A reservoir compressibility evaluation method, system, device and storage medium
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHANGQING ENGINEERING DESIGN CO LTD
- Filing Date
- 2024-11-28
- Publication Date
- 2026-05-29
Smart Images
Figure CN122114328A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of oil and gas exploration and development technology, and particularly relates to a method, system, equipment and storage medium for evaluating reservoir compressibility. Background Technology
[0002] Compressibility refers to the likelihood or ease with which a reservoir can form a complex network of volumetric fracturing fractures to achieve effective production enhancement. The significance of compressibility assessment lies in its reflection of the ease with which hydraulically fractured fractures extend and the development trend of fracture extension morphology within the reservoir's own environment. Therefore, during fracturing, compressibility criteria can be used to screen and accurately locate fracturing zones, ensuring sufficient fracture propagation and improving fracturing stimulation effectiveness.
[0003] Currently, various methods exist for evaluating reservoir compressibility. Rickman proposed using a brittleness index calculated based on Poisson's ratio and Young's modulus to represent compressibility; high Young's modulus and low Poisson's ratio tend to generate complex fractures. Buller and Enderlin et al. characterized reservoir rock compressibility through the brittleness and ductility of minerals. However, research results relying solely on single factors such as rock mechanics parameters or rock mineral composition are insufficient to reflect the comprehensive characteristics of reservoir rocks. Yuan Junliang et al. established a distribution map of reservoir compressibility based on three aspects: rock mechanics parameters, fracture toughness, and brittleness index, and studied the compressibility of shale gas reservoirs. R. Rickman et al. proposed using the normalized average of elastic modulus and Poisson's ratio as an index of shale compressibility, laying the foundation for evaluating reservoir compressibility using well logging data. Mullen and Enderlin proposed combining sediment, mineral content, natural weak points, and reservoir stress state to define a new compressibility evaluation index. Jin et al. proposed combining rock brittleness and strain energy release rate during fracturing to evaluate reservoir compressibility.
[0004] In summary, various effective methods have been developed for assessing reservoir compressibility, but each method has certain disadvantages and shortcomings. First, the factors considered are not comprehensive enough, with most compressibility assessment methods only considering a single factor or a simple superposition of multiple factors. Second, the assessment methods do not consider the mutual influence between various factors. Third, there is no definite standard for allocating weights, and the determination of weights is highly subjective, resulting in poor assessment results for reservoir compressibility. Summary of the Invention
[0005] To address the problem of poor reservoir compressibility evaluation results due to the high subjectivity in the weighting coefficients of factors influencing reservoir compressibility, this invention provides a reservoir compressibility evaluation method, system, equipment, and storage medium.
[0006] To achieve the above objectives, the present invention provides the following technical solution: This invention provides a method for evaluating reservoir compressibility, comprising: The parameter values of factors affecting reservoir compressibility are standardized by range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficients of compressibility factors are determined by combining the analytic hierarchy process (AHP) and the CRITIC method for weighting. The compressibility coefficient of the reservoir is obtained by weighting the standardized values of the compressibility factors with weighting coefficients. The compressibility of a reservoir is evaluated based on its fracturing coefficient, which guides reservoir fracturing.
[0007] The factors affecting reservoir compressibility include reservoir brittleness, hydraulic fracturing index, fracture toughness, critical fracture pressure at which natural weak surfaces open, and the degree of development of natural fractures.
[0008] The standardized values of the parameters affecting reservoir compressibility, obtained by standardizing them using range transformation or empirical assignment, include: The reservoir brittleness, fracture toughness, and critical fracture pressure of natural weak surfaces are standardized using range transformation. The hydraulic fracturing index and the degree of development of natural fractures are standardized by empirical assignment; The empirically assigned value of the hydraulic fracturing index is as follows: A value of 1 is assigned to a hydraulic crack that directly penetrates, and a value of 0 is assigned to a hydraulic crack that is captured. The empirical values assigned to the degree of development of natural cracks are as follows: The value for undeveloped cracks is 0.2, the value for moderately developed cracks is 0.5, the value for highly developed cracks is 0.8, and the values for other cases are 0.2~0.5 and 0.5~0.8.
[0009] The weighting method based on the combination of the analytic hierarchy process (AHP) and the CRITIC method, which determines the weight coefficients of compressibility factors, includes: The subjective weight coefficients of compressibility factors were obtained using the analytic hierarchy process (AHP). The objective weighting coefficients of compressibility factors were obtained using the CRITIC method; Based on the subjective and objective weights of compressibility factors, the comprehensive weight of compressibility factors is obtained, and the comprehensive weight is:
[0010] in, This is the subjective weighting coefficient. For objective weighting.
[0011] The subjective weight coefficients of compressibility factors obtained through the analytic hierarchy process are as follows: The factors affecting reservoir compressibility are stratified according to their correlations; The relative importance of each factor at each level is determined by pairwise comparisons, and a quantitative representation of the relative importance of each factor at each level is given to construct a judgment matrix. The subjective weight coefficient of the main compressibility factor is obtained by using mathematical methods to find the eigenvector corresponding to the largest eigenvalue of the judgment matrix.
[0012] The objective weighting coefficients of compressibility factors obtained through the CRITIC method include: The amount of information required to determine compressibility factors is
[0013] in, For the first The amount of information about each compressible factor; For the first The standard deviation of a compressibility factor represents the contrast intensity within a single compressibility factor; Compressibility factor and compressibility factors The correlation coefficient between them The expression:
[0014] in, Indicating compressibility factors and compressibility factors Covariance between , These represent compressibility factors. and compressibility factors The variance; The objective weighting coefficient for compressibility factors is determined as follows:
[0015] in, For the first Objective weighting coefficients of each compressibility factor.
[0016] The process of obtaining the reservoir's fracturing coefficient by weighting the standardized values of the compressibility factors with weighting coefficients includes: The fracturing coefficient of a reservoir is calculated using the following formula:
[0017] In the formula The fracturing coefficient; This is the standardized value of the compressibility factor; The weighting coefficients for compressibility factors; c is the correction coefficient; n is the number of compressibility factors.
[0018] The present invention also provides a reservoir compressibility evaluation system, comprising: The factor standardization module is used to standardize the parameter values of factors affecting reservoir compressibility by using range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficient determination module is used to determine the weight coefficients of compressibility factors based on a combination of the analytic hierarchy process and the CRITIC method. The fracturing coefficient calculation module is used to calculate the reservoir's fracturing coefficient by weighting the standardized values of the fracturing factors with weighting coefficients. The evaluation module is used to evaluate reservoir compressibility based on the reservoir's fracturing coefficient, and to guide reservoir fracturing.
[0019] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described reservoir compressibility evaluation method.
[0020] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described reservoir compressibility evaluation method.
[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention significantly improves the accuracy and comprehensiveness of reservoir evaluation by introducing the CRITIC method to conduct a thorough and detailed weight analysis of various key factors affecting reservoir compressibility. The invention comprehensively considers factors such as shale brittleness, the ease of opening natural weak points, the complexity of fracture meshes, and rock fracture toughness. These factors are systematically integrated into the evaluation model, and weights are scientifically allocated through a combination of the analytic hierarchy process (AHP) and the CRITIC method. This approach considers both the importance of each factor and their interrelationships and influences, effectively overcoming the problems of incomplete factor consideration and subjective weight allocation in previous evaluation methods, resulting in more accurate evaluation results. The application of this invention provides a more accurate and reliable basis for oil and gas field exploration and development, as well as efficient fracturing design.
[0022] Furthermore, the CRITIC method is used to assign objective weights to compressibility factors. The CRITIC method incorporates the correlation between factors into the weight calculation, reducing the influence of subjective judgment. This helps to more accurately reflect the actual importance of each factor in the evaluation system and improve the reliability of the evaluation results. Attached Figure Description
[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0024] Figure 1 This is a flowchart of the reservoir compressibility evaluation method of the present invention; Figure 2 A schematic diagram of a fracturing network in a shale gas horizontal well, as an example; Figure 3 The critical fracture pressure values for the opening of natural weak surfaces with different occurrences in the Longmaxi Formation shale of Example 1; Figure 4 This is an interpretation of the microseismic fracture monitoring in a well of the Longmaxi Formation in Example 1; Figure 5 This is a schematic diagram of the reservoir compressibility evaluation system according to a preferred embodiment of the present invention; Figure 6 This is a schematic diagram of the electronic device structure according to a preferred embodiment of the present invention. Detailed Implementation
[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.
[0026] Compressibility is the primary property to consider in reservoir hydraulic fracturing. It is influenced by many factors, and in order to comprehensively evaluate the impact of various factors on compressibility, a compressibility index model needs to be established for quantitative evaluation.
[0027] This invention proposes a method for evaluating reservoir compressibility, aiming to accurately assess reservoir compressibility, promote the full propagation of fracturing fractures in the fracturing zone, and improve the fracturing stimulation effect. For example... Figure 1 As shown, the reservoir compressibility evaluation method of the present invention includes: The parameter values of factors affecting reservoir compressibility are standardized by range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficients of compressibility factors are determined by combining the analytic hierarchy process (AHP) and the CRITIC method for weighting. The compressibility coefficient of the reservoir is obtained by weighting the standardized values of the compressibility factors with weighting coefficients. The compressibility of a reservoir is evaluated based on its fracturing coefficient, which guides reservoir fracturing.
[0028] The parameter values of factors affecting reservoir compressibility are standardized using range transformation or empirical assignment to obtain standardized values for compressibility factors, specifically: It should be noted that the main factors affecting reservoir compressibility have different units and dimensions, and the parameter values and effective ranges of each factor are different. In order to calculate the compressibility coefficient, it is necessary to standardize the parameter values.
[0029] The factors affecting reservoir compressibility include reservoir brittleness, hydraulic fracturing index, fracture toughness, critical fracture pressure at which natural weak surfaces open, and the degree of development of natural fractures.
[0030] For factors such as reservoir brittleness, fracture toughness, and critical fracture pressure at the opening of natural weak surfaces, range transformation is used for standardization. Parameters in the range transformation are divided into positive and negative indices. Positive indices are those with higher values, while negative indices are those with lower values. Shale brittleness is positively correlated with compressibility, while critical fracture pressure at the opening of natural weak surfaces and fracture toughness are negatively correlated with compressibility. Therefore, shale brittleness is a positive indicative factor, while critical fracture pressure at the opening of natural weak surfaces and fracture toughness are negative indices.
[0031] For positive indicators, the following formula is used for calculation:
[0032] For the contrarian indicator, the following formula is used for calculation:
[0033] In the formula, S is the standardized value of the parameter, X is the parameter value, maxX is the maximum value of the parameter, and minX is the minimum value of the parameter. After range transformation, the index values are all between 0 and 1, and both positive and negative indices are converted into positive indices, with the optimal value being 1 and the worst value being 0.
[0034] The hydraulic fracturing index and the degree of development of natural fractures were standardized by empirical assignment; The quantification of the hydraulic fracturing index adopts an empirical assignment method. The accuracy of the assignment depends on the comprehensive understanding of the hydraulic fracturing situation. The general scoring principle is that direct penetration of the hydraulic fracture is assigned a value of 1, and the capture of the hydraulic fracture is assigned a value of 0. The development of natural weak surfaces is quantified by using an empirical assignment method. The accuracy of the assignment depends on the comprehensive understanding of the crack development. The general scoring principle is that no crack development is assigned a value of 0.2, moderate crack development is assigned a value of 0.5, well-developed crack development is assigned a value of 0.8, and other cases are assigned values of 0.2~0.5 and 0.5~0.8.
[0035] The weighting method based on the combination of the analytic hierarchy process and the CRITIC method is used to determine the weight coefficients of the compressibility factors, specifically as follows: It should be noted that in determining the fracturing coefficient of a reservoir, different factors affect the compressibility of shale reservoirs in different ways, and the different weight values will greatly affect the accuracy of the compressibility determination. Therefore, in order to scientifically determine the magnitude of the influence of each factor on compressibility, this invention adopts a combined weighting method of analytic hierarchy process (AHP) and CRITIC method to determine the weights of the compressibility factors.
[0036] The subjective weight coefficients of compressibility factors are obtained through the analytic hierarchy process (AHP), specifically: The factors affecting reservoir compressibility are stratified according to their correlations; The relative importance of each factor at each level is determined by pairwise comparisons, and a quantitative representation of the relative importance of each factor at each level is given to construct a judgment matrix. The subjective weight coefficient of the main compressibility factor is obtained by using mathematical methods to find the eigenvector corresponding to the largest eigenvalue of the judgment matrix.
[0037] The objective weighting coefficients of compressibility factors are obtained using the CRITIC method, specifically as follows: According to the CRITIC method, c is defined as the information content of the indicators in the evaluation system. Then the information content of the j-th compressibility factor is:
[0038] in, For the first The standard deviation of a compressibility factor represents the contrast intensity within a single compressibility factor; Compressibility factor and compressibility factors The correlation coefficient between them The expression:
[0039] in, Indicating compressibility factors and compressibility factors Covariance between , These represent compressibility factors. and compressibility factors The variance.
[0040] The larger the value, the higher the value. Each compressibility factor contains more information, and its corresponding weighting coefficient should be higher. Therefore, the first... Objective weighting coefficient of each compressibility factor for
[0041] The subjective and objective weights of compressibility factors were obtained using the analytic hierarchy process (AHP) and the CRITIC method, respectively, and then the weight coefficients of each compressibility factor were derived.
[0042] in, This is the subjective weighting coefficient. For objective weighting.
[0043] The reservoir's fracturing coefficient is obtained by weighting the standardized values of the compressibility factors with weighting coefficients, specifically as follows: The fracturing coefficient of a reservoir is calculated using the following formula:
[0044] In the formula The fracturing coefficient; This is the standardized value of the compressibility factor; is the weighting coefficient of compressibility factors; c is the correction coefficient, which is an empirical value taken according to the characteristics of different reservoirs; n is the number of compressibility factors.
[0045] The complexity of the fracture network formed in a formation is closely related to the brittleness of the formation rocks and the development of natural weak surfaces. Higher formation rock brittleness, more developed natural weak surfaces, and easier opening of closed natural weak surfaces during fracturing result in a more complex fracture network. The size of the reservoir stimulation volume depends primarily on the rock's fracture toughness and the penetration characteristics of natural weak surfaces. Lower fracture toughness values, and the greater the likelihood of hydraulic fractures penetrating natural weak surfaces upon initial intersection, lead to a higher probability of obtaining a larger reservoir stimulation volume. Shale gas well production depends not only on the reservoir stimulation volume but also on the complexity of the fracture network. Only when both the reservoir stimulation volume and the complexity of the fracture network are optimal will fracturing be most effective, resulting in higher economic benefits.
[0046] Based on reservoir parameter characteristics and the formula for calculating the fracturing coefficient, compressibility is divided into three levels, as shown in Table 1. It is recommended that shale fracturing be performed on shale formations with a compressibility coefficient greater than 0.5. If such areas do not exist, areas with a high compressibility coefficient should be selected whenever possible. Under the same fracture network fracturing technology conditions, the fracture networks formed in formations with good compressibility will be significantly different from those in formations with poor compressibility. Figure 2 As shown.
[0047] Table 1. Characteristics of compressible shale reservoirs of different grades
[0048] Example 1 The formula for calculating the fracturing coefficient of a reservoir, based on the method provided by this invention, is as follows:
[0049]
[0050]
[0051]
[0052] In the formula, FI is the fracturing coefficient; It is the brittleness index; for Weighting coefficients; The degree of ease with which a naturally weak surface opens; for Weighting coefficients; It is the fracture toughness index; for Weighting coefficients; The hydraulic fracturing index; for The weighting coefficient; P is the critical pressure within the natural weak surface opening. , These represent the maximum and minimum critical fracture pressures within a naturally weak surface of arbitrary orientation, typically taken as the maximum and minimum geostress of the target layer, in MPa. This represents the type I fracture toughness value. , The maximum and minimum type I fracture toughness values in the region. ; The normalized index for fracture toughness is the fracture toughness value for Type I fracture. This is a type II fracture toughness value. , These are the maximum and minimum type II fracture toughness values in the region. ; This is the normalization index for the type II fracture toughness value. All parameters without specified units are dimensionless and range from 0 to 1.
[0053] Taking a shale gas reservoir in a certain block as an example, the specific reservoir geological parameters are shown in Table 2.
[0054] Table 2 Geological parameters of shale gas reservoirs
[0055] Note: The elastic modulus of the Longmaxi Formation shale ranges from 8 to 56 GPa, the Poisson's ratio ranges from 0.1 to 0.36, and the uniaxial tensile strength ranges from 0 to 8 MPa. Substituting the above parameters into the formula for calculating the fracturing coefficient of the constructed reservoir, we obtain: , , , , , , , , .
[0056] The calculation results show that the shale reservoirs in this area have high brittleness, and natural weak surfaces are easily opened, such as... Figure 3 As shown, the probability of forming a complex fracture network is relatively high, but hydraulic fractures cannot penetrate natural weak surfaces, and the fracture toughness index of the target layer is relatively small. It is also difficult for hydraulic fractures to extend in the matrix rock. This indicates that it is difficult to obtain a large reservoir stimulation volume after hydraulic fracturing of shale reservoirs in this area, and the overall compressibility is generally average. Figure 4 This is a microseismic monitoring image of a horizontal well in the region after volumetric fracturing. The microseismic event points are relatively dense and mainly distributed on the horizontal plane rather than along the plane perpendicular to the minimum horizontal stress. Although a complex fracture network is formed, the obtained reservoir stimulation volume is not ideal, and the compressibility of the target reservoir is generally poor, which is in complete agreement with the calculation results of the model in this invention.
[0057] like Figure 5 As shown, another object of the present invention is to provide a reservoir compressibility evaluation system, comprising: The factor standardization module is used to standardize the parameter values of factors affecting reservoir compressibility by using range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficient determination module is used to determine the weight coefficients of compressibility factors based on a combination of the analytic hierarchy process and the CRITIC method. The fracturing coefficient calculation module is used to calculate the reservoir's fracturing coefficient by weighting the standardized values of the fracturing factors with weighting coefficients. The evaluation module is used to evaluate reservoir compressibility based on the reservoir's fracturing coefficient.
[0058] like Figure 6 As shown, a third objective of the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the reservoir compressibility evaluation method.
[0059] The parameter values of factors affecting reservoir compressibility are standardized by range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficients of compressibility factors are determined by combining the analytic hierarchy process (AHP) and the CRITIC method for weighting. The compressibility coefficient of the reservoir is obtained by weighting the standardized values of the compressibility factors with weighting coefficients. The compressibility of a reservoir is evaluated based on its fracturing coefficient.
[0060] A fourth objective of this invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the reservoir compressibility evaluation method.
[0061] The parameter values of factors affecting reservoir compressibility are standardized by range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficients of compressibility factors are determined by combining the analytic hierarchy process (AHP) and the CRITIC method for weighting. The compressibility coefficient of the reservoir is obtained by weighting the standardized values of the compressibility factors with weighting coefficients. The compressibility of a reservoir is evaluated based on its fracturing coefficient.
[0062] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, 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.
[0063] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0064] 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 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0065] 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 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A method for evaluating reservoir compressibility, characterized in that, include: The parameter values of factors affecting reservoir compressibility are standardized by range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficients of compressibility factors are determined by combining the analytic hierarchy process (AHP) and the CRITIC method for weighting. The compressibility coefficient of the reservoir is obtained by weighting the standardized values of the compressibility factors with weighting coefficients. The compressibility of a reservoir is evaluated based on its fracturing coefficient, which guides reservoir fracturing.
2. The method for evaluating reservoir compressibility according to claim 1, characterized in that, The factors affecting reservoir compressibility include reservoir brittleness, hydraulic fracturing index, fracture toughness, critical fracture pressure at which natural weak surfaces open, and the degree of development of natural fractures.
3. The method for evaluating reservoir compressibility according to claim 2, characterized in that, The standardized values of the parameters affecting reservoir compressibility, obtained by standardizing them using range transformation or empirical assignment, include: The reservoir brittleness, fracture toughness, and critical fracture pressure of natural weak surfaces are standardized using range transformation. The hydraulic fracturing index and the degree of development of natural fractures are standardized by empirical assignment; The empirically assigned value of the hydraulic fracturing index is as follows: A value of 1 is assigned to a hydraulic crack that directly penetrates, and a value of 0 is assigned to a hydraulic crack that is captured. The empirical values assigned to the degree of development of natural cracks are as follows: The value for undeveloped cracks is 0.2, the value for moderately developed cracks is 0.5, the value for highly developed cracks is 0.8, and the values for other cases are 0.2~0.5 and 0.5~0.
8.
4. The method for evaluating reservoir compressibility according to claim 1, characterized in that, The weighting method based on the combination of the analytic hierarchy process (AHP) and the CRITIC method, which determines the weight coefficients of compressibility factors, includes: The subjective weight coefficients of compressibility factors were obtained using the analytic hierarchy process (AHP). The objective weighting coefficients of compressibility factors were obtained using the CRITIC method; Based on the subjective and objective weights of compressibility factors, the comprehensive weight of compressibility factors is obtained, and the comprehensive weight is: in, This is the subjective weighting coefficient. For objective weighting.
5. A method for evaluating reservoir compressibility according to claim 4, characterized in that, The subjective weight coefficients of compressibility factors obtained through the analytic hierarchy process are as follows: The factors affecting reservoir compressibility are stratified according to their correlations; The relative importance of each factor at each level is determined by pairwise comparisons, and a quantitative representation of the relative importance of each factor at each level is given to construct a judgment matrix. The subjective weight coefficient of the main compressibility factor is obtained by using mathematical methods to find the eigenvector corresponding to the largest eigenvalue of the judgment matrix.
6. A method for evaluating reservoir compressibility according to claim 4, characterized in that, The objective weighting coefficients of compressibility factors obtained through the CRITIC method include: The amount of information required to determine compressibility factors is in, For the first The amount of information about each compressible factor; For the first The standard deviation of a compressibility factor represents the contrast intensity within a single compressibility factor; Compressibility factor and compressibility factors The correlation coefficient between them The expression: in, Indicating compressibility factors and compressibility factors Covariance between , These represent compressibility factors. and compressibility factors The variance; The objective weighting coefficient for compressibility factors is determined as follows: in, For the first Objective weighting coefficients of each compressibility factor.
7. The method for evaluating reservoir compressibility according to claim 1, characterized in that, The process of obtaining the reservoir's fracturing coefficient by weighting the standardized values of the compressibility factors with weighting coefficients includes: The fracturing coefficient of a reservoir is calculated using the following formula: In the formula The fracturing coefficient; This is the standardized value of the compressibility factor; The weighting coefficients for compressibility factors; c is the correction coefficient; n is the number of compressibility factors.
8. A reservoir compressibility evaluation system, characterized in that, include: The factor standardization module is used to standardize the parameter values of factors affecting reservoir compressibility by using range transformation or empirical assignment to obtain standardized values of compressibility factors. The weight coefficient determination module is used to determine the weight coefficients of compressibility factors based on a combination of the analytic hierarchy process and the CRITIC method. The fracturing coefficient calculation module is used to calculate the reservoir's fracturing coefficient by weighting the standardized values of the fracturing factors with weighting coefficients. The evaluation module is used to evaluate reservoir compressibility based on the reservoir's fracturing coefficient, and to guide reservoir fracturing.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the reservoir compressibility evaluation method according to any one of claims 1-7.
10. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the reservoir compressibility evaluation method according to any one of claims 1-7.