Method for predicting elastic modulus of sand-shale reservoir, computing device and storage medium

Abstract

The application provides a sandstone and mudstone reservoir elastic modulus prediction method, a computing device and a storage medium. The method comprises the following steps: adding sandstone pores to a quartz matrix and adding mudstone pores to a mudstone matrix, combining the quartz matrix containing the sandstone pores and the mudstone matrix containing the mudstone pores to simulate a target sandstone and mudstone reservoir core sample, determining a first simulated elastic modulus of the quartz matrix containing the sandstone pores and a second simulated elastic modulus of the mudstone matrix containing the mudstone pores by using a DEM model; determining a first predicted elastic modulus of a skeleton model of the target sandstone and mudstone reservoir core sample and a second predicted elastic modulus of a mineral matrix of the target sandstone and mudstone reservoir core sample by using a Voigt-Ruess-Hill model; and predicting an elastic modulus of the target sandstone and mudstone reservoir when saturated with fluid by using a Gassmann equation according to the first predicted elastic modulus, the second predicted elastic modulus and an elastic modulus of the fluid in the target sandstone and mudstone reservoir core sample. The elastic modulus of the sandstone and mudstone reservoir can be accurately predicted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rock physics research, and particularly relates to a method for predicting elastic modulus of sand-shale reservoirs, a computing device and a storage medium. BACKGROUND

[0002] The seismic rock physics method plays an important role in the exploration and development of unconventional oil and gas reservoirs, and can effectively describe the complexity of reservoir pore structure, physical property and fluid content. In the process of seismic rock physics research, the rock physics model provides elastic parameters for well logging and seismic inversion, especially the shear wave information, and the rock physics method has a theoretical basis and conforms to the geological law. The Xu-White model is a relatively mature application, which is a rock physics model based on sand-shale and can simulate the pore characteristics, mineral composition and fluid of sand-shale. However, the Xu-White model only generally considers the pores in the sand-shale reservoir and does not consider the pore types and the distribution of different types of pores. Xu and Payne (2009) established a carbonate rock physics model based on the Xu-White model, which divides the pores in the rock into three types, namely, round pores, micro-fractures and pores between the former two. However, the distribution of different types of pores is still not considered.

[0003] Therefore, there is an urgent need for a method for accurately predicting the elastic modulus of sand-shale reservoirs by considering the pore types and the distribution of different types of pores in the sand-shale reservoirs. SUMMARY

[0004] The main purpose of the present application is to provide a method for predicting the elastic modulus of sand-shale reservoirs, a computing device and a storage medium, so as to accurately predict the elastic modulus of sand-shale reservoirs.

[0005] In a first aspect, the present application provides a method for predicting the elastic modulus of a sand-shale reservoir, comprising: simulating adding sandstone pores to a quartz matrix and simulating adding shale pores to a shale matrix, using the combination of the quartz matrix containing the sandstone pores and the shale matrix containing the shale pores to simulate a target sand-shale reservoir core sample, determining a first simulated elastic modulus of the quartz matrix containing the sandstone pores and a second simulated elastic modulus of the shale matrix containing the shale pores using a DEM model, wherein the sandstone pores have a pore aspect ratio greater than or equal to a preset threshold, and the shale pores have a pore aspect ratio less than the preset threshold; determining a first predicted elastic modulus of a skeleton model of the target sand-shale reservoir core sample according to the first simulated elastic modulus and the second simulated elastic modulus using a Voigt-Ruess-Hill model, and determining a second predicted elastic modulus of a mineral matrix of the target sand-shale reservoir core sample according to the volume fraction and the elastic modulus of each mineral component in the target sand-shale reservoir core sample using the Voigt-Ruess-Hill model; and predicting the elastic modulus of the target sand-shale reservoir when saturated with fluid according to the first predicted elastic modulus, the second predicted elastic modulus, and the elastic modulus of the fluid in the target sand-shale reservoir core sample using a Gassmann equation.

[0006] In one embodiment, the method further comprises: determining a first simulated density of the quartz matrix containing the sandstone pores according to the respective densities of the quartz and the gas in the sandstone pores and the volume fractions of the quartz and the gas in the sandstone pores in the total volume of the gas in the quartz and the sandstone pores, and determining a second simulated density of the shale matrix containing the shale pores according to the respective densities of the clay and the gas in the shale pores and the volume fractions of the clay and the gas in the shale pores in the total volume of the gas in the clay and the shale pores; and predicting the density of the target sand-shale reservoir when saturated with fluid according to the volume fraction and the density of the fluid in the target sand-shale reservoir core sample, the volume fraction and the first simulated density of the quartz matrix containing the sandstone pores in the target sand-shale reservoir core sample, the volume fraction and the second simulated density of the shale matrix containing the shale pores in the target sand-shale reservoir core sample, and the volume fraction and the density of the mineral components other than the quartz and the clay in the target sand-shale reservoir core sample.

[0007] In one embodiment, the method further comprises: determining a first simulated density of the quartz matrix containing the sandstone pores according to the respective densities of the quartz and the gas in the sandstone pores and the volume fractions of the quartz and the gas in the sandstone pores in the total volume of the gas in the quartz and the sandstone pores, and determining a second simulated density of the shale matrix containing the shale pores according to the respective densities of the clay and the gas in the shale pores and the volume fractions of the clay and the gas in the shale pores in the total volume of the gas in the clay and the shale pores; and predicting the density of the target sand-shale reservoir when saturated with fluid according to the volume fraction and the density of the fluid in the target sand-shale reservoir core sample, the volume fraction and the first simulated density of the quartz matrix containing the sandstone pores in the target sand-shale reservoir core sample, the volume fraction and the second simulated density of the shale matrix containing the shale pores in the target sand-shale reservoir core sample, and the volume fraction and the density of the mineral components other than the quartz and the clay in the target sand-shale reservoir core sample.

[0008] R sat = Rqs *V sands +R cs *V clays +R calcite *V calcites +R dol *V dols +R f *Porosity

[0009] wherein R sat represents the predicted density of the target sand-shale reservoir when saturated with fluid, R qs represents the first simulated density, V sands represents the volume fraction of the quartz matrix containing sandstone pores in the target sand-shale reservoir core sample, R cs represents the second simulated density, V clays represents the volume fraction of the shale matrix containing shale pores in the target sand-shale reservoir core sample, R calcite represents the density of calcite, V calcites represents the volume fraction of calcite in the target sand-shale reservoir core sample, R dol represents the density of dolomite, V dols represents the volume fraction of dolomite in the target sand-shale reservoir core sample, R f represents the density of fluid, and Porosity represents the volume fraction of fluid in the target sand-shale reservoir core sample, i.e., the total porosity of the target sand-shale reservoir core sample.

[0010] In one embodiment, before the adding of the sandstone pores to the quartz matrix and the adding of the shale pores to the shale matrix are simulated, the method further comprises: obtaining a first measured porosity of the sandstone pores and a second measured porosity of the shale pores in the target sand-shale reservoir core sample; and the adding of the sandstone pores to the quartz matrix and the adding of the shale pores to the shale matrix are simulated such that the porosity of the sandstone pores reaches the first measured porosity and the porosity of the shale pores reaches the second measured porosity.

[0011] In one embodiment, the obtaining of the first measured porosity of the sandstone pores and the second measured porosity of the shale pores in the target sand-shale reservoir core sample comprises: applying a preset pressure to the target sand-shale reservoir core sample by using a variable pressure porosity-permeability test method, and taking the proportion of the number of un-closed pores to the total number of pores as the first measured porosity of the sandstone pores, and taking the proportion of the number of closed pores to the total number of pores as the second measured porosity of the shale pores.

[0012] In one embodiment, determining a first simulated elastic modulus of a quartz matrix containing sandstone pores using a DEM model includes determining the first simulated elastic modulus of the quartz matrix containing the sandstone pores using the following equation:

[0013]

[0014]

[0015]

[0016]

[0017] where K1 represents a bulk modulus of the quartz matrix, K2 represents a bulk modulus of the sandstone pores, y represents a volume fraction of the sandstone pores, and both represent a first simulated bulk modulus, μ1 represents a shear modulus of the quartz matrix, μ2 represents a shear modulus of the sandstone pores, and both represent a first simulated shear modulus, P (*2) (y) and Q (*2) (y) both represent a geometric factor.

[0018] Determining a second simulated elastic modulus of a shale matrix containing shale pores using a DEM model includes determining the second simulated elastic modulus of the shale matrix containing the shale pores using the following equation:

[0019]

[0020]

[0021]

[0022]

[0023] where K3 represents a bulk modulus of the shale matrix, K4 represents a bulk modulus of the shale pores, x represents a volume fraction of the shale pores, and both represent a second simulated bulk modulus, μ3 represents a shear modulus of the shale matrix, μ4 represents a shear modulus of the shale pores, and both represent a second simulated shear modulus, P (*2) (y) and Q (*2) (y) both represent a geometric factor.

[0024] In one embodiment, a first predicted elastic modulus of a target sand-shale reservoir core sample skeleton model is determined according to the first simulated elastic modulus and the second simulated elastic modulus by using a Voigt-Reuss-Hill model, comprising: determining the first predicted elastic modulus of the target sand-shale reservoir core sample skeleton model by using the following formula:

[0025]

[0026]

[0027]

[0028] wherein M m1 represents the first predicted elastic modulus, M v1 represents an elastic modulus calculated by using a Voigt upper limit method, M R1 represents an elastic modulus calculated by using a Reuss lower limit method, M1 and M2 respectively represent the first and second simulated elastic modulus, and f1 and f2 respectively represent volume fractions of a quartz matrix containing sandstone pores and a shale matrix containing shale pores;

[0029] A second predicted elastic modulus of a target sand-shale reservoir core sample skeleton model when no pores are contained is determined according to volume fractions and elastic moduli of each mineral component in the target sand-shale reservoir core sample by using a Voigt-Reuss-Hill model, comprising: determining the second predicted elastic modulus of a mineral matrix of the target sand-shale reservoir core sample by using the following formula:

[0030]

[0031]

[0032]

[0033] wherein M m2 represents the second predicted elastic modulus, M v2 represents an elastic modulus calculated by using a Voigt upper limit method, M R2 represents an elastic modulus calculated by using a Reuss lower limit method, M j represents an elastic modulus of the jth component, M j represents a volume fraction of the jth component, and the four components include quartz, clay, calcite and dolomite.

[0034] In one embodiment, the Gassmann model is utilized to predict the elastic modulus of the target sand-shale reservoir when saturated with fluid according to the first predicted elastic modulus, the second predicted elastic modulus, and the elastic modulus of the fluid in the target sand-shale reservoir core sample, including: predicting the elastic modulus of the target sand-shale reservoir when saturated with fluid according to the following formula:

[0035]

[0036] μ sat = μ dry

[0037] wherein K sat represents the predicted bulk modulus of the target sand-shale reservoir when saturated with fluid, K dry represents the first predicted bulk modulus, K0 represents the second predicted bulk modulus, K f represents the bulk modulus of the fluid, represents the total porosity of the target sand-shale reservoir core sample, μ sat represents the predicted shear modulus of the target sand-shale reservoir when saturated with fluid, μ dry represents the first predicted shear modulus.

[0038] In one embodiment, further comprising: determining seismic parameters of the target sand-shale reservoir according to the predicted elastic modulus and the density of the target sand-shale reservoir when saturated with fluid, wherein the seismic parameters include shear wave velocity and compressional wave velocity.

[0039] In a second aspect, the present application provides a computing device, comprising a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the prediction method of the elastic modulus of the sand-shale reservoir as described above are implemented.

[0040] In a third aspect, the present application provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the prediction method of the elastic modulus of the sand-shale reservoir as described above are implemented.

[0041] According to the actual situation of the pores in the sand-shale reservoir, the pores in the sand-shale reservoir are divided into two types: sandstone pores and argillaceous pores, wherein the sandstone pores are not easy to close and are mainly distributed in the quartz matrix, and the argillaceous pores are easy to close and are mainly distributed in the argillaceous matrix, so that the simulation effect is more in line with the actual situation of the sand-shale reservoir, and the prediction result is more accurate. BRIEF DESCRIPTION OF DRAWINGS

[0042] The accompanying drawings, which form a part of this specification, are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the application and, together with the description, serve to explain the application. In the drawings:

[0043] Figure 1 Flow chart of a method for predicting elastic modulus of a sand shale reservoir according to an example embodiment of the present application;

[0044] Figure 2 Flow chart of a method for predicting elastic modulus of a sand shale reservoir according to an example embodiment of the present application;

[0045] Figure 3 Graph of pressure-porosity test data according to an example embodiment of the present application;

[0046] Figure 4 Graph of a comparison between predicted velocity values and original velocity values according to an example embodiment of the present application. DETAILED DESCRIPTION

[0047] It should be noted that the embodiments and features of the embodiments in the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0048] Embodiment One

[0049] The present embodiment provides a method for predicting elastic modulus of a sand shale reservoir, Figure 1 Flow chart of a method for predicting elastic modulus of a sand shale reservoir according to an example embodiment of the present application. As shown in Figure 1 the method of the present embodiment includes:

[0050] S100: simulate adding sandstone pores to a quartz matrix and simulate adding shale pores to a shale matrix, use the combination of the quartz matrix containing sandstone pores and the shale matrix containing shale pores to simulate a target sand shale reservoir core sample, determine a first simulated elastic modulus of the quartz matrix containing sandstone pores and a second simulated elastic modulus of the shale matrix containing shale pores using a DEM model, wherein the sandstone pores have a pore aspect ratio greater than or equal to a preset threshold value, and the shale pores have a pore aspect ratio less than the preset threshold value.

[0051] S200: determine a first predicted elastic modulus of a skeleton model of the target sand shale reservoir core sample according to the first simulated elastic modulus and the second simulated elastic modulus using a Voigt-Ruess-Hill model, and determine a second predicted elastic modulus of a mineral matrix of the target sand shale reservoir core sample according to the volume fraction and elastic modulus of each mineral component in the target sand shale reservoir core sample using the Voigt-Ruess-Hill model.

[0052] S300: predicting the elastic modulus of the target sand-shale reservoir when saturated with fluid by using the Gassmann equation according to the first predicted elastic modulus, the second predicted elastic modulus and the elastic modulus of the fluid in the target sand-shale reservoir core sample.

[0053] Through the above steps, the types of pores in the sand-shale reservoir are distinguished, and the distribution of different types of pores is distinguished according to actual conditions. On this basis, the prediction of the elastic modulus of the sand-shale reservoir can make the prediction result have higher accuracy.

[0054] In the above steps, the preset threshold value can be set as needed and is not specifically limited here.

[0055] In one example, the method of the present embodiment can further include: determining a first simulated density of the quartz matrix containing the sandstone pores according to the respective densities of the quartz and the gas in the sandstone pores and the volume proportions of the quartz and the gas in the total volume of the gas in the sandstone pores, and determining a second simulated density of the argillaceous matrix containing the argillaceous pores according to the respective densities of the clay and the gas in the argillaceous pores and the volume proportions of the clay and the gas in the total volume of the gas in the argillaceous pores; and predicting the density of the target sand-shale reservoir when saturated with fluid according to the volume fraction and density of the fluid in the target sand-shale reservoir core sample, the volume fraction and first simulated density of the quartz matrix containing the sandstone pores in the target sand-shale reservoir core sample, the volume fraction and second simulated density of the argillaceous matrix containing the argillaceous pores in the target sand-shale reservoir core sample, and the volume fraction and density of the mineral composition other than quartz and clay in the target sand-shale reservoir core sample.

[0056] The prediction of the density of the target sand-shale reservoir when saturated with fluid according to the volume fraction and density of the fluid in the target sand-shale reservoir core sample, the volume fraction and first simulated density of the quartz matrix containing the sandstone pores in the target sand-shale reservoir core sample, the volume fraction and second simulated density of the argillaceous matrix containing the argillaceous pores in the target sand-shale reservoir core sample, and the volume fraction and density of the mineral composition other than quartz and clay in the target sand-shale reservoir core sample can include: predicting the density of the target sand-shale reservoir when saturated with fluid by using the following formula:

[0057] R sat = R qs * V sands + R cs * V clays + R calcite * V calcites + R dol * V dols + R f * Porosity

[0058] wherein R sat represents the predicted density of the target sand shale reservoir when saturated with fluid, R gs represents the first simulated density, V sands represents the volume fraction of the quartz matrix containing sandstone pores in the target sand shale reservoir core sample, R cs represents the second simulated density, V clays represents the volume fraction of the argillaceous matrix containing argillaceous pores in the target sand shale reservoir core sample, R calcite represents the density of calcite, V calcites represents the volume fraction of calcite in the target sand shale reservoir core sample, R dol represents the density of dolomite, V dols represents the volume fraction of dolomite in the target sand shale reservoir core sample, R f represents the density of fluid, Porosity represents the volume fraction of fluid in the target sand shale reservoir core sample, i.e., the total porosity of the target sand shale reservoir core sample.

[0059] Before simulating the addition of sandstone pores to the quartz matrix and simulating the addition of argillaceous pores to the argillaceous matrix, it can also include: obtaining a first measured porosity of the sandstone pores and a second measured porosity of the argillaceous pores in the target sand shale reservoir core sample; simulating the addition of sandstone pores to the quartz matrix and simulating the addition of argillaceous pores to the argillaceous matrix, including: simulating the addition of sandstone pores to the quartz matrix and simulating the addition of argillaceous pores to the argillaceous matrix, so that the porosity of the sandstone pores reaches the first measured porosity, and so that the porosity of the argillaceous pores reaches the second measured porosity.

[0060] By making the porosities added to the quartz matrix and the argillaceous matrix the same as the first and second measured porosities respectively, the subsequently calculated first and second simulated elastic moduli have higher accuracy, which is conducive to achieving accurate prediction of the elastic modulus of the target sand shale reservoir.

[0061] In one example, obtaining the first measured porosity of the sandstone pores and the second measured porosity of the argillaceous pores in the target sand shale reservoir core sample can include: using a variable pressure porosity permeability test method, applying a preset pressure to the target sand shale reservoir core sample, taking the proportion of the number of unsealed pores to the total number of pores as the first measured porosity of the sandstone pores, and taking the proportion of the number of sealed pores to the total number of pores as the second measured porosity of the argillaceous pores.

[0062] wherein determining the first simulated elastic modulus of the quartz matrix containing sandstone pores using the DEM model can include: determining the first simulated elastic modulus of the quartz matrix containing sandstone pores using the following formula:

[0063]

[0064]

[0065]

[0066]

[0067] wherein K1 represents a bulk modulus of the quartz matrix, K2 represents a bulk modulus of the sandstone pore, y represents a volume fraction of the sandstone pore, and both represent a first simulated bulk modulus, μ1 represents a shear modulus of the quartz matrix, μ2 represents a shear modulus of the sandstone pore, and both represent a first simulated shear modulus, P (*2) (y) and Q (*2) (y) both represent a geometric factor.

[0068] Determining a second simulated elastic modulus of a shale matrix including shale pores using a DEM model can include:

[0069] Determining a second simulated elastic modulus of a shale matrix including shale pores using the following equation:

[0070]

[0071]

[0072]

[0073]

[0074] wherein K3 represents a bulk modulus of the shale matrix, K4 represents a bulk modulus of the shale pore, x represents a volume fraction of the shale pore, and both represent a second simulated bulk modulus, μ3 represents a shear modulus of the shale matrix, μ4 represents a shear modulus of the shale pore, and both represent a second simulated shear modulus, P (*2) (y) and Q (*2) (y) both represent a geometric factor.

[0075] wherein determining a first predicted elastic modulus of a target sand-shale reservoir core sample skeleton model from the first simulated elastic modulus, the second simulated elastic modulus using a Voigt-Reuss-Hill model can include determining a first predicted elastic modulus of a target sand-shale reservoir core sample skeleton model using the following equation:

[0076]

[0077]

[0078]

[0079] wherein M m1 represents the first predicted elastic modulus, M v1 represents the elastic modulus calculated using the Voigt upper bound method, M R1 represents the elastic modulus calculated using the Reuss lower bound method, M1 and M2 represent the first and second simulated elastic moduli, respectively, and fi and f2 represent the volume fractions of the quartz matrix containing sandstone pores and the argillaceous matrix containing argillaceous pores, respectively.

[0080] Determining the second predicted elastic modulus of the target sand-shale reservoir core sample skeleton model when no pores are included using the Voigt-Ruess-Hill model according to the volume fractions and elastic moduli of each mineral component in the target sand-shale reservoir core sample can include determining the second predicted elastic modulus of the mineral matrix of the target sand-shale reservoir core sample using the following equation:

[0081]

[0082]

[0083]

[0084] wherein M m2 represents the second predicted elastic modulus, M v2 represents the elastic modulus calculated using the Voigt upper bound method, M R2 represents the elastic modulus calculated using the Reuss lower bound method, M j represents the elastic modulus of the jth component, M j represents the volume fraction of the jth component, the 4 components including quartz, clay, calcite, and dolomite.

[0085] wherein predicting the elastic modulus of the target sand-shale reservoir when saturated with fluid using the Gassmann model according to the first predicted elastic modulus, the second predicted elastic modulus, and the elastic modulus of the fluid in the target sand-shale reservoir core sample can include predicting the elastic modulus of the target sand-shale reservoir when saturated with fluid using the following equation:

[0086]

[0087] μ sat = μ dry

[0088] wherein K satrepresents the predicted bulk modulus of the target sand-shale reservoir when saturated with fluid, K dry represents the first predicted bulk modulus, K0represents the second predicted bulk modulus, K f represents the bulk modulus of the fluid, represents the total porosity of the target sand-shale reservoir core sample, μ sat represents the predicted shear modulus of the target sand-shale reservoir when saturated with fluid, μ dry represents the first predicted shear modulus.

[0089] The method of the embodiment can further include determining a seismic parameter of the target sand-shale reservoir according to the predicted elastic modulus and the density of the target sand-shale reservoir when saturated with fluid, wherein the seismic parameter includes a shear wave velocity and a compressional wave velocity.

[0090] According to the method of the embodiment, the pores in the sand-shale reservoir are divided into two types, sandstone pores and argillaceous pores, according to the actual conditions of the pores in the sand-shale reservoir, wherein the sandstone pores are not easy to close and are mainly distributed in the quartz matrix, and the argillaceous pores are easy to close and are mainly distributed in the argillaceous matrix, so that the simulation effect is more in line with the actual conditions of the sand-shale reservoir, and the prediction result is more accurate. Meanwhile, the measured porosities of the two types of pores in the target sand-shale reservoir are considered, which further improves the accuracy of the prediction result. Therefore, the compressional wave velocity and the shear wave velocity of the sand-shale reservoir calculated according to the predicted elastic modulus and the density are also more accurate, and the entire technical solution has better prediction effect.

[0091] Embodiment two

[0092] The embodiment provides a computing device including a processor and a memory, and the memory stores a computer program, when the computer program is executed by the processor, the steps of the prediction method of the elastic modulus of the sand-shale reservoir as described above are realized.

[0093] Those skilled in the art can understand that each aspect of the present application can be implemented as a system, a method or a program product. Therefore, each aspect of the present application can be embodied as a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuitry", "module" or "system" here.

[0094] In one embodiment, the computing device can include one or more processors (CPUs), input / output interfaces, network interfaces, and memories.

[0095] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash FLASH RAM). Memory is an example of computer-readable media.

[0096] Example 3

[0097] This embodiment provides a storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the method for predicting the elastic modulus of sandstone and mudstone reservoirs as described above.

[0098] Those skilled in the art will understand that embodiments of the present invention can be provided as methods or computer program products. Therefore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0099] This invention is described with reference to flowchart illustrations of methods and computer program products according to embodiments of the invention. It should be understood that each step in the flowchart and combinations of steps in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the process. Figure 1 A device for a function specified in one or more processes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 The function specified in one or more processes.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 2 Steps of a specified function in one or more processes.

[0102] Storage media includes permanent and non-permanent, removable and non-removable media can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0103] Embodiment four

[0104] Sand shale reservoir has been one of the important fields of oil and gas exploration, how to effectively predict the seismic parameters of sand shale reservoir is very important, and the pore as an important part of microstructure has a great influence on the elastic properties of the reservoir. This embodiment comprehensively considers the pore types in the sand shale reservoir and the distribution of different air types, and further predicts the elastic modulus and density of the sand shale reservoir to further predict the seismic parameters of the sand shale reservoir.

[0105] The central idea of the method of this embodiment includes the following steps (refer to Figure 3 ) :

[0106] First step: the pores in the sand shale reservoir rock are divided into two types of sandstone pores and argillaceous pores, the pore type is distinguished by the aspect ratio of the pore (the ratio of the short axis to the long axis of the pore), the aspect ratio of the sandstone pore can be set to 0.1-0.9, and the aspect ratio of the argillaceous pore can be set to 0.1-0.001. The setting here is because the pores in the argillaceous are generally the pores between the clay mineral layers, and the aspect ratio is smaller than that of the sandstone pore;

[0107] Second step, according to the statistical results of the variable pressure porosity test, the sandstone porosity and the argillaceous porosity are obtained;

[0108] Third step, the equivalent rock physical parameters of the sandstone skeleton containing pores are calculated by the DEM model;

[0109] Fourth step, the equivalent rock physical parameters of the argillaceous skeleton containing pores are calculated by the DEM model;

[0110] Fifth step, the combination of sandstone and argillaceous skeleton is carried out by woigt-Reuss-Hill average, and the equivalent rock physical parameters of the mixture of the two are calculated;

[0111] Sixth step, the mixed mineral matrix of sand shale reservoir is calculated by the woigt-Reuss-Hill average as the physical parameter of the small eye;

[0112] Seventh step, the fluid replacement is carried out by the Gassmann model, and the rock physical parameters containing different fluids in the seismic frequency band are obtained.

[0113] This embodiment takes the data of core C as an example to illustrate the prediction method of the elastic modulus of the sand shale reservoir:

[0114] (1) The rock analysis and variable pressure-porosity test data are shown in the following table: Figure 3 The mineral composition of core C includes quartz, clay, calcite and dolomite, and the mineral content accounts for 0.35, 0.5, 0.1 and 0.05 of the total mineral composition. The total porosity of core C is 0.109, and according to Figure 4 , it is known that the porosity and permeability are almost unchanged at a pressure of 7400 Psi, and the porosity content 0.098 at this pressure is taken as the porosity of the sandstone pore which is difficult to close, and the difference 0.011 between the total porosity and the porosity of the sandstone pore is taken as the porosity of the argillaceous pore which is easy to close.

[0115] (2) The DEM model is used to add sandstone pores to the quartz matrix, and the equivalent elastic modulus of the quartz matrix after adding pores is calculated. At the same time, the argillaceous mechanism is added to the argillaceous pore, and the equivalent elastic modulus of the argillaceous matrix after adding pores is calculated.

[0116] The expression of DEM is:

[0117]

[0118]

[0119] K * (0)=K1

[0120] μ * (0)=μ1

[0121] Wherein, K1 is the bulk modulus of the initial main phase phase 1, that is, the bulk modulus of the quartz matrix or the argillaceous matrix, μ1 is the shear modulus of the initial main phase phase 1, that is, the shear modulus of the quartz matrix or the argillaceous matrix, K2 is the bulk modulus of the initial main phase phase 2, that is, the bulk modulus of the sandstone pore or the argillaceous pore, μ2 is the shear modulus of the initial main phase phase 2, that is, the shear modulus of the sandstone pore or the argillaceous pore, y is the volume content of the initial main phase phase 2, P is the geometric factor, and Q is the geometric factor.

[0122] The equivalent bulk modulus of the quartz matrix containing sandstone pores is calculated by using the above expression of DEM: K stiffand shear modulus μ stiff The equivalent density R of the quartz matrix containing quartz pores is calculated simultaneously qs The calculation expression is:

[0123] R qs = R_q*V_q+R_g*Porosity_q.

[0124] Where R_q is the density of quartz minerals, V_q is the proportion of quartz in the total volume of quartz and sandstone pores, R_g is the density of air, and Porosity_q is the sandstone porosity.

[0125] The equivalent bulk modulus K of the shale matrix containing shale pores is calculated using the expression of the above DEM: soft and μ soft The equivalent density R of the shale matrix containing shale pores is calculated simultaneously cs The calculation expression is:

[0126] R cs = R_c*V_c+R_g*Porosity_c.

[0127] Where R_c is the density of shale (clay) minerals, V_c is the proportion of shale in the total volume of shale and shale pores, R_g is the density of air, and Porosity_c is the sandstone porosity.

[0128] (3) On the basis of the above, the equivalent elastic modulus of the sand-shale skeleton model is calculated using the Voigt-Ruess-Hill formula, that is, the equivalent elastic modulus of the combination of the quartz matrix containing sandstone pores and the shale matrix containing shale pores and the equivalent elastic modulus of the mineral matrix model in the sand-shale reservoir are calculated.

[0129] The expression of Voigt-Ruess-Hill is:

[0130]

[0131] Where

[0132]

[0133]

[0134] Where M i is the modulus of the i-th component of the mineral composition of the rock, f i is the volume fraction of the i-th component of the mineral composition of the rock (the value of fi can be obtained by rock geochemical analysis, M i is f iThe elastic parameter value of the corresponding mineral belongs to the physical property of the mineral itself, which can be obtained by consulting relevant manuals. M v The rock modulus M obtained by using the Voigt upper limit method for calculation R The rock modulus M obtained by using the Reuss lower limit method for calculation m The rock equivalent elastic modulus to be solved.

[0135] The equivalent bulk modulus K of the sand shale reservoir containing porosity and not containing fluid is calculated by using the above expression dry And the shear modulus μ dry .

[0136] The equivalent bulk modulus K0 and shear modulus μ0 of the mineral matrix of the sand shale reservoir not containing porosity and fluid are calculated by using the above expression. The proportions of quartz, clay, calcite and dolomite are 0.35, 0.5, 0.1 and 0.05 respectively.

[0137] (4) The elastic modulus of the rock when the pores are saturated with water is calculated by using the Gassmann equation, and the expression is:

[0138]

[0139] μ sat =μ dry

[0140] Wherein, K sat represents the bulk modulus of the sand shale reservoir when saturated with water, K f represents the bulk modulus of water, represents the total porosity, μ sat represents the shear modulus of the sand shale reservoir when saturated with water.

[0141] The density of the sand shale reservoir when saturated with water is also calculated:

[0142] R sat =R qs *V sands +R cs *V clays +R calcite *V calcites +R dol *V dols +R f *Porosity

[0143] Wherein, V sands is the volume ratio of quartz containing pores in the rock, V clays is the volume ratio of clay containing pores in the rock, R calcite is the density of calcite, V calcites is the volume ratio of calcite in the rock, Rdol is the density of dolomite, V dols is the volume ratio of dolomite in the rock, R f Here is the density of water (Note: when other fluids are filled in the sandstone and mudstone reservoir pores, it can also be the density of other fluids), Porosity is the total porosity of the rock.

[0144] (5) The final predicted velocity value of the calculation model is calculated, and the calculation formula of the longitudinal wave velocity and the transverse wave velocity is as follows:

[0145]

[0146]

[0147] Where, V p_sat represents the longitudinal wave velocity, V s_sat represents the transverse wave velocity.

[0148] ​ The actual velocity prediction of the core C and the core B is given, and the predicted value is compared with the actual velocity value (that is, the original velocity in the figure). It can be found that the model predicted value is basically consistent with the actual value, and good prediction effect is achieved.

[0149] By using the method of the application, the longitudinal wave velocity and the transverse wave velocity of the sandstone and mudstone reservoir are predicted in combination with the actual test data of the sandstone and mudstone reservoir core. In the rock physical model calculation process, the variable pressure-porosity velocity test is used to obtain the hard porosity which is not easy to close in the rock and the soft porosity which is easy to close. The pores in the sand and the pores in the mud in the rock are considered respectively, which is more in line with the actual microstructure distribution of the sandstone and mudstone reservoir. At the same time, the micro-equivalent medium model (DEM) is used to process the process of adding pores, realize the calculation of the equivalent modulus of the skeleton rock, and use the Gassmann model to expand the model from the theoretical high frequency value to the low frequency value of the saturated fluid. The method effectively extracts the soft porosity and hard porosity content, has good prediction effect, and can be applied to the rock physical prediction of the sandstone and mudstone reservoir, and can be applied to the prediction of the logging transverse wave and other elastic parameters.

[0150] It should be noted that the terms used herein are only for the purpose of describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. When the terms "comprise" and / or "include" are used in the specification, it means that the features, steps, operations, devices, components and / or their combinations are present.

[0151] It should be noted that the terms "first", "second", and the like, in the description and in the claims of the present application are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of orderly execution or performance other than those explicitly described or other than shown in the figures.

[0152] It is to be understood that the exemplary embodiments set forth herein can be implemented in a variety of forms and that the present disclosure is not limited to only the embodiments described and / or illustrated herein. The exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art, and will allow others skilled in the art to claim the benefit of the exemplary embodiments.

Claims

1. A method of predicting the elastic modulus of a sand shale reservoir, characterized in that, The method comprises: adding sandstone pores to a quartz matrix and adding shale pores to a shale matrix are simulated, a combination of the quartz matrix containing the sandstone pores and the shale matrix containing the shale pores is used to simulate a target sand-shale reservoir core sample, a first simulated elastic modulus of the quartz matrix containing the sandstone pores and a second simulated elastic modulus of the shale matrix containing the shale pores are determined by using a DEM model, wherein a pore aspect ratio of the sandstone pores is greater than or equal to a preset threshold, and a pore aspect ratio of the shale pores is less than the preset threshold; a first predicted elastic modulus of a skeleton model of the target sand-shale reservoir core sample is determined by using a Voigt-Ruess-Hill model according to the first simulated elastic modulus and the second simulated elastic modulus, and a second predicted elastic modulus of a mineral matrix of the target sand-shale reservoir core sample is determined by using the Voigt-Ruess-Hill model according to a volume fraction and an elastic modulus of each mineral component in the target sand-shale reservoir core sample; an elastic modulus of the target sand-shale reservoir when saturated with fluid is predicted by using a Gassmann equation according to the first predicted elastic modulus, the second predicted elastic modulus, and an elastic modulus of the fluid in the target sand-shale reservoir core sample.

2. The method of predicting the elastic modulus of a sand shale reservoir according to claim 1, characterized in that, The method further comprises: a first simulated density of the quartz matrix containing the sandstone pores is determined according to densities of the quartz and the gas in the sandstone pores and volume proportions of the quartz and the gas in the sandstone pores in a total volume of the gas in the quartz and the sandstone pores, and a second simulated density of the shale matrix containing the shale pores is determined according to densities of the clay and the gas in the shale pores and volume proportions of the clay and the gas in the shale pores in a total volume of the gas in the clay and the shale pores; a density of the target sand-shale reservoir when saturated with fluid is predicted according to a volume fraction and a density of the fluid in the target sand-shale reservoir core sample, a volume fraction and the first simulated density of the quartz matrix containing the sandstone pores in the target sand-shale reservoir core sample, a volume fraction and the second simulated density of the shale matrix containing the shale pores in the target sand-shale reservoir core sample, and volume fractions and densities of mineral components other than the quartz and the clay in the target sand-shale reservoir core sample.

3. The method of predicting elastic modulus of sand shale reservoirs as claimed in claim 2 wherein, The density of the target sand-shale reservoir when saturated with fluid is predicted according to a volume fraction and a density of the fluid in the target sand-shale reservoir core sample, a volume fraction and the first simulated density of the quartz matrix containing the sandstone pores in the target sand-shale reservoir core sample, a volume fraction and the second simulated density of the shale matrix containing the shale pores in the target sand-shale reservoir core sample, and volume fractions and densities of mineral components other than the quartz and the clay in the target sand-shale reservoir core sample, comprising: the density of the target sand-shale reservoir when saturated with fluid is predicted by using the following formula: R sat = R qs *V sands + R cs *V clays + R calcite *V calcites + R dol *V dols + R f * Porosity wherein R sat represents the predicted density of the target sand-shale reservoir when saturated with fluid, R qs represents the first modeled density, V sands represents the volumetric fraction of quartz matrix containing sandstone pores in the target sand-shale reservoir core sample, R cs represents the second modeled density, V clays represents the volumetric fraction of shale matrix containing shale pores in the target sand-shale reservoir core sample, R calcite represents the density of calcite, V calcites represents the volumetric fraction of calcite in the target sand-shale reservoir core sample, R dol represents the density of dolomite, V dols represents the volumetric fraction of dolomite in the target sand-shale reservoir core sample, R f represents the density of fluid, Porosity represents the volumetric fraction of fluid in the target sand-shale reservoir core sample, i.e. the total porosity of the target sand-shale reservoir core sample.

4. The method of predicting elastic modulus of sand shale reservoirs as claimed in claim 1 wherein, Before the adding of the sandstone pores to the quartz matrix and the adding of the shale pores to the shale matrix are simulated, the method further comprises: obtaining a first measured porosity of the sandstone pores and a second measured porosity of the shale pores in the target sand-shale reservoir core sample; the adding of the sandstone pores to the quartz matrix and the adding of the shale pores to the shale matrix comprise: The adding of sandstone pores to the quartz matrix and the adding of shale pores to the shale matrix are simulated so that the porosity of the sandstone pores reaches the first measured porosity and so that the porosity of the shale pores reaches the second measured porosity.

5. The method of predicting the elastic modulus of a sand shale reservoir according to claim 4, characterized in that, The first measured porosity of the sandstone pores and the second measured porosity of the shale pores in a target sand-shale reservoir core sample are obtained, including: A variable pressure porosity-permeability test is used to apply a preset pressure to the target sand-shale reservoir core sample, and the proportion of the number of un-closed pores to the total number of pores is taken as the first measured porosity of the sandstone pores, and the proportion of the number of closed pores to the total number of pores is taken as the second measured porosity of the shale pores.

6. The method of predicting elastic modulus of shale reservoirs as claimed in claim 1, wherein, A first simulated elastic modulus of a quartz matrix containing sandstone pores is determined using a DEM model, including: The first simulated elastic modulus of the quartz matrix containing sandstone pores is determined using the following formula: where K1 represents the bulk modulus of the quartz matrix, K2 represents the bulk modulus of the sandstone pore, and y represents the volume fraction of the sandstone pore, and both represent the first simulated bulk modulus, μ1 represents the shear modulus of the quartz matrix, and μ2 represents the shear modulus of the sandstone pore, and both represent the first simulated shear modulus, P (*2) (y) and Q (*2) (y) both represent a geometric factor; A second simulated elastic modulus of a shale matrix containing shale pores is determined using a DEM model, including: The second simulated elastic modulus of the shale matrix containing shale pores is determined using the following formula: where K3 represents the bulk modulus of the shale matrix, K4 represents the bulk modulus of the shale pores, x represents the volume fraction of the shale pores, and both represent the second simulated bulk modulus, μ3 represents the shear modulus of the shale matrix, μ4 represents the shear modulus of the shale pores, and both represent the second simulated shear modulus, P (*2) (y) and Q (*2) (y) both represent a geometric factor.

7. The method of predicting elastic modulus of sand shale reservoirs as claimed in claim 1 wherein, A first predicted elastic modulus of a skeleton model of the target sand-shale reservoir core sample is determined using a Voigt-Reuss-Hill model according to the first simulated elastic modulus and the second simulated elastic modulus, including: The first predicted elastic modulus of the skeleton model of the target sand-shale reservoir core sample is determined using the following formula: where M m1 represents the first predicted elastic modulus, M v1 represents the elastic modulus calculated using the Voigt upper bound method, M R1 represents the elastic modulus calculated using the Reuss lower bound method, M1 and M2 represent the first and second simulated elastic moduli, respectively, and fi and f2 represent the volume fractions of the quartz matrix containing sandstone pores and the argillaceous matrix containing argillaceous pores, respectively; A second predicted elastic modulus of the skeleton model of the target sand-shale reservoir core sample when no pores are contained is determined using a Voigt-Reuss-Hill model according to the volume fraction and the elastic modulus of each mineral component in the target sand-shale reservoir core sample, including: The second predicted elastic modulus of the mineral matrix of the target sand-shale reservoir core sample is determined using the following formula: where M m2 represents the second predicted modulus of elasticity, M v2 represents the modulus of elasticity calculated using the Voigt upper limit method, M R2 represents the modulus of elasticity calculated using the Reuss lower limit method, M j represents the modulus of elasticity of the jth component, M j represents the volume fraction of the jth component, the 4 components including quartz, clay, calcite, and dolomite.

8. The method of predicting elastic modulus of sand shale reservoirs as claimed in claim 1 wherein, A predicted elastic modulus of the target sand-shale reservoir when saturated with fluid is predicted using a Gassmann model according to the first predicted elastic modulus, the second predicted elastic modulus, and the elastic modulus of the fluid in the target sand-shale reservoir core sample, including: The predicted elastic modulus of the target sand-shale reservoir when saturated with fluid is predicted using the following formula: μ sat = μ dry where K sat represents the predicted bulk modulus of the target sand-shale reservoir when saturated with fluid, K dry represents the first predicted bulk modulus, K0represents the second predicted bulk modulus, K f represents the bulk modulus of the fluid, represents the total porosity of the target sand-shale reservoir core sample, μ sat represents the predicted shear modulus of the target sand-shale reservoir when saturated with fluid, μ dry represents the first predicted shear modulus.

9. The method of predicting the elastic modulus of a sand shale reservoir according to any one of claims 2 to 5, characterized in that, Further comprising: According to the predicted elastic modulus and the density of the target sand-shale reservoir when saturated with fluid, a seismic parameter of the target sand-shale reservoir is determined, wherein the seismic parameter includes a shear wave velocity and a longitudinal wave velocity.

10. A computing device comprising a processor and a memory, characterized in that, The memory stores a computer program, and when the computer program is executed by the processor, the steps of the prediction method of the elastic modulus of the sand-shale reservoir according to any one of claims 1 to 9 are implemented.

11. A storage medium having stored therein a computer program, characterized in that When the computer program is executed by the processor, the steps of the prediction method of the elastic modulus of the sand-shale reservoir according to any one of claims 1 to 9 are implemented.

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