CN-122024885-A - Shale reservoir analysis method and device, electronic equipment and storage medium

CN122024885ACN 122024885 ACN122024885 ACN 122024885ACN-122024885-A

Abstract

The embodiment of the invention provides an analysis method, device, electronic equipment and storage medium of a shale reservoir, which comprise the steps of constructing a shale reservoir physical model according to geological features, sedimentary layering factors and effective stress of the shale reservoir, determining a first elastic modulus parameter of a first sedimentary layering, a second elastic modulus parameter of a second sedimentary layering and a first stiffness coefficient matrix based on the shale reservoir physical model, constructing a training sample set according to porosity, pore pressure, the first elastic modulus parameter, the second elastic modulus parameter and the first stiffness coefficient matrix, training a deep learning model based on the training sample set, inputting the porosity, the pore pressure, the actually measured elastic modulus parameter and the first elastic modulus parameter into the deep learning model to obtain a second stiffness coefficient matrix, determining the anisotropic strength of the shale reservoir according to the second stiffness coefficient matrix, and improving the efficiency of calculating the anisotropic strength of the shale reservoir.

Inventors

LIU DI
HAN RUIDONG
HUANG NA
ZHAO YIDAN
WU SHUYAN
LI HONG

Assignees

中国石油天然气集团有限公司
中国石油集团东方地球物理勘探有限责任公司
中油油气勘探软件国家工程研究中心有限公司

Dates

Publication Date: 20260512
Application Date: 20241112

Claims (8)

1. A method of shale reservoir analysis, for application to an electronic device, the method comprising: constructing a shale reservoir physical model according to geological features, sedimentary stratification factors and effective stress of the shale reservoir, wherein the sedimentary stratification factors are used for representing sedimentary stratification strength; Determining a first elastic modulus parameter of a first sedimentary stratification corresponding to the shale reservoir based on the shale reservoir physical model, and a second elastic modulus parameter and a first stiffness coefficient matrix of a second sedimentary stratification corresponding to the shale reservoir, wherein the first sedimentary stratification is obtained by simulating based on mineral components of the shale reservoir, and the second sedimentary stratification is obtained by simulating based on geological features of the shale reservoir; constructing a training sample set according to the porosity, the pore pressure, the first elastic modulus parameter, the second elastic modulus parameter and the first stiffness coefficient matrix of the shale reservoir, wherein a training sample in the training sample set comprises an array formed by the porosity, the pore pressure, the first elastic modulus parameter and the second elastic modulus parameter, and the first stiffness coefficient matrix is a reference result corresponding to the array; Training a deep learning model based on the training sample set; Inputting the porosity, pore pressure, measured elastic modulus parameters and the first elastic modulus parameters of the shale reservoir into a trained deep learning model to obtain a second rigidity coefficient matrix; And determining the anisotropic strength of the shale reservoir according to the second rigidity coefficient matrix.
2. The method of claim 1, wherein constructing a shale reservoir physical model from the geological features of the shale reservoir, the sedimentary stratification factors, the effective stress, comprises: Constructing a physical model corresponding to the first sedimentary stratification based on mineral components and sedimentary stratification factors of the shale reservoir; determining an effective stress experienced by the shale reservoir; Calculating a second fracture density corresponding to the shale reservoir according to the effective stress and a first fracture density corresponding to the shale reservoir, wherein the first fracture density refers to the fracture density when the shale reservoir is not subjected to the effective stress; And constructing a physical model corresponding to the second sedimentary stratification according to the second fracture density, the porosity and the mixed fluid property on the basis of the physical model of the first sedimentary stratification, so as to obtain the shale reservoir physical model.
3. The method of claim 2, wherein the mineral components include non-clay mineral components, and organic matter components, wherein the constructing a physical model corresponding to the first sedimentary stratification based on the mineral components, sedimentary stratification factors of the shale reservoir comprises: Constructing a physical model of the mixture based on the non-clay mineral component and the organic component; and constructing a physical model of the first sedimentary stratification according to clay mineral components and sedimentary stratification factors in the shale reservoir on the basis of the physical model of the mixture.
4. The method of claim 2, wherein the determining the effective stress to which the shale reservoir is subjected comprises: determining overburden pressure and pore pressure of the shale reservoir; determining a difference between overburden pressure and pore pressure of the shale reservoir as the effective stress; under the condition that an included angle exists between the shale reservoir and the horizontal plane, the effective stress is decomposed into vertical effective stress and parallel effective stress, the vertical effective stress is vertical to the upper surface of the shale reservoir, and the parallel effective stress is parallel to the upper surface of the shale reservoir.
5. The method of claim 1, wherein the determining a first elastic modulus parameter for a first sedimentary stratification of the shale reservoir and a second elastic modulus parameter and a first stiffness coefficient matrix for a second sedimentary stratification of the shale reservoir based on the shale reservoir physical model comprises: Calculating a third elastic modulus parameter of the mixture based on the non-clay mineral component and the organic component in the shale reservoir; calculating a first elastic modulus parameter of the first sedimentary stratification based on clay mineral components, sedimentary stratification factors, and the third elastic modulus parameter in the shale reservoir; Calculating a fourth elastic modulus parameter of the third deposition lamination and a first rigidity coefficient matrix of a second deposition lamination based on the first elastic modulus parameter and the crack density; A second elastic modulus parameter of the second sedimentary layering is calculated based on the fourth elastic modulus parameter, porosity, fluid properties.
6. An apparatus for analysis of a shale reservoir, the apparatus comprising: the first construction module is used for constructing a shale reservoir physical model according to geological features, sedimentary layering factors and effective stress of the shale reservoir; The first determining module is used for determining a first elastic modulus parameter of a first sedimentary stratification corresponding to the shale reservoir based on the shale reservoir physical model, and a second elastic modulus parameter and a first rigidity coefficient matrix of a second sedimentary stratification corresponding to the shale reservoir; The second construction module is used for constructing a training sample set according to the porosity, the pore pressure, the first elastic modulus parameter, the second elastic modulus parameter and the first rigidity coefficient matrix of the shale reservoir; the training module is used for training the deep learning model based on the training sample set; The second determining module is used for inputting the porosity, the pore pressure, the actually measured elastic modulus parameter and the first elastic modulus parameter of the shale reservoir into a trained deep learning model to obtain a second rigidity coefficient matrix; And the third determining module is used for determining the anisotropic strength of the shale reservoir according to the second rigidity coefficient matrix.
7. An electronic device, comprising a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface are in communication with each other via the communication bus, and wherein the memory is configured to store executable instructions that cause the processor to perform the shale reservoir analysis method of any of claims 1-5.
8. A storage medium having stored thereon a program or instructions which when executed by a processor performs the method of analysis of shale reservoirs of any of claims 1 to 5.

Description

Shale reservoir analysis method and device, electronic equipment and storage medium Technical Field The invention relates to the field of oil-gas seismic exploration and development, in particular to a shale reservoir analysis method, a shale reservoir analysis device, electronic equipment and a shale reservoir storage medium. Background China develops a large number of overmature shale reservoirs, and the shale reservoirs become dominant force for increasing the production of the reservoirs. Shale reservoirs typically exhibit VTI (VERTICAL TRANSVERSE Isotropy, vertical isotropy) properties due to the sedimentary stratification of the shale reservoir and the development of microcracks nearly horizontal with the formation, with seismic responses being greatly different from the propagation velocity of seismic waves in isotropic and anisotropic media. The inaccurate anisotropic parameters are used to influence the accuracy of seismic imaging and the subsequent elasticity and mechanical characteristic research, so that reliable basis is difficult to provide for the drilling safety and hydraulic fracturing design of the shale reservoir horizontal well. Therefore, the anisotropic high-precision prediction scheme of the shale reservoir is researched, the precision of seismic imaging is improved, and the method has important significance in aspects such as fracture prediction, oil reservoir description and the like. The shale has a complex microstructure, various factors influencing the shale anisotropic strength, and the shale anisotropic strength can be influenced by the directional arrangement of complex mineral components, organic matters and clay particles, the development of microcracks and the like. In the prior art, only a single factor is usually considered when the shale anisotropic strength is calculated, the accuracy of the obtained anisotropic strength is low, and in the prior art, the shale reservoir physical model is usually adopted to calculate the anisotropic strength, so that the data acquisition difficulty is high, and the time is consumed. Disclosure of Invention The embodiment of the invention provides a shale reservoir analysis method, a shale reservoir analysis device, electronic equipment and a storage medium, which can improve the efficiency of calculating shale anisotropy intensity. In order to solve the problems, the embodiment of the invention discloses a shale reservoir analysis method, which comprises the following steps: constructing a shale reservoir physical model according to geological features, sedimentary stratification factors and effective stress of the shale reservoir, wherein the sedimentary stratification factors are used for representing sedimentary stratification strength; Determining a first elastic modulus parameter of a first sedimentary stratification corresponding to the shale reservoir based on the shale reservoir physical model, and a second elastic modulus parameter and a first stiffness coefficient matrix of a second sedimentary stratification corresponding to the shale reservoir, wherein the first sedimentary stratification is obtained by simulating based on mineral components of the shale reservoir, and the second sedimentary stratification is obtained by simulating based on geological features of the shale reservoir; constructing a training sample set according to the porosity, the pore pressure, the first elastic modulus parameter, the second elastic modulus parameter and the first stiffness coefficient matrix of the shale reservoir, wherein a training sample in the training sample set comprises an array formed by the porosity, the pore pressure, the first elastic modulus parameter and the second elastic modulus parameter, and the first stiffness coefficient matrix is a reference result corresponding to the array; Training a deep learning model based on the training sample set; Inputting the porosity, pore pressure, measured elastic modulus parameters and the first elastic modulus parameters of the shale reservoir into a trained deep learning model to obtain a second rigidity coefficient matrix; And determining the anisotropic strength of the shale reservoir according to the second rigidity coefficient matrix. Optionally, the constructing a shale reservoir physical model according to geological features, sedimentary layering factors and effective stress of the shale reservoir comprises: Constructing a physical model corresponding to the first sedimentary stratification based on mineral components and sedimentary stratification factors of the shale reservoir; Simulating effective stress suffered by the shale reservoir according to the pressure coefficient of the shale reservoir; Calculating a second fracture density corresponding to the shale reservoir according to the effective stress and a first fracture density corresponding to the shale reservoir, wherein the first fracture density refers to the fracture density when the shale reservoir is not subjected t