and bottom water energy, layers I-2 and I-6 showed significant reservoir building potential, while layer II-1 had limited reservoir building potential.

[0142] Table 8. Quantitative Calculation Results of Water Intrusion in Each Sublayer of Block M8

[0143]

[0144] (2) Block M14

[0145] 1) Water body energy assessment

[0146] Calculations show that layers I-2 and I-6 exhibit moderate to weak water-drive characteristics, while layer II-1 exhibits stronger water-drive characteristics. The evaluation results are consistent with the current flooding status observed in each layer (Table 9).

[0147] Table 9. Comprehensive Evaluation of Water Drive Energy in Gas Reservoir of Block M14

[0148]

[0149] 2) Detailed characterization of water intrusion dynamics

[0150] The development dynamics of Block M14 indicate that continuous development has led to formation water intrusion into the gas-bearing reservoir, damaging its integrity and weakening its ability to block bottom water. This results in co-production of gas and water, thus affecting reservoir recovery efficiency. Simultaneously, with the stepwise increase in water production, the daily gas production across the entire area shows a gradual downward trend. The direction of edge and bottom water intrusion is influenced by factors such as reservoir physical property distribution, pressure drop direction, and gas well structural location. Therefore, the direction of water intrusion is primarily controlled by the pressure drop direction, such as... Figure 16 As shown.

[0151] 3) Quantitative characterization of water intrusion dynamics

[0152] The average bottom water rise height was recorded as 29.5 meters, with a rise rate of 3.03 m / a (Table 10). Based on the degree of flooding and bottom water energy, layers I-2 and I-6 show significant potential for gas storage construction, while layer II-1 has limited potential.

[0153] Table 10 Quantitative Calculation Results of Water Intrusion in Each Sublayer of Block M14

[0154]

[0155] Based on the above analysis, it can be seen that the preferred reservoir construction layer has a good reserve base, is less affected by water production during the production process, has inactive edge water, low water intrusion, and basically meets the reservoir capacity requirements. The static parameters of the II-1 sublayer in the M14 block are relatively good, but the bottom water energy is sufficient. Except for the areas not controlled by wells, the rest are flooded, with a flooding degree as high as 70.7%. Therefore, it is not recommended as a reservoir construction layer.

[0156] Triaxial fatigue tests on the caprock mudstone showed that 1000 fatigue cycles under pressures of 8-12.8 MPa had no effect on the rock mechanical properties of the caprock mudstone. The caprock in the reservoir area is laterally continuous, thick, has poor permeability, high fatigue strength, and good sealing performance. Based on existing data, the evaluation results indicate that the SGR value of the boundary fault in the reservoir section is generally high. The calculated shear failure limit bearing capacity of the caprock is 25.3 MPa. Considering an 80% safety factor, the safe bearing capacity is 20.4 MPa, and the minimum safe bearing capacity of the fault is 14.6 MPa.

[0157] From a geological perspective, the I sand group is mainly composed of interbedded sediments between river channels and floodplains, with interbedded sand and mud. During the deposition of layers 2 and 6, mid-shoals and side shoals were well developed, and the sand bodies had good connectivity. The reservoir properties of layers I-2 and I-6 are better than those of other layers. The sand bodies are continuously distributed laterally and are spread throughout the entire reservoir construction area.

[0158] Dynamically, the water drive index of each main layer in the M8 and M14 well areas was calculated. The evaluation results are basically consistent with the current water flooding status of each layer. In terms of water flooding degree and bottom water energy, layers I-2 and I-6 have great potential for reservoir construction, while layer II-1 has less room for reservoir construction.

[0159] Therefore, the I-2 and I-6 sub-layers in the M8 and M14 well areas were ultimately selected as favorable layers for the construction of the M gas storage facility, i.e., the I-2 and I-6 sub-layers are the best layers for the construction of the storage facility.

[0160] Given the differences in gas-bearing area and water flooding degree among the selected reservoir formations, the deployment of injection and production wells should consider the vertical gas-bearing superposition relationship. Furthermore, under the principles of complex geological conditions in the gas reservoir, maximizing the use of existing wells, and improving the economic efficiency of reservoir construction, a numerical simulation model is used to study the feasibility of reservoir construction in the M gas reservoir. The specific process is as follows:

[0161] (1) Design Scheme

[0162] The design scheme aims to reach the designed storage capacity after six cycles, with a total working gas volume of 263 million cubic meters, of which 152 million cubic meters are allocated to block M8 and 110 million cubic meters to block M14. This overall storage capacity meets the design requirements and peak-shaving needs. The daily water production of the gas storage facility is 68 cubic meters, with 36 cubic meters from block M8 and 32 cubic meters from block M14. The mixed well network mainly utilizes horizontal wells to control individual gas reservoirs, and vertical wells for combined production and injection. Figure 17 and Figure 18 (As shown).

[0163] (2) Analysis of reaching full capacity and production capacity

[0164] Initially, low-speed, slow injection and minimal extraction are employed in new wells to gradually build up storage capacity and working gas volume. According to numerical simulation results, bottom gas replenishment is completed in 1-2 cycles, capacity is reached in 6 cycles, formation pressure reaches its upper limit, and stable injection-production operation begins in the 7th cycle. Figure 19 ).

[0165] (3) Water production prediction

[0166] Layer II-1 of block M14 exhibits significant water intrusion and complex gas-water interactions, with flooded areas accounting for 74% of the total area. Figure 20 In contrast, I-2 and I-6 experienced the least water intrusion, with flooded areas accounting for 32% to 51% of their respective regions. Similarly, layer II-1 of block M8 also exhibited significant water intrusion. Figure 21 The flooded area was 53%. In contrast, the water intrusion in the I-2 and I-6 sublayers was limited, with flooded areas ranging from 33% to 49%. The above study adjusted for the differences in water intrusion between different sublayers, further highlighting that I-2 and I-6 are more suitable for gas storage due to their lower water intrusion levels.

[0167] Applying this method to the site selection of a gas storage facility in the M multi-layered water-bearing gas reservoir, the following conclusions can be drawn from the above analysis:

[0168] (1) From a geological perspective, blocks M8 and M14 exhibit good reservoir properties, with an average porosity exceeding 20%. During the depositional periods of I-2 and I-6 in layer I, well-developed point bars and side beaches ensured good sand body connectivity and stable interlayer distribution. The caprock exhibits lateral continuity, with SGR values ​​of the boundary faults of layers I-2 and I-6 mainly exceeding 50%. The caprock shale thickness ranges from 53 to 78 meters, with a permeability of less than 0.05 mD, demonstrating excellent sealing capabilities. It can maintain mechanical integrity even after 1000 fatigue cycles under pressure conditions of 8-12.8 MPa.

[0169] (2) From the perspective of production dynamics, the I-2 and I-6 layers exhibit layered edge-water gas reservoirs with relatively low water intrusion, and their water drive indices are 0.16 and 2.41, respectively. These layers are characterized by weak water body energy, lateral continuity, large thickness, and good physical properties, possessing a solid reserve foundation. During production, they exhibit characteristics of minimal water production impact, inactive edge water, and low water intrusion intensity.

[0170] (3) Finally, based on the above method, the M8 and M14 well areas with high reservoir construction potential in the multi-layered water-bearing M gas reservoir were selected in the planar direction. In the vertical direction, the I-2 and I-6 sub-layers with weaker water intrusion energy in these two blocks were selected. The feasibility of gas reservoir construction and operation was studied through numerical simulation. The simulation prediction results show that the overall reservoir construction scheme has good operation effect, low oil ring damage, and can effectively block bottom water intrusion, fully demonstrating the accuracy, reliability and feasibility of this method.

[0171] The above are merely preferred embodiments of the present invention. It should be noted that any modifications and improvements made by those skilled in the art without departing from the present technical solution should also be considered to fall within the scope of protection claimed in this claim.

Claims

1. A method for selecting the optimal site location for an underground gas storage facility in a multi-layered water-bearing gas reservoir, characterized in that, Includes the following steps: S1, evaluate the reservoir characteristics of each layer in the target gas reservoir, and compare and assess the connectivity and permeability of each layer; the reservoir characteristics include sedimentary characteristics, sand body distribution, interlayer distribution, lithology, and reservoir physical properties. S2, using the relationship between the lithological configuration on both sides of the fault and the fault gouge ratio to analyze the reservoir-capsule system and evaluate the changes in the three-dimensional stress field under injection-production pressure disturbance; S3, from a production dynamics perspective, calculates the water drive index based on production dynamics data. WEDI The study analyzed the production capacity of the target gas reservoir using historical data, calculated water intrusion and gas-water ratio layer by layer, and combined this with the water drive index. WEDI To provide a detailed characterization and quantitative representation of water intrusion dynamics, and to clarify the distribution and migration of air and water; in, ； In the formula: WEDI - Water drive index, a quantity with a dimensionless value of 1; W e - The cumulative water inundation volume, in ten thousand cubic meters; G p - Cumulative gas production figures, in ten thousand cubic meters; W p - Cumulative water production, in ten thousand cubic meters; B g - Natural gas volume factor, a quantity with a dimensionless value of 1; B w - Formation water volume factor, dimensionless; When performing numerical simulation to calculate water intrusion and air-water ratio layer by layer, based on the results of fine three-dimensional geological modeling, the grid and attribute data are systematically coarsened to generate a three-dimensional structure and attribute model suitable for numerical simulation, and equilibrium zones and historical fitting are specifically divided. During the historical data fitting process, production control methods such as oil control during oil production, gas control during gas production, and liquid control during water production are used interchangeably. Fitting is performed by well area, layer system, well and stage to ensure that the model accurately represents the reservoir dynamics. Then, the aquifer characteristics are simulated and characterized using a historically fitted numerical simulation model, the water drive energy is comprehensively evaluated, and the water intrusion dynamics are quantitatively analyzed, including identifying the water intrusion direction, calculating the current average air-water interface, and determining the water intrusion area, volume, and rate of each sublayer. S4. Based on steps S1 to S3, by evaluating the flooding degree and bottom water energy of each sub-layer, the favorable layer for reservoir construction is selected. Based on a comprehensive evaluation of reservoir characteristics, sealing integrity, and gas-water flow characteristics, the optimal reservoir site is selected, and then the feasibility of construction and operation at the selected optimal reservoir site is analyzed through numerical simulation.

2. The optimal site selection method for multi-layered water-bearing gas reservoir underground gas storage according to claim 1, characterized in that: In step S2, the sealing integrity of the target gas reservoir is assessed based on the static sealing integrity of the caprock, the static sealing integrity of the fault, and the dynamic sealing integrity of the trap.

3. The optimal site selection method for multi-layered water-bearing gas reservoir underground gas storage according to claim 2, characterized in that: The static sealing integrity of the cap layer was evaluated by combining dynamic breakthrough pressure tests with fatigue tests. Based on the geological information of the target gas reservoir, structural modeling, sedimentary facies modeling, and reservoir property modeling are performed to predict the distribution of well perimeter physical parameters and establish a comprehensive three-dimensional geological model of reservoir physical properties. The static sealing capacity of faults within the gas reservoir is evaluated by utilizing the lithological contact relationship between two fault blocks and the distribution of fault gouge ratio.

4. The optimal site selection method for multi-layered water-bearing gas reservoir underground gas storage according to claim 3, characterized in that, The process of assessing the dynamic closure integrity of a trap includes the following steps: First, using the rock mechanics parameters obtained from experiments and the geostress data obtained from micro-fracture tests, combined with the three-dimensional geological model of reservoir properties, a three-dimensional geomechanical model is constructed. Secondly, simulate gas reservoir development and injection-production operations to simulate fluid pressure changes; Secondly, a dynamic geomechanical model is formed by analyzing the dynamic geostress field under injection-production disturbance through fluid-structure interaction simulation. Finally, the ultimate bearing capacity of geological structures was assessed by combining dynamic stress fields with rock mechanics parameters.

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