Method and device for determining percolation characteristics of a reservoir

Abstract

The application discloses a method and device for determining percolation characteristics of a reservoir, and belongs to the technical field of oil and gas reservoir exploration and development. The application divides different reservoir space matching types by the structural characteristics and distribution characteristics of the reservoir space in a core, constructs a corresponding reservoir conceptual model for each reservoir space matching type, establishes a corresponding percolation model for different types of reservoir spaces in the reservoir conceptual model, and obtains the pressure response of the outlet end of different reservoir conceptual models in the process of solving the percolation model, so as to draw a well test characteristic curve, and determine the corresponding relationship between different reservoir space matching types and percolation characteristics according to the well test characteristic curves of different reservoir conceptual models, thereby providing support for the identification and evaluation of multiple medium reservoirs.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas reservoir exploration and development, and particularly relates to a method and device for determining the percolation characteristics of a reservoir. BACKGROUND

[0002] Fracture-vug carbonate reservoirs have the characteristics of multiple media coexisting and strong heterogeneity. Different scales of pores, fractures and vugs are developed in such reservoirs, and the reservoir space matching relationship is diverse, which leads to complex flow rules of fluid flowing in such reservoirs. In production, the open flow capacity and stable production capacity of gas wells in such reservoirs are very different. Therefore, in order to better carry out resource exploitation, it is necessary to determine the percolation characteristics corresponding to different reservoir space matching in such reservoirs.

[0003] At present, when determining the percolation characteristics of multiple media carbonate reservoirs, on a macroscopic level, well testing technology is usually used to evaluate the percolation of the reservoir. For multiple media carbonate reservoirs, the well testing curve obtained by using this method mostly shows the percolation characteristics of composite formations, and does not show the percolation characteristics of dual media or multiple media, and the relationship between reservoir space matching and percolation characteristics cannot be determined. On a microscopic level, indoor core percolation experiments are usually used to simulate the reservoir pressure recovery process, and the corresponding relationship between the reservoir structure characteristics and the outlet pressure change is obtained. However, due to the small scale of the core sample used in the experiment, it is difficult to obtain enough accurate and continuous data points to draw the pressure recovery curve, so it is difficult to determine the percolation characteristics corresponding to different reservoir space matching in the reservoir. SUMMARY

[0004] The embodiments of the present application provide a method and device for determining the percolation characteristics of a reservoir, which can determine the percolation characteristics corresponding to different reservoir space matching types of the reservoir. The technical solution is as follows:

[0005] On one aspect, a method for determining the percolation characteristics of a reservoir is provided, and the method comprises:

[0006] Based on the reservoir space information of the reservoir space in the reservoir, a reservoir conceptual model corresponding to different reservoir space matching types is constructed, and the reservoir space information is used to indicate the structure characteristics and distribution characteristics of the reservoir space;

[0007] The flow state of gas in the reservoir structure indicated by each reservoir conceptual model under a reference condition is simulated, and a percolation model is obtained, wherein the percolation model comprises the flow characteristics of gas in each type of reservoir space;

[0008] The percolation model is solved, and the pressure response of the outlet end of each reservoir conceptual model is obtained;

[0009] The well test characteristic curve corresponding to each reservoir conceptual model is determined based on the pressure response of the outlet end of each reservoir conceptual model, and the well test characteristic curve is used to indicate the percolation characteristics of the reservoir space matching type corresponding to the reservoir conceptual model.

[0010] In one aspect, a percolation characteristic determination apparatus for a reservoir is provided, and the apparatus comprises:

[0011] A model construction module is configured to construct reservoir conceptual models corresponding to different reservoir space matching types based on reservoir space information of reservoir spaces in a reservoir, and the reservoir space information is used to indicate structural characteristics and distribution characteristics of the reservoir spaces.

[0012] A model acquisition module is configured to simulate a flow state of a gas in a reservoir structure indicated by the reservoir conceptual model under a reference condition based on the reservoir conceptual model, and obtain a percolation model, wherein the percolation model comprises flow characteristics of the gas in each type of reservoir space.

[0013] A data acquisition module is configured to solve the percolation model, and obtain a pressure response of an outlet end of each reservoir conceptual model.

[0014] A curve determination module is configured to determine a well test characteristic curve corresponding to each reservoir conceptual model based on the pressure response of the outlet end of each reservoir conceptual model, and the well test characteristic curve is used to indicate percolation characteristics of the reservoir space matching type corresponding to the reservoir conceptual model.

[0015] In one possible implementation, the model acquisition module is configured to:

[0016] Simulate the flow state of the gas in the reservoir structure indicated by the reservoir conceptual model under the reference condition based on a multi-flow field coupling micro numerical simulation method, and obtain a flow system corresponding to each type of percolation medium in the reservoir conceptual model.

[0017] Obtain the percolation model based on the flow system corresponding to each type of percolation medium, a boundary condition, and an initial condition.

[0018] In one possible implementation, the data acquisition module is configured to:

[0019] For any reservoir conceptual model, an outer boundary of the any reservoir conceptual model is set as a constant pressure boundary, and a constant flow rate of the gas is simulated at the outlet end of the any reservoir conceptual model.

[0020] The outlet end of the any reservoir conceptual model is closed, a pressure recovery process is simulated, and a pressure response of the outlet end of the any reservoir conceptual model is obtained.

[0021] In a possible implementation, the duration of the simulated constant flow rate production gas is a first duration, and the duration of the simulated pressure buildup process is a second duration, the first duration being at least greater than one third of the second duration.

[0022] In a possible implementation, the curve determining module is configured to:

[0023] determine a pressure derivative based on the pressure response of the outlet end of the reservoir conceptual model;

[0024] determine a pressure and pressure derivative change curve as a well test characteristic curve corresponding to the reservoir conceptual model.

[0025] In an aspect, a computer device is provided, which includes one or more processors and one or more memories having stored therein at least one program code, which is loaded and executed by the one or more processors to implement operations performed by the reservoir percolation feature determination method.

[0026] In an aspect, a computer readable storage medium is provided, which has stored therein at least one program code, which is loaded and executed by a processor to implement operations performed by the reservoir percolation feature determination method.

[0027] The technical solution provided by the embodiments of the present application can divide different reservoir space matching types based on the structural features and distribution features of the reservoir space in the core, construct a corresponding reservoir conceptual model for each reservoir space matching type, establish a corresponding percolation model for different types of reservoir space in the reservoir conceptual model, and obtain the pressure response features corresponding to different reservoir conceptual models in the process of pressure buildup simulation based on the percolation model, so as to obtain the well test characteristic curves corresponding to different reservoir conceptual models and determine the corresponding relationship between different reservoir space matching types and percolation features, thereby providing support for the identification and evaluation of the multi-medium reservoir. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0029] Figure 1 is a flowchart of a reservoir percolation feature determination method provided by the embodiments of the present application;

[0030] Figure 2is a flow chart of a reservoir percolation feature determination method provided by an embodiment of the present application;

[0031] Figure 3 is a schematic diagram of a reservoir space matching type provided by an embodiment of the present application;

[0032] Figure 4 is a schematic diagram of a core internal structure and reservoir conceptual model provided by an embodiment of the present application;

[0033] Figure 5 is a schematic diagram of a grid model provided by an embodiment of the present application;

[0034] Figure 6 is a schematic diagram of a reservoir conceptual model provided by an embodiment of the present application;

[0035] Figure 7 is a well test characteristic curve schematic diagram provided by an embodiment of the present application;

[0036] Figure 8 is a structural schematic diagram of a reservoir percolation feature determination device provided by an embodiment of the present application;

[0037] Figure 9 is a structural schematic diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical scheme and advantages of the present application more clear, the following will make further detailed description on the embodiments of the present application in combination with the drawings.

[0039] Figure 1 is a flow chart of a reservoir percolation feature determination method provided by an embodiment of the present application, referring to Figure 1 , the method can be applied to a computer device, and the method comprises the following steps:

[0040] 101. Constructing a reservoir conceptual model corresponding to different reservoir space matching types based on reservoir space information of reservoir spaces in a reservoir, the reservoir space information being used to indicate structural features and distribution features of the reservoir spaces.

[0041] 102. Simulating a flow state of a gas in a reservoir structure indicated by each of the reservoir conceptual models under a reference condition to obtain a percolation model, the percolation model comprising flow features of the gas in each type of reservoir space.

[0042] 103. Solving the percolation model to obtain a pressure response of an outlet end of each of the reservoir conceptual models.

[0043] 104. Based on the pressure response at the outlet end of each reservoir concept model, determine the well test characteristic curve corresponding to each reservoir concept model. The well test characteristic curve is used to indicate the seepage characteristics of the reservoir space combination type corresponding to the reservoir concept model.

[0044] The technical solution provided in this application classifies different reservoir space combination types based on the structural and distribution characteristics of reservoir space in the core. A corresponding reservoir concept model is constructed for each reservoir space combination type. Then, a corresponding seepage model is established for different types of reservoir space within the reservoir concept model. During the solution process of the seepage model, the pressure response at the outlet end of different reservoir concept models can be obtained, and well test characteristic curves can be plotted. Based on the well test characteristic curves of different reservoir concept models, the correspondence between different reservoir space combination types and seepage characteristics is determined, providing support for the identification and evaluation of multi-medium reservoirs.

[0045] In one possible implementation, based on reservoir space information, a reservoir conceptual model corresponding to different reservoir space combination types is constructed, including:

[0046] Obtain reservoir space information from at least one core sample of the reservoir;

[0047] Based on the reservoir space information of the core, the reservoir space combination type corresponding to the core is determined;

[0048] For any reservoir space combination type, based on the reservoir space information corresponding to the core belonging to that reservoir space combination type, a reservoir concept model corresponding to that reservoir space combination type is constructed.

[0049] In one possible implementation, the storage space information includes the equivalent diameter of the storage space, the geometry factor, the apparent surface area, and the proportion of each type of storage space.

[0050] This involves obtaining reservoir space information from at least one core sample of the reservoir, including:

[0051] Based on the CT scan image corresponding to the core, a digital core is constructed.

[0052] Based on the digital core, structural characteristic parameters of each reservoir space are obtained, including the equivalent diameter, geometric shape factor, and apparent surface area of ​​the reservoir space.

[0053] Based on the structural characteristic parameters of each storage space, the type of each storage space is determined;

[0054] Obtain the distribution characteristics of various types of reservoir spaces in the core.

[0055] In one possible implementation, based on the reservoir conceptual model, the flow state of gas in the reservoir structure indicated by the reservoir conceptual model under reference conditions is simulated to obtain a seepage model, including:

[0056] Based on the microscopic numerical simulation method of multi-flow field coupling, the flow state of gas in the reservoir structure indicated by the reservoir conceptual model under reference conditions is simulated to obtain the flow system corresponding to various seepage media in the reservoir conceptual model.

[0057] Based on the flow system, boundary conditions, and initial conditions corresponding to these various seepage media, the seepage model is obtained.

[0058] In one possible implementation, the seepage model is solved to obtain the pressure response at the outlet end of each reservoir conceptual model, including:

[0059] For any reservoir conceptual model, the outer boundary of the reservoir conceptual model is set as a constant pressure boundary, and a constant flow of gas is simulated at the outlet end of the reservoir conceptual model.

[0060] By closing the outlet end of any reservoir conceptual model and simulating the pressure recovery process, the pressure response at the outlet end of the reservoir conceptual model is obtained.

[0061] In one possible implementation, the duration of the simulated constant flow gas production is a first duration, and the duration of the simulated pressure recovery process is a second duration, wherein the first duration is at least one-third longer than the second duration.

[0062] In one possible implementation, the well test characteristic curves corresponding to each reservoir conceptual model are determined based on the pressure response at the outlet end of each reservoir conceptual model, including:

[0063] Based on the pressure response at the outlet end of the reservoir conceptual model, the pressure derivative is determined;

[0064] The pressure and pressure derivative variation curves are identified as the well test characteristic curves corresponding to the reservoir conceptual model.

[0065] The technical solution provided in this application, based on the establishment of a reservoir conceptual model with different combinations of pores, cavities, and fractures, conducts forward modeling of seepage pressure recovery in multi-medium reservoirs to obtain the correspondence between pore, cavity, and fracture combinations and well test characteristic curves. That is, it obtains the correspondence between different reservoir space combination types and well test characteristic curves, and determines the seepage characteristics corresponding to different reservoir space combination types. In actual operation, the seepage characteristics of a certain reservoir area can be inferred based on the information of the reservoir space reflected in the macroscopic well test data, providing support for the identification and evaluation of multi-medium reservoirs, and facilitating the selection of more favorable reservoir space combination types in actual operation.Figure 2 This is a flowchart of a method for determining the seepage characteristics of a reservoir, provided in an embodiment of this application. This method can be applied to computer equipment. (See also...) Figure 2 This embodiment may specifically include the following steps:

[0066] 201. Obtain multiple core samples from the reservoir to be tested.

[0067] In this embodiment, taking a fractured-void type carbonate reservoir as an example, this type of reservoir contains various reservoir spaces, such as pores, caverns, and fractures, with diverse combinations of reservoir spaces. The flow patterns of fluids in this type of reservoir are complex. In this embodiment, reservoir rocks from multiple different regions and depths can be obtained to prepare core samples, ensuring that the development of reservoir spaces in the obtained core samples covers various combinations of reservoir spaces.

[0068] 202. Obtain reservoir space information for each core sample.

[0069] The reservoir space information is used to indicate the structural and distribution characteristics of the reservoir space in the core. For example, the reservoir space information may include the equivalent diameter, geometric shape factor, apparent specific surface area, and the proportion of each type of reservoir space. Of course, the reservoir space information may also include other data, which is not limited in this embodiment.

[0070] In this embodiment, a digital core can be constructed based on the CT (Computed Tomography) scan image corresponding to the core, and structural characteristic parameters of each reservoir space can be obtained based on the digital core. For example, structural characteristic parameters of each reservoir space in the digital core can be extracted by combining core thin sections, imaging logging, and other results, including the equivalent diameter, geometric shape factor, and apparent specific surface area of ​​the reservoir space. Then, based on the structural characteristic parameters of each reservoir space, the type of each reservoir space is determined, and the distribution of each type of reservoir space in the core is statistically analyzed to obtain the distribution characteristics of each type of reservoir space in the core. It should be noted that different reservoirs include different types of reservoir spaces. In this embodiment, taking carbonate reservoirs as an example, three types of reservoir spaces can be classified: pores, caverns, and fractures. Reservoir spaces with a diameter greater than 2 mm are considered caverns, and reservoir spaces with a diameter less than 2 mm are considered pores. The geometric shape factor F ≤ 0.05 or the radius of the circumscribed sphere (R) is specified. min ) and equivalent sphere radius (R) e The ratio R) min / R e Storage space greater than 20 is a crack.

[0071] It should be noted that the above description of the method for obtaining storage space information is only an exemplary description of one possible implementation. The embodiments of this application do not limit which specific method is used to obtain storage space information.

[0072] 203. Based on the reservoir space information of the core, determine the reservoir space combination type corresponding to the core.

[0073] In one possible approach, reservoir space information from the core can be used to determine the morphology, scale, development size, and contact relationships of different reservoir spaces within the core, thereby classifying different reservoir space combination types. Taking carbonate reservoirs as an example, six reservoir space combination types can be identified, including isolated fracture type, isolated cavern type, isolated pore type, bedding karst type, fracture-cavity type, and cavern-fracture type.

[0074] In this embodiment, the Dengying Formation reservoir of the Sinian System in the Gaoshiti-Moxi area of ​​central Sichuan is used as an example to illustrate steps 201 to 203. The Dengying Formation is located at a depth of 5000–5300 m, with the Dengying-4 Member reservoir being the most developed. The reservoir lithology is mainly composed of algal-clustered dolomite, algal-stromatolite, algal-veined dolomite, and sandstone dolomite. Core porosity ranges from 2% to 5%, with an average of 3.97%; permeability ranges from 0.01 mD to 5 mD, with an average of 2.89 mD, exhibiting characteristics of low porosity and low permeability. Based on core thin section and imaging logging analysis, the reservoir space in this area is genetically classified into three main categories: porosity, vugs, and fractures. Among these, porosity includes intergranular and intercrystalline pores, with highly irregular morphology and a size of approximately 0.03 mm to 0.1 mm, often associated with intergranular pores. Caves are mostly layered, or distributed in a beaded pattern along fissures and solution cracks, or distributed around karst breccia. The morphology of caves includes flattened round, elliptical, banded, teardrop-shaped, fissure-shaped, and irregular shapes. Small caves (2mm-5mm) are the most numerous, accounting for over 75% of the total, followed by medium-sized caves (5mm-20mm), accounting for about 15%, while large caves (greater than 20mm) are the fewest, accounting for only 6.1%. Fissures include tectonic fissures and dissolution fissures. Typically, the porosity of fissures is less than 0.05%; in the embodiments of this application, based on the reservoir space information of the core, the fissure density was obtained as 0.86-7.62 fissures / m.

[0075] In this embodiment, based on the results of digital core analysis and the development and contact location of pores, cavities, and fractures, six reservoir space configuration types can be identified for the corresponding area: isolated fracture type, isolated cavern type, isolated pore type, bedding karst type, fracture-cavity type, and cavern-fracture type. Specifically: Isolated fracture type: Several fractures in different directions rarely communicate with each other; neither pores nor cavities are developed. Isolated cavern type: A small number of cavities are unevenly distributed in the core and are not interconnected; pores are not developed. Isolated pore type: Primarily composed of primary pores, with a small number of cavities locally developed. Bedding karst type: Caverns and pores are developed, and the pores are interconnected, exhibiting a clear directionality. Fracture-cavity type: Numerous cavities and a small number of fractures are developed; the fractures serve as communication channels between the cavities. Cavern-fracture type: Both caverns and fractures are relatively well-developed; the fractures are not only the main seepage channels but also important reservoir spaces. Figure 3 This is a schematic diagram of a storage space configuration type provided in an embodiment of this application. Figure 3 The images show CT scans, fracture identification images, and digital cores of six cores, which correspond to the six reservoir space combination types mentioned above.

[0076] 204. For any reservoir space combination type, based on the reservoir space information corresponding to the core belonging to that reservoir space combination type, construct the reservoir concept model corresponding to that reservoir space combination type.

[0077] In one possible implementation, for the identified reservoir space combination types, a meter-scale reservoir conceptual model corresponding to each reservoir space type can be constructed based on the principle of similarity. In this embodiment, taking the aforementioned six reservoir space combination types as examples, based on the statistical variation patterns of fracture, vault, and pore characteristic parameters, a corresponding meter-scale reservoir conceptual model is established using the principle of similarity. The principle of similarity means that each element constituting the model must be similar to its corresponding element in the prototype. For example, in this embodiment, each core sample is extracted from a carbonate reservoir, and the reservoir conceptual model corresponding to each core sample contains three types of seepage media: fractures, vaults, and matrix. When constructing the reservoir conceptual model, based on statistical fracture characteristic parameters, such as fracture aperture and length, regular parallel plates are used to represent fractures, and fractures with different orientations are scattered or intersecting to form a fracture network; based on statistical parameters such as cave diameter, regular spheres of different diameters are used to represent caves, and caves form cave groups or are distributed in isolation in the model; the matrix porosity and rock skeleton are the background phase, with uniform equivalent porosity and equivalent permeability. Figure 4 This is a schematic diagram of the internal structure of a core and a conceptual model of a reservoir provided in an embodiment of this application, as shown below. Figure 4 As shown, based on the internal structure 401 of the core, a reservoir conceptual model 402 can be obtained.

[0078] 205. Based on the reservoir conceptual model, the flow state of gas in the reservoir structure indicated by the reservoir conceptual model under reference conditions is simulated to obtain the seepage model.

[0079] The reference condition can be set to high temperature and high pressure. This seepage model includes the flow characteristics of gas in various types of storage spaces, that is, the flow characteristics of gas in various types of seepage media.

[0080] In this embodiment of the application, taking the single-phase gas flowing in the reservoir as an example, based on the above-mentioned reservoir conceptual model, the flow state of the gas under high temperature and high pressure formation conditions is simulated. Taking the reservoir as including three seepage media, namely fractures, caverns and matrix, the microscopic numerical simulation method of multi-flow field coupling can be applied to obtain three flow systems, namely fracture system, cavern system and bedrock system. Based on multiple seepage systems, and combined with boundary conditions, a seepage model is established.

[0081] Among them, the reservoir capacity of fractures in the rock core is relatively small, but it can play a role in improving the seepage capacity. The flow of gas in fractures or fracture networks is called fracture flow. Its flow velocity is related to the fracture opening and can be described by the cubic ratio. In one possible implementation, the flow equation of the fracture system is expressed as the following formula (1):

[0082]

[0083] The distribution of karst caves in the rock core is relatively discrete, and some caves are connected by fractures. The contribution of these caves to porosity can reach 30% to 50%, indicating good storage performance. The flow of gas in the karst caves can be regarded as the free flow of viscous fluid, which conforms to the Navier-Stokes equations for compressible fluids. In one possible implementation, the flow equation of the karst cave system is expressed as the following formula (2):

[0084]

[0085] The flow of gas in the matrix is ​​Darcy flow, and the interface between the media follows continuous boundary conditions of flow rate and pressure. In one possible implementation, the flow equation of the bedrock system is expressed as the following formula (3):

[0086]

[0087] Among them, Q f The outlet flow rate of the crack region is expressed in m / s.

[0088] l represents the distance between the inlet and outlet of the crack region, in meters;

[0089] b represents the crack aperture in the crack region, in meters;

[0090] p fThe pressure in the crack region is expressed in Pa; Δp f The pressure difference between the two ends of the fracture region is expressed in Pa.

[0091] p s The pressure in the cave area is expressed in Pa. This represents the pressure gradient in the karst cave region, expressed in Pa / m.

[0092] μ represents the effective viscosity of the fluid in the rock core, in mPa·s;

[0093] u s The velocity of the flow in the cave area is expressed in m / s.

[0094] D(u s ) represents the strain tensor, which is dimensionless; It represents the divergence of the strain tensor and is dimensionless.

[0095] u d The velocity in the matrix region is expressed in m / s.

[0096] f represents the mass force of the fluid in the rock core, N / m. 2 ;

[0097] p d This represents the pressure in the matrix region, expressed in Pa. This represents the pressure gradient in the matrix region, expressed in Pa / m.

[0098] K m This represents the equivalent permeability in the matrix pore throat model, in mD.

[0099] In one possible implementation, assuming the reservoir conceptual model is saturated gas, the initial pressure is set to the original formation pressure of the reservoir, for example, 55 MPa, and the temperature is 120°C. One end of the model is connected to a constant pressure boundary, and the other end is set as an outlet, producing gas at a constant flow rate. Then the boundary conditions and initial conditions can be expressed as the following formulas (4), (5), and (6):

[0100] p| t＝0 =p i (4)

[0101] p| r＝L =p i (5)

[0102]

[0103] Among them, K m The equivalent permeability in the matrix pore-throat model is expressed in mD.

[0104] q sc Indicates the gas flow rate at the outlet, m 3 / s;

[0105] p represents the pressure at time t at a distance r from the outlet, in Pa;

[0106] L represents the distance from the outlet end to the outer boundary of the reservoir conceptual model, in meters (m).

[0107] μ represents the effective viscosity of the fluid in the rock core, in mPa·s;

[0108] Z represents the gas deviation factor under pressure p, which is dimensionless;

[0109] h represents the model thickness, in meters;

[0110] p i This represents the initial simulated pressure, in Pa.

[0111] T represents temperature, in °C.

[0112] 206. Solve the seepage model to obtain the pressure response at the outlet end of each reservoir conceptual model.

[0113] In one possible implementation, the pressure response at the outlet of the reservoir conceptual model can be obtained through pressure recovery simulation. This pressure response can be the pressure change data at the outlet. For example, for any reservoir conceptual model, its outer boundary is set as a constant-pressure boundary, i.e., the rectangular outer boundary of the reservoir conceptual model is set as a constant-pressure boundary, where the constant-pressure boundary is the same as the initial simulation pressure. A constant flow of gas is simulated at the outlet of any reservoir conceptual model; then, the outlet of the reservoir conceptual model is closed, and the pressure recovery process is simulated to obtain the pressure change data at the outlet of the reservoir conceptual model, i.e., the pressure response. The sampling time density for obtaining the pressure change data at the outlet can be set to 0.1 s / time. In another possible implementation, the duration of the simulated constant-flow gas production is a first duration, and the duration of the simulated pressure recovery process is a second duration. The first duration is greater than one-third of the second duration, ensuring that during the simulated constant-flow gas production process, the pressure in the reservoir conceptual model changes, i.e., the pressure drop affects the entire reservoir space region in the model.

[0114] In one possible implementation, the seepage model can be solved based on the finite element method. First, the reservoir conceptual model is meshed. Figure 5 This is a schematic diagram of a mesh model provided in an embodiment of this application. After meshing the reservoir conceptual model, the following diagram is obtained: Figure 5The mesh model shown is used as a basis for solving the various parameters in the above seepage model based on the meshed reservoir conceptual model. It should be noted that this application does not limit the specific process of solving the seepage model using the finite element method. For example, taking a seepage model based on a carbonate reservoir as an example, since bedrock is widely present in the core and the gas flow in the bedrock conforms to Darcy's law, the finite element method is mainly used to solve the pressure and velocity fields of the flow in fractured and cavernous regions. When simulating the underground gas seepage process, one end of the reservoir conceptual model can be connected to a constant pressure boundary, and the outlet end of the reservoir conceptual model can be closed to simulate the pressure recovery process. See [link to relevant documentation]. Figure 6 , Figure 6 This is a schematic diagram of a reservoir conceptual model provided in an embodiment of this application, such as... Figure 6 As shown, one end of the reservoir conceptual model is connected to the isobaric boundary 601, and the other end is set as the outlet 602. Before simulating the pressure recovery process, it is necessary to ensure that the pressure drop wave extends to the entire reservoir space region in the model, i.e. Figure 6 In region 603, the gas is produced at a constant flow rate at the outlet for a period of time. After that, the outlet of the reservoir conceptual model is closed, and a pressure recovery simulation is performed to obtain the pressure change information at the outlet of the reservoir conceptual model during the pressure recovery simulation. That is, the pressure response at the outlet is recorded during the pressure recovery simulation.

[0115] 207. Based on the pressure response at the outlet end of each reservoir conceptual model, determine the well test characteristic curve corresponding to each reservoir conceptual model.

[0116] Among them, the well test characteristic curve is used to indicate the seepage characteristics of the reservoir space combination type corresponding to the reservoir conceptual model.

[0117] In this embodiment of the application, the pressure derivative can be determined based on the pressure response at the outlet end of the reservoir conceptual model, thereby drawing pressure and pressure derivative change curves to obtain well test characteristic curves corresponding to different reservoir conceptual models.

[0118] 208. Based on the well test characteristic curves, determine the correspondence between the reservoir space combination type and the seepage characteristics.

[0119] In one possible implementation, the characteristic flow stage of gas can be obtained based on the above-mentioned well test characteristic curves and the reservoir concept model corresponding to the well test characteristic curves. The micro-permeability characteristics corresponding to different reservoir space combination types can be obtained based on the well test characteristic curves. Figure 7 This is a schematic diagram of a well test characteristic curve provided in an embodiment of this application. Taking the Dengying Formation reservoir of the Sinian system in the Gaoshiti-Moxi area of ​​central Sichuan as an example, it can obtain the following... Figure 7 The well test characteristic curves shown are based on Figure 7The well test characteristic curves shown below reveal the seepage characteristics corresponding to each reservoir space combination type, as follows:

[0120] Isolated fracture type: When gas flow reaches the impermeable boundary in multiple directions, and only a very small portion enters the narrow fracture channel, the pressure derivative appears as a straight line with a slope approximately 1. As the fracture development worsens, the pressure derivative curve continues to rise and coincides with the pressure curve. Subsequently, another fracture zone is connected, at which point the pressure curve and the pressure derivative curve gradually separate, indicating that a new gas supply zone begins to smooth out pressure changes, such as... Figure 7 Curve 701 in Figure (a) is shown;

[0121] Isolated cave type: Initially, gas flow occurs within the cave, approximating radial flow. Later, due to the lack of connection to other openings, the gas supply area decreases, and the pressure derivative curve begins to rise, as shown in the example. Figure 7 Curve 702 in Figure (c) is shown;

[0122] Isolated pore type: Due to the extremely dense matrix, early gas flow reaches the impermeable boundary, and the pressure curve and pressure derivative curve basically coincide. Later, flow occurs within localized cavities, and the pressure curve and pressure derivative curve gradually separate. Figure 7 Curve 703 in Figure (a) is shown;

[0123] Stratified karst: The early pressure derivative curve shows a horizontal segment of radial flow, exhibiting characteristics of apparent homogeneity. Figure 7 As shown in Figure (b);

[0124] Fissure-cavity type: Early gas flow is within the cavities, approximately radial, followed by a transitional flow phase, exhibiting the boundary effects of a high-permeability gas supply zone. As the fissures connect more cavities, the pressure derivative curve begins to decline, such as... Figure 7 Curve 704 in Figure (c) is shown;

[0125] Cave-fissure type: Early gas flow exhibits characteristics of linear flow in fissures, followed by a transitional flow phase. Later, depending on the number of fissures connecting to the cave, the pressure derivative curve may show an upward or downward slope, such as... Figure 8 As shown in Figure (d).

[0126] Based on the characteristics of the six well test curves mentioned above, the seepage patterns of fracture-void reservoirs in the Gaoshiti-Moxi area can be classified into four categories: curve intersection type, apparent homogeneous type, radial composite type, and pressure fracture type. Among them, the seepage patterns corresponding to the isolated fracture type and isolated pore type reservoir space combination types are curve intersection type; the seepage pattern corresponding to the bedding karst type is apparent homogeneous type; the seepage patterns corresponding to the isolated cavern type and fracture-cavrn type reservoir space combination types are radial composite type; and the seepage pattern corresponding to the cavern-fracture type is pressure fracture type.

[0127] The technical solution provided in this application classifies different reservoir space combinations based on the structural and distribution characteristics of the reservoir space in the core. For each reservoir space combination type, a corresponding reservoir conceptual model is constructed. That is, by combining core thin sections, imaging logging, and digital core analysis results of fracture-void reservoirs, reservoir conceptual models with different combinations of pores, fractures, and vaults are established. Then, for different types of reservoir spaces in the reservoir conceptual model—namely, for the three types of seepage media in the reservoir conceptual model: fractures, caverns, and matrix—corresponding seepage models are established, and the finite element method is used to solve the seepage models. During pressure recovery simulation based on the seepage models, the pressure response characteristics corresponding to different reservoir conceptual models can be obtained, thereby obtaining well test characteristic curves corresponding to different reservoir conceptual models and determining the correspondence between different reservoir space combinations and seepage characteristics. Moreover, obtaining well test characteristic curves from the microscopic data level eliminates the need for actual well testing operations, reducing the labor cost of obtaining well test characteristic curves and improving the efficiency of obtaining them.

[0128] By applying the technical solution provided in this application, the seepage characteristics corresponding to different reservoir space combination types can be determined, revealing the correspondence between reservoir space combination types and seepage characteristics from a mechanistic perspective. In actual operation, the seepage characteristics of a reservoir area can be inferred based on the information about the reservoir space reflected in macroscopic well test data, providing support for the identification and evaluation of multi-medium reservoirs. Furthermore, when deploying wells, favorable reservoir space combination types can be selected by combining well test characteristic curves. It should be noted that in this application embodiment, only fractured-void type carbonate reservoirs are used as an example to illustrate the method for obtaining the seepage characteristics corresponding to reservoir space combination types. The method for obtaining the seepage characteristics corresponding to reservoir space combination types in other types of reservoirs is the same as steps 201 to 208 described above.

[0129] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0130] Figure 8 This is a schematic diagram of a reservoir seepage characteristic determination device provided in an embodiment of this application. See also... Figure 9 The device includes:

[0131] The model building module 801 is used to build a reservoir concept model corresponding to different reservoir space combination types based on the reservoir space information of the reservoir space. The reservoir space information is used to indicate the structural and distribution characteristics of the reservoir space.

[0132] The model acquisition module 802 is used to simulate the flow state of gas in the reservoir structure indicated by the reservoir concept model under reference conditions based on the reservoir concept model, and obtain a seepage model, which includes the flow characteristics of gas in various types of reservoir spaces.

[0133] The data acquisition module 803 is used to solve the seepage model and obtain the pressure response at the outlet end of each reservoir conceptual model;

[0134] The curve determination module 804 is used to determine the well test characteristic curve corresponding to each reservoir concept model based on the pressure response at the outlet end of each reservoir concept model. The well test characteristic curve is used to indicate the seepage characteristics of the reservoir space combination type corresponding to the reservoir concept model.

[0135] In one possible implementation, the model building module 801 includes:

[0136] The information acquisition submodule is used to acquire reservoir space information from at least one core sample of the reservoir.

[0137] The type determination submodule is used to determine the reservoir space combination type corresponding to the core based on the reservoir space information of the core.

[0138] The model building submodule is used to construct a reservoir concept model corresponding to any reservoir space combination type based on the reservoir space information of the core belonging to that reservoir space combination type.

[0139] In one possible implementation, the storage space information includes the equivalent diameter of the storage space, the geometry factor, the apparent surface area, and the proportion of each type of storage space.

[0140] This information retrieval submodule is used for:

[0141] Based on the CT scan image corresponding to the core, a digital core is constructed.

[0142] Based on the digital core, structural characteristic parameters of each reservoir space are obtained, including the equivalent diameter, geometric shape factor, and apparent surface area of ​​the reservoir space.

[0143] Based on the structural characteristic parameters of each storage space, the type of each storage space is determined;

[0144] Obtain the distribution characteristics of various types of reservoir spaces in the core.

[0145] In one possible implementation, the model acquisition module 802 is used for:

[0146] Based on the microscopic numerical simulation method of multi-flow field coupling, the flow state of gas in the reservoir structure indicated by the reservoir conceptual model under reference conditions is simulated to obtain the flow system corresponding to various seepage media in the reservoir conceptual model.

[0147] Based on the flow system, boundary conditions, and initial conditions corresponding to these various seepage media, the seepage model is obtained.

[0148] In one possible implementation, the data acquisition module 803 is used for:

[0149] For any reservoir conceptual model, the outer boundary of the reservoir conceptual model is set as a constant pressure boundary, and a constant flow of gas is simulated at the outlet end of the reservoir conceptual model.

[0150] By closing the outlet end of any reservoir conceptual model and simulating the pressure recovery process, the pressure response at the outlet end of the reservoir conceptual model is obtained.

[0151] In one possible implementation, the duration of the simulated constant flow gas production is a first duration, and the duration of the simulated pressure recovery process is a second duration, wherein the first duration is greater than one-third of the second duration.

[0152] In one possible implementation, the curve determination module 804 is used for:

[0153] Based on the pressure response at the outlet end of the reservoir conceptual model, the pressure derivative is determined;

[0154] The pressure and pressure derivative variation curves are identified as the well test characteristic curves corresponding to the reservoir conceptual model.

[0155] The apparatus provided in this application classifies different reservoir space combination types based on the structural and distribution characteristics of reservoir spaces in the core. For each reservoir space combination type, a corresponding reservoir concept model is constructed. Then, for different types of reservoir spaces in the reservoir concept model, a corresponding seepage model is established. During the pressure recovery simulation based on the seepage model, the pressure response characteristics corresponding to different reservoir concept models can be obtained, thereby obtaining the well test characteristic curves corresponding to different reservoir concept models. The correspondence between different reservoir space combination types and seepage characteristics is determined, providing support for the identification and evaluation of multi-medium reservoirs.

[0156] It should be noted that the reservoir seepage characteristic determination device provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the reservoir seepage characteristic determination device and the reservoir seepage characteristic determination method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0157] ​ This is a schematic diagram of the structure of a computer device 900 provided in an embodiment of this application. The computer device 900 can vary significantly due to differences in configuration or performance. It may include one or more Central Processing Units (CPUs) 901 and one or more memories 902. Each memory 902 stores at least one line of program code, which is loaded and executed by the one or more processors 901 to implement the methods provided in the various method embodiments described above. Of course, the computer device 900 may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The computer device 900 may also include other components for implementing device functions, which will not be elaborated upon here.

[0158] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including at least one line of program code, which can be executed by a processor to complete the reservoir percolation characteristic determination method in the above embodiments. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0159] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program with at least one piece of program code associated with the hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0160] The above are merely optional embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining the seepage characteristics of a reservoir, characterized in that, The method includes: Obtain reservoir space information from at least one core of the reservoir, wherein the reservoir space information is used to indicate the structural and distribution characteristics of the reservoir space; Based on the reservoir space information of the core, the reservoir space combination type corresponding to the core is determined. The reservoir space combination type includes isolated fracture type, isolated cave type, isolated pore type, bedding karst type, fracture-cavity type, and cave-fracture type. For any reservoir space combination type, based on the reservoir space information corresponding to the core belonging to the reservoir space combination type, a reservoir concept model at the meter scale corresponding to the reservoir space combination type is constructed using the similarity principle. The similarity principle means that each element that makes up the model must be similar to the corresponding element of the prototype. Based on the reservoir conceptual model, the flow state of gas in the reservoir structure indicated by the reservoir conceptual model under reference conditions is simulated to obtain a seepage model, which includes the flow characteristics of gas in various types of reservoir spaces. The seepage model is solved to obtain the pressure response at the outlet end of each reservoir conceptual model; Based on the pressure response at the outlet end of each reservoir concept model, the well test characteristic curve corresponding to each reservoir concept model is determined. The well test characteristic curve is used to indicate the seepage characteristics of the reservoir space combination type corresponding to the reservoir concept model. Based on the well test characteristic curves corresponding to each reservoir conceptual model, the correspondence between the reservoir space combination type and the seepage characteristics is determined; wherein, the seepage patterns corresponding to the isolated fracture type and the isolated pore type are curve intersection type, the seepage pattern corresponding to the bedding karst type is apparent homogeneous type, the seepage patterns corresponding to the isolated cave type and the fracture-cavity type are radial composite type, the seepage pattern corresponding to the cave-fracture type is pressure fracture type, and the seepage pattern is the pattern corresponding to the seepage characteristics.

2. The method according to claim 1, characterized in that, The storage space information includes the equivalent diameter, geometric shape factor, apparent surface area, and proportion of each type of storage space. The acquisition of reservoir space information from at least one core sample of the reservoir includes: Based on the CT scan images corresponding to the core, a digital core corresponding to the core is constructed; Based on the digital core, structural characteristic parameters of each reservoir space are obtained, including the equivalent diameter, geometric shape factor, and apparent surface area of ​​the reservoir space. Based on the structural characteristic parameters of each storage space, the type of each storage space is determined; The distribution characteristics of various types of reservoir spaces in the core were obtained.

3. The method according to claim 1, characterized in that, The process of simulating the gas flow state in the reservoir structure indicated by the reservoir conceptual model under reference conditions, based on the reservoir conceptual model, yields a seepage model, including: Based on the microscopic numerical simulation method of multi-flow field coupling, the flow state of gas in the reservoir structure indicated by the reservoir conceptual model under reference conditions is simulated to obtain the flow system corresponding to various seepage media in the reservoir conceptual model. The seepage model is obtained based on the flow system, boundary conditions, and initial conditions corresponding to the various seepage media.

4. The method according to claim 1, characterized in that, Solving the seepage model to obtain the pressure response at the outlet end of each reservoir conceptual model includes: For any reservoir conceptual model, the outer boundary of the reservoir conceptual model is set as a constant pressure boundary, and a constant flow of gas is simulated at the outlet end of the reservoir conceptual model. By closing the outlet end of any of the reservoir conceptual models and simulating the pressure recovery process, the pressure response at the outlet end of any of the reservoir conceptual models is obtained.

5. The method according to claim 4, characterized in that, The duration of the simulated constant flow gas production is the first duration, and the duration of the simulated pressure recovery process is the second duration. The first duration is more than one-third of the second duration.

6. The method according to claim 1, characterized in that, The determination of the well test characteristic curves corresponding to each reservoir conceptual model based on the pressure response at the outlet end of each reservoir conceptual model includes: Based on the pressure response at the outlet end of the reservoir conceptual model, the pressure derivative is determined; The pressure and pressure derivative variation curves are determined as the well test characteristic curves corresponding to the reservoir conceptual model.

7. A device for determining the seepage characteristics of a reservoir, characterized in that, The device includes: The model building module is used to acquire reservoir space information of at least one core sample from the reservoir, wherein the reservoir space information is used to indicate the structural and distribution characteristics of the reservoir space; based on the reservoir space information of the core sample, the module determines the reservoir space combination type corresponding to the core sample, wherein the reservoir space combination type includes isolated fracture type, isolated cavern type, isolated pore type, bedding-parallel karst type, fracture-cavity type, and cavern-fracture type; for any reservoir space combination type, based on the reservoir space information corresponding to the core sample belonging to the reservoir space combination type, the module constructs a reservoir conceptual model at the meter scale corresponding to the reservoir space combination type using the similarity principle, wherein the similarity principle means that each element constituting the model must be similar to the corresponding element of the prototype; The model acquisition module is used to simulate the flow state of gas in the reservoir structure indicated by the reservoir concept model under reference conditions based on the reservoir concept model, and obtain a seepage model, which includes the flow characteristics of gas in various types of reservoir spaces. The data acquisition module is used to solve the seepage model to obtain the pressure response at the outlet end of each reservoir conceptual model; The curve determination module is used to determine the well test characteristic curve corresponding to each reservoir conceptual model based on the pressure response at the outlet end of each reservoir conceptual model. The well test characteristic curve is used to indicate the seepage characteristics of the reservoir space combination type corresponding to the reservoir conceptual model. Based on the well test characteristic curves corresponding to each reservoir conceptual model, the module determines the correspondence between the reservoir space combination type and the seepage characteristics. Among them, the seepage mode corresponding to the isolated fracture type and the isolated pore type is the curve intersection type, the seepage mode corresponding to the bedding karst type is the apparent homogeneous type, the seepage mode corresponding to the isolated cave type and the fracture-cavity type is the radial composite type, the seepage mode corresponding to the cave-fracture type is the pressure fracture type, and the seepage mode is the mode corresponding to the seepage characteristics.

8. The apparatus according to claim 7, characterized in that, The storage space information includes the equivalent diameter, geometric shape factor, apparent surface area, and proportion of each type of storage space. The information acquisition submodule is used for: Based on the CT scan images corresponding to the core, a digital core corresponding to the core is constructed; Based on the digital core, structural characteristic parameters of each reservoir space are obtained, including the equivalent diameter, geometric shape factor, and apparent surface area of ​​the reservoir space. Based on the structural characteristic parameters of each storage space, the type of each storage space is determined; The distribution characteristics of various types of reservoir spaces in the core were obtained.

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