Multi-parameter fusion shale compressibility evaluation method and system

Abstract

The invention relates to a multi-parameter fusion shale compressibility evaluation method and system, and the method comprises the steps: directly starting from the characteristics of shale compressibility, and carrying out the quantitative calculation of the fracturing index of a shale reservoir; on the basis of key parameters such as porosity, permeability Young modulus, brittleness index, fracture toughness and tensile strength, three on-site fracturing construction parameters including the ratio of sand to liquid, the ratio of slick water and the ratio of medium sand or above are fused, evaluation parameters are all changed into positive indexes after being subjected to normalization processing, and then the weight of each parameter is calculated through a variable coefficient method; and finally, creating a compressibility evaluation method capable of comprehensively, reasonably and quantitatively reflecting the shale oil reservoir, wherein the model evaluates the compressibility of the shale reservoir from multiple angles. According to the method, the compressibility of the shale reservoir can be objectively, comprehensively and scientifically evaluated, interference of human factors is reduced, the overall efficiency and effect of fracturing operation are remarkably improved, and the fracturing transformation effect and the reservoir utilization degree of the shale reservoir are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of oilfield development, and in particular relates to a multi-parameter fusion shale compressibility evaluation method and system. Background Art

[0002] The compressibility of shale reservoirs depends on factors such as the difference in ground stress, the brittleness of rocks, and the development of natural fractures. It is a comprehensive indicator. At present, international and domestic research mainly focuses on how to quantify the brittleness index of shale and use the brittleness index to directly evaluate the compressibility of reservoirs. However, the indicators for evaluating the fracturing ability of shale are not limited to the brittleness index itself. Many factors will also affect the fracturing effect of shale, especially the brittleness index and the production after shale fracturing. It is often difficult to establish a direct relationship. Breyer et al. emphasized the importance of shale brittleness and toughness to fracturing ability; Chen Yun et al. proposed a new method for evaluating rock brittleness based on energy dissipation; Yuan Junliang et al. combined the brittleness index with rock mechanical parameters to evaluate the fracturing ability of formations; the elastic parameter method introduced by Rickman et al. is a widely used brittleness evaluation method; Li Qinghui et al. pointed out that the mineral composition of rocks has a significant impact on the brittleness index. In addition, some researchers have proposed to evaluate the fracturing ability of shale based on construction pressure inversion, but this method may have a certain empirical judgment component in practical applications because it is difficult to accurately identify the fracture point.

[0003] Shale oil reservoirs have extremely poor physical properties. To achieve their economical and efficient exploitation, hydraulic fracturing has become an indispensable process technology. Before hydraulic fracturing of reservoirs, evaluating the compressibility of reservoirs is a crucial prerequisite. Reservoir compressibility refers to the possibility of forming a complex fracture network structure in the reservoir and achieving a significant transformation volume under the same fracturing technology conditions, as well as the probability of ultimately achieving a high recovery rate. At present, international research on the evaluation of shale oil fracturing is not comprehensive enough. The existing evaluation methods mainly focus on the identification of geological "sweet spots" or engineering "sweet spots", and the combination of the two is relatively general. In the field of shale gas, especially for areas where the distribution of geological static indicators (such as porosity, permeability, oil and gas saturation, total organic carbon content, gas content, etc.) is relatively stable, the formation of a persistent and interconnected complex fracture network is the core goal of hydraulic fracturing transformation. In order to achieve this goal, it is necessary to conduct high-quality evaluation of key shale physical property parameters.

[0004] In the evaluation of engineering "sweet spots", the rock brittleness index is an indispensable parameter for characterizing the fracturability of reservoirs, but there are deficiencies in using a single brittleness index to evaluate reservoir fracturability. In view of the fact that rock brittleness is difficult to accurately characterize reservoir fracturability, domestic and foreign scholars have introduced rock fracture toughness and proposed a fracturability index that combines brittleness index and fracture toughness for shale gas reservoir fracturability evaluation. However, a single brittleness index and fracture toughness may not be able to fully and accurately evaluate the fracturability of reservoirs. For example, some reservoirs with high brittleness index and fracture toughness may not have ideal actual fracturability effects due to the influence of other factors (such as ground stress state, degree of fracture development, etc.). Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a multi-parameter fusion shale compressibility evaluation method and system;

[0006] In order to create a fracturing evaluation model that can comprehensively consider multiple factors, the present invention adds three field fracturing construction parameters such as comprehensive sand-to-liquid ratio, slickwater ratio, and medium sand and above ratio on the basis of key geological parameters such as porosity, permeability Young's modulus, brittleness index, fracture toughness, and tensile strength. The present invention proposes a comprehensive evaluation method that can quantitatively measure the fracturing potential of shale oil reservoirs. This model evaluates the fracturing potential of shale reservoirs from multiple dimensions.

[0007] In the present invention, firstly, a calculation model of key parameters such as porosity, permeability Young's modulus, brittleness index, fracture toughness, and tensile strength is constructed through core description, logging and other curves; then, on this basis, the on-site fracturing construction parameters (comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio) are added, and finally, the weight of each evaluation parameter is obtained by using the coefficient of variation method, and the weight is multiplied by the normalized evaluation parameter and added in sequence, and the result is used as the formation compressibility evaluation index. The method of the present invention improves the overall efficiency and effect of fracturing operations and solves the shortcomings of existing evaluation methods.

[0008] The present invention also provides a shale compressibility evaluation system based on stress inversion.

[0009] The technical solution of the present invention is:

[0010] A multi-parameter fusion shale compressibility evaluation method, comprising:

[0011] S1. Calculate the rock porosity compressibility evaluation index through core description and logging curves. The rock porosity compressibility evaluation index is obtained by using the multivariate regression equation of acoustic wave time difference, density, organic carbon content, mudstone index and porosity, and the permeability is obtained by the flow unit method;

[0012] S2. According to the conventional logging interpretation results, the elastic rock mechanics parameters are statistically analyzed to calculate the Young's modulus and Poisson's ratio of the rock;

[0013] S3, calculating the brittle index compressibility evaluation index based on the Young's modulus and Poisson's ratio calculated in S2, and obtaining the brittle index compressibility evaluation index;

[0014] S4. Based on the analysis of reservoir and mechanical parameters, shale density, gamma, and acoustic time-difference logging data are used as independent variables to perform function regression to obtain a multivariate regression fitting function, and type I and type II fracture toughness indexes of each fracturing interval are calculated;

[0015] S5. Taking the compressibility evaluation index of the tensile strength index as the objective function and taking the shale density and the conventional logging data of the longitudinal wave velocity as the independent variables, a function regression is performed to obtain the compressibility evaluation index of the tensile strength index;

[0016] S6. Calculate the comprehensive sand-liquid ratio, the proportion of slick water, and the proportion of medium sand and above;

[0017] S7. The eight parameters are normalized by using the range transformation method, and the parameters with different units and dimensions are divided into positive indicators and negative indicators. After normalization, they all become positive indicators; the eight parameters include rock porosity, permeability, Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-liquid ratio, slick water ratio and medium sand and above ratio;

[0018] S8. Use the coefficient of variation method to calculate the weights of eight parameters: rock porosity, permeability, Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-to-liquid ratio, slickwater ratio, and medium sand and above ratio. Multiply the weights with the normalized evaluation parameters and add them up in sequence. Use the results as the formation compressibility evaluation index to complete the shale compressibility evaluation.

[0019] According to the preferred embodiment of the present invention, the rock porosity is obtained by using logging interpretation data, and the calculation formula is as follows:

[0020]

[0021] TOC=40.6-15.6*DEN+0.013*GR+0.009*CNL (2)

[0022] Φ=0.32*AC-0.55*DEN+0.84*TOC-0.48*SH+8.67 (3)

[0023] Where: SH is the mudstone index; TOC is the organic carbon content; DEN is the rock density; GR is the natural gamma logging value of the estimated well section; GR max is the natural gamma logging value at pure mudstone; GRmin is the natural gamma logging value at pure sandstone; CNL is the compensated neutron; AC is the acoustic time difference; Φ is the rock porosity.

[0024] According to the preferred embodiment of the present invention, the permeability is calculated by the flow index, and the calculation formula is as follows:

[0025]

[0026] K=0.0012×I n (5)

[0027] Where K is permeability, mD; I is flow index, μs / m; S is total Stoneley wave time difference, μs / m, extracted from array acoustic logging time difference; ρm is mud density, g / cm 3 ; Km is the mud bulk modulus, obtained from mud density and longitudinal and shear wave velocities, MPa; G is the formation shear modulus, obtained from density logging and shear wave velocity, MPa.

[0028] Preferably, according to the present invention, the Young's modulus calculation formula is as follows:

[0029]

[0030] Where: E is Young's modulus; Δt is the longitudinal wave time difference; Δt s is the shear wave time difference; ρ is the rock density.

[0031] Preferably, according to the present invention, the Poisson's ratio calculation formula is as follows:

[0032]

[0033] Where: ν is the static Poisson's ratio of rock; Δt s is the transverse wave time difference; Δt is the longitudinal wave time difference.

[0034] Preferably, according to the present invention, the brittleness index is calculated using Young's modulus and Poisson's ratio, and the calculation formula is as follows:

[0035]

[0036] Where: Brit is the brittleness index of rock, dimensionless; E is Young's modulus, GPa; v is the static Poisson's ratio of rock.

[0037] According to the preferred embodiment of the present invention, the type I and type II fracture toughness index K Ⅰ and K Ⅱ Using logging interpretation data, the calculation formula is as follows:

[0038]

[0039] Where: ρ is shale density; Vcl is shale mud content; DT is acoustic time difference, μm / s.

[0040] Preferably, according to the present invention, the tensile strength is calculated by the following formula:

[0041] σ t =14.91ln(V p )+22.41ln(ρ)-140.2 (11)

[0042] Where: t is the tensile strength; ρ is the shale density; V p is the longitudinal wave velocity.

[0043] Preferably, according to the present invention, each parameter is normalized by using the range transformation method, and each parameter with different units and dimensions is divided into a positive index and a negative index. After normalization, all parameters become positive indicators. The calculation method of the positive index and the negative index is as follows:

[0044] Among them, the positive indicators are as follows:

[0045]

[0046] Among them, the negative indicators are as follows:

[0047]

[0048] Where S1 is the normalized value of the positive parameter; S2 is the normalized value of the negative parameter; X max is the maximum value of the parameter; X min is the minimum value of the parameter; X is the parameter value.

[0049] Preferably, according to the present invention, the coefficient of variation method is used to obtain the weight of each parameter, and the calculation formula is as follows:

[0050]

[0051] Where: i = 1, ..., m; j = 1, ..., n; m is the total number of evaluation indicators whose weights are to be determined; n is the number of samples for each evaluation indicator; w i is the i-th parameter weight; C i is the coefficient of variation of the i-th parameter; σ i is the standard deviation of the i-th parameter; μ i is the average value of the i-th parameter; r ij is the sample matrix of the i-th parameter evaluation index.

[0052] Preferably, the weights are multiplied by the normalized evaluation parameters respectively and added in sequence, and the results are used as the formation compressibility evaluation index; the calculation formula is as follows:

[0053]

[0054] Where: I CF is the formation compressibility evaluation index; x i is the i-th evaluation index after normalization; W i The i-th weight of the eight parameters determined by the coefficient of variation method.

[0055] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a multi-parameter fusion shale compressibility evaluation method when executing the computer program.

[0056] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a multi-parameter fusion shale compressibility evaluation method.

[0057] A multi-parameter fusion shale compressibility evaluation system, including:

[0058] The rock porosity and permeability compressibility evaluation index calculation module is configured to: calculate the rock porosity compressibility evaluation index through core description and logging curve, wherein the rock porosity compressibility evaluation index is obtained by using the multivariate regression equation of acoustic wave time difference, density, organic carbon content, mudstone index and porosity, and the permeability is obtained by the flow unit method;

[0059] The Young's modulus and Poisson's ratio calculation module is configured to: calculate the Young's modulus and Poisson's ratio of the rock based on the results of conventional well logging interpretation and statistical elastic rock mechanics parameters;

[0060] The brittle index compressibility evaluation index calculation module is configured to: calculate the brittle index compressibility evaluation index based on the calculated Young's modulus and Poisson's ratio to obtain the brittle index compressibility evaluation index;

[0061] The fracture toughness index calculation module is configured as follows: based on the analysis of reservoir and mechanical parameters, a multivariate regression fitting function is obtained by function regression using shale density, gamma, and acoustic time difference logging data as independent variables, and the type I and type II fracture toughness indexes of each fracturing interval are calculated;

[0062] The tensile strength index compressibility evaluation index calculation module is configured as follows: taking the tensile strength index compressibility evaluation index as the target function and taking the shale density and the conventional logging data of the longitudinal wave velocity as the independent variables to perform function regression, thereby obtaining the tensile strength index compressibility evaluation index;

[0063] The calculation module of comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio is configured to: calculate the comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio; the normalization processing module is configured to: use the range transformation method to normalize the eight parameters, and divide the parameters with different units and dimensions into positive indicators and negative indicators, and all become positive indicators after normalization; the eight parameters include rock porosity, permeability, Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio;

[0064] The shale compressibility evaluation module is configured as follows: the weights of eight parameters, including rock porosity, permeability, Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-to-liquid ratio, slickwater ratio, and medium sand and above ratio, are calculated using the coefficient of variation method; the weights are multiplied by the normalized evaluation parameters and added in sequence; the results are used as the formation compressibility evaluation index to complete the shale compressibility evaluation.

[0065] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0066] 1. The present invention combines the five main influencing factors of formation compressibility index, namely porosity, permeability, Young's modulus, brittleness index, fracture toughness, and tensile strength, and determines the weight of each influencing factor according to the coefficient of variation method; at the same time, it integrates the three on-site fracturing construction parameters of comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio, and creates a method for evaluating the compressibility of shale reservoirs in an all-round and reasonable quantitative manner. This result changes the deficiency that the evaluation of shale compressibility is mainly focused on the brittleness index parameter.

[0067] 2. The present invention establishes a multi-parameter fusion shale compressibility evaluation method and system. In view of the fact that shale compressibility is a comprehensive representation of reservoir rock characteristics and construction parameters, a new method for evaluating shale compressibility is proposed from the perspective of fracture rupture, extension and filling, taking into account reservoir rock characteristics and construction parameters.

[0068] 3. The present invention provides a new method for evaluating the effect of shale fracturing transformation using construction data. In the absence of microseismic monitoring and output profile test data, the method can still effectively evaluate the fracturing effect, which is of great significance for realizing the "one section, one policy, fine fracturing" of shale gas wells. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a schematic diagram of the technical route of the multi-parameter fusion shale compressibility evaluation method of the present invention;

[0070] Figure 2 It is a schematic diagram of explaining the multi-parameter fusion shale compressibility evaluation method of the present invention;

[0071] Figure 3 It is a schematic diagram of regression data of comprehensive compressibility results and field production evaluated by using the multi-parameter fusion shale compressibility evaluation method of the present invention. DETAILED DESCRIPTION

[0072] The present invention will be further defined below in conjunction with the accompanying drawings and embodiments, but is not limited thereto.

[0073] Example 1

[0074] A multi-parameter fusion shale compressibility evaluation method, comprising:

[0075] S1. Calculate the rock porosity compressibility evaluation index through core description and logging curves. The rock porosity compressibility evaluation index is obtained by using the multivariate regression equation of acoustic wave time difference, density, organic carbon content, mudstone index and porosity. The permeability compressibility evaluation index can be calculated by flow unit parameters.

[0076] S2. According to the conventional logging interpretation results, the elastic rock mechanics parameters are statistically analyzed to calculate the Young's modulus and Poisson's ratio of the rock;

[0077] S3, calculating the brittle index compressibility evaluation index based on the Young's modulus and Poisson's ratio calculated in S2, and obtaining the brittle index compressibility evaluation index;

[0078] S4. Based on the analysis of reservoir and mechanical parameters, shale density, gamma, and acoustic time-difference logging data are used as independent variables to perform function regression to obtain a multivariate regression fitting function, and type I and type II fracture toughness indexes of each fracturing interval are calculated;

[0079] S5. Taking the compressibility evaluation index of the tensile strength index as the objective function and taking the shale density and the conventional logging data of the longitudinal wave velocity as the independent variables, a function regression is performed to obtain the compressibility evaluation index of the tensile strength index;

[0080] S6. Use the amount of added sand, total liquid, slick water, 40 / 70 mesh proppant, 30 / 50 mesh proppant and total proppant obtained from the actual field fracturing data to calculate the comprehensive sand-to-liquid ratio, slick water percentage, and medium sand and above percentage; the comprehensive sand-to-liquid ratio refers to the ratio of the amount of added sand to the total liquid; the slick water percentage refers to the ratio of the slick water percentage to the total liquid; the medium sand and above percentage refers to the ratio of the 40 / 70 mesh and 30 / 50 mesh proppant to the total proppant;

[0081] S7. The eight parameters are normalized by using the range transformation method, and the parameters with different units and dimensions are divided into positive indicators and negative indicators. After normalization, they all become positive indicators; the eight parameters include rock porosity, permeability, Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-liquid ratio, slick water ratio and medium sand and above ratio;

[0082] S8. Use the coefficient of variation method to calculate the weights of eight parameters, including rock porosity (rock porosity compressibility evaluation index), Young's modulus, brittleness index (brittleness index compressibility evaluation index), fracture toughness index, tensile strength (tensile strength index compressibility evaluation index), comprehensive sand-to-liquid ratio, slickwater ratio and medium sand and above ratio. Multiply the weights with the normalized evaluation parameters and add them up in sequence. Use the results as the formation compressibility evaluation index to complete the shale compressibility evaluation.

[0083] Example 2

[0084] The multi-parameter fusion shale compressibility evaluation method according to Example 1 is different in that:

[0085] The rock porosity is obtained using logging interpretation data, and the calculation formula is as follows:

[0086]

[0087] TOC=40.6-15.6*DEN+0.013*GR+0.009*CNL (2)

[0088] Φ=0.32*AC-0.55*DEN+0.84*TOC-0.48*SH+8.67 (3)

[0089] Where: SH is the mudstone index; TOC is the organic carbon content; DEN is the rock density; GR is the natural gamma logging value of the estimated well section; GR max is the natural gamma logging value at pure mudstone; GR min is the natural gamma logging value at pure sandstone; CNL is the compensated neutron; AC is the acoustic time difference; Φ is the rock porosity.

[0090] The permeability needs to be further calculated through the flow index. The relevant calculation formula is as follows:

[0091]

[0092] K=0.0012×I n (5)

[0093] Where K is permeability, mD; I is flow index, μs / m; S is total Stoneley wave time difference, μs / m, extracted from array acoustic logging time difference; ρm is mud density, g / cm 3 ; Km is the mud bulk modulus, obtained from mud density and longitudinal and shear wave velocities, MPa; G is the formation shear modulus, obtained from density logging and shear wave velocity, MPa;

[0094] The Young's modulus calculation formula is as follows:

[0095]

[0096] Where: E is Young's modulus; Δt is the longitudinal wave time difference; Δt s is the shear wave time difference; ρ is the rock density.

[0097] The Poisson's ratio is calculated as follows:

[0098]

[0099] Where: ν is the static Poisson's ratio of rock; Δt s is the transverse wave time difference; Δt is the longitudinal wave time difference.

[0100] The brittleness index is calculated using Young's modulus and Poisson's ratio, and the calculation formula is as follows:

[0101]

[0102] Where: Brit is the brittleness index of rock, dimensionless; E is Young's modulus, GPa; v is the static Poisson's ratio of rock.

[0103] Type I and Type II fracture toughness index K Ⅰ and K Ⅱ Using logging interpretation data, the calculation formula is as follows:

[0104]

[0105] Where: ρ is shale density; Vcl is shale mud content; DT is acoustic time difference, μm / s.

[0106] The tensile strength is calculated using the following formula:

[0107] σ t =14.91ln(V p )+22.41ln(ρ)-140.2 (11)

[0108] Where: t is the tensile strength; ρ is the shale density; V p is the longitudinal wave velocity.

[0109] The range transformation method is used to normalize the parameters, and the parameters with different units and dimensions are divided into positive indicators and negative indicators. After normalization, they all become positive indicators. The calculation methods of positive indicators and negative indicators are as follows:

[0110] Among them, the positive indicators are as follows:

[0111]

[0112] Among them, the negative indicators are as follows:

[0113]

[0114] Where S1 is the normalized value of the positive parameter; S2 is the normalized value of the negative parameter; X max is the maximum value of the parameter; X min is the minimum value of the parameter; X is the parameter value.

[0115] The coefficient of variation method is used to obtain the weight of each parameter. The calculation formula is as follows:

[0116]

[0117] Where: i = 1, ..., m; j = 1, ..., n; m is the total number of evaluation indicators whose weights are to be determined; n is the number of samples for each evaluation indicator; w i is the i-th parameter weight; C i is the coefficient of variation of the i-th parameter; σ i is the standard deviation of the i-th parameter; μ i is the average value of the i-th parameter; r ij is the sample matrix of the i-th parameter evaluation index.

[0118] Table 1 Weight table of each parameter calculated by coefficient of variation method;

[0119]

[0120] The weights are multiplied by the normalized evaluation parameters and added in sequence, and the results are used as the formation compressibility evaluation index; the calculation formula is as follows:

[0121]

[0122] Where: I CF is the formation compressibility evaluation index; x i is the i-th evaluation index after normalization; W i The i-th weight of the eight parameters determined by the coefficient of variation method.

[0123] Figure 1 This is a schematic diagram of electrical logging interpretation of well TKC1-1H-3Ckl; Figure 2This is a schematic diagram of electrical logging interpretation in well TKC1-3H-3Ckl.

[0124] Example 3

[0125] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the multi-parameter fusion shale compressibility evaluation method described in Example 1 or 2 when executing the computer program.

[0126] Example 4

[0127] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the multi-parameter fusion shale compressibility evaluation method described in Example 1 or 2.

[0128] Example 5

[0129] A multi-parameter fusion shale compressibility evaluation system, including:

[0130] The rock porosity and permeability compressibility evaluation index calculation module is configured to: calculate the rock porosity compressibility evaluation index through core description and logging curve, wherein the rock porosity compressibility evaluation index is obtained by using the multivariate regression equation of acoustic wave time difference, density, organic carbon content, mudstone index and porosity, and the permeability compressibility evaluation index can be calculated by flow unit parameters;

[0131] The Young's modulus and Poisson's ratio calculation module is configured to: calculate the Young's modulus and Poisson's ratio of the rock based on the results of conventional well logging interpretation and statistical elastic rock mechanics parameters;

[0132] The brittle index compressibility evaluation index calculation module is configured to: calculate the brittle index compressibility evaluation index based on the calculated Young's modulus and Poisson's ratio to obtain the brittle index compressibility evaluation index;

[0133] The fracture toughness index calculation module is configured as follows: based on the analysis of reservoir and mechanical parameters, a multivariate regression fitting function is obtained by function regression using shale density, gamma, and acoustic time difference logging data as independent variables, and the type I and type II fracture toughness indexes of each fracturing interval are calculated;

[0134] The tensile strength index compressibility evaluation index calculation module is configured as follows: taking the tensile strength index compressibility evaluation index as the target function and taking the shale density and the conventional logging data of the longitudinal wave velocity as the independent variables to perform function regression, thereby obtaining the tensile strength index compressibility evaluation index;

[0135] The calculation module of comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio is configured to: calculate the comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio; the normalization processing module is configured to: use the range transformation method to normalize the eight parameters, and divide the parameters with different units and dimensions into positive indicators and negative indicators, and all become positive indicators after normalization; the eight parameters include rock porosity, permeability, Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio;

[0136] The shale compressibility evaluation module is configured as follows: the weights of eight parameters, including rock porosity, permeability Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-to-liquid ratio, slick water ratio, and medium sand and above ratio, are calculated using the coefficient of variation method; the weights are multiplied by the normalized evaluation parameters and added in sequence; the results are used as the formation compressibility evaluation index to complete the shale compressibility evaluation.

[0137] The above are only some preferred embodiments of the present invention. Any person skilled in the art may modify the above technical solutions or modify them into equivalent technical solutions. Therefore, the corresponding simple modifications or equivalent transformations made according to the technical solutions of the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. A multi-parameter fusion shale compressibility evaluation method, characterized in that: include: S1. Calculate the rock porosity compressibility evaluation index through core description and logging curves, where the rock porosity compressibility evaluation index is obtained using the multivariate regression equation of acoustic wave time difference, density, organic carbon content, mudstone index and porosity; S2. According to the conventional logging interpretation results, the elastic rock mechanics parameters are statistically analyzed to calculate the Young's modulus and Poisson's ratio of the rock; S3, calculating the brittle index compressibility evaluation index based on the Young's modulus and Poisson's ratio calculated in S2, and obtaining the brittle index compressibility evaluation index; S4. Based on the analysis of reservoir and mechanical parameters, shale density, gamma, and acoustic time-difference logging data are used as independent variables to perform function regression to obtain a multivariate regression fitting function, and type I and type II fracture toughness indexes of each fracturing interval are calculated; S5. Taking the compressibility evaluation index of the tensile strength index as the objective function and taking the shale density and the conventional logging data of the longitudinal wave velocity as the independent variables, a function regression is performed to obtain the compressibility evaluation index of the tensile strength index; S6. Calculate the comprehensive sand-liquid ratio, the proportion of slick water, and the proportion of medium sand and above; S7. The eight parameters are normalized by using the range transformation method, and the parameters with different units and dimensions are divided into positive indicators and negative indicators. After normalization, they all become positive indicators; the eight parameters include rock porosity, permeability Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-liquid ratio, slick water ratio and medium sand and above ratio; S8. Use the coefficient of variation method to calculate the weights of eight parameters, including rock porosity, permeability Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-to-liquid ratio, slickwater ratio and medium sand and above ratio. Multiply the weights with the normalized evaluation parameters and add them up in sequence. Use the results as the formation compressibility evaluation index to complete the shale compressibility evaluation.

2. A multi-parameter fusion shale compressibility evaluation method according to claim 1, characterized in that: The rock porosity is obtained using logging interpretation data, and the calculation formula is as follows: TOC=40.6-15.6*DEN+0.013*GR+0.009*CNL (2) Φ=0.32*AC-0.55*DEN+0.84*TOC-0.48*SH+8.67 (3) Where: SH is the mudstone index; TOC is the organic carbon content; DEN is the rock density; GR is the natural gamma logging value of the estimated well section; GR max is the natural gamma logging value at pure mudstone; GR min is the natural gamma logging value at pure sandstone; CNL is the compensated neutron; AC is the acoustic time difference; Φ is the rock porosity; Further preferably, the Young's modulus calculation formula is as follows: Where: E is Young's modulus; Δt is the longitudinal wave time difference; Δt s is the shear wave time difference; ρ is the rock density.

3. A multi-parameter fusion shale compressibility evaluation method according to claim 1, characterized in that: The Poisson's ratio is calculated as follows: Where: ν is the static Poisson's ratio of rock; Δt s is the transverse wave time difference; Δt is the longitudinal wave time difference; Further preferably, the brittleness index is calculated using Young's modulus and Poisson's ratio, and the calculation formula is as follows: Where: Brit is the brittleness index of rock, dimensionless; E is Young's modulus, GPa; v is the static Poisson's ratio of rock; Further preferably, the type I and type II fracture toughness index K Ⅰ and K Ⅱ Using logging interpretation data, the calculation formula is as follows: Where: ρ is shale density; Vcl is shale mud content; DT is acoustic time difference, μm / s.

4. A multi-parameter fusion shale compressibility evaluation method according to claim 1, characterized in that: The tensile strength is calculated using the following formula: s t =14.91ln(V p )+22.41ln(ρ)-140.2 (9) Where: t is the tensile strength; ρ is the shale density; V p is the longitudinal wave velocity.

5. A multi-parameter fusion shale compressibility evaluation method according to claim 1, characterized in that: The range transformation method is used to normalize the parameters, and the parameters with different units and dimensions are divided into positive indicators and negative indicators. After normalization, they all become positive indicators. The calculation methods of positive indicators and negative indicators are as follows: Among them, the positive indicators are as follows: Among them, the negative indicators are as follows: Where S1 is the normalized value of the positive parameter; S2 is the normalized value of the negative parameter; X max is the maximum value of the parameter; X min is the minimum value of the parameter; X is the parameter value.

6. A multi-parameter fusion shale compressibility evaluation method according to claim 1, characterized in that: The coefficient of variation method is used to obtain the weight of each parameter. The calculation formula is as follows: Where: i = 1, ..., m; j=1,…,n; m is the total number of evaluation indicators whose weights are to be determined; n is the number of samples for each evaluation indicator; w i is the i-th parameter weight; C i is the coefficient of variation of the i-th parameter; σ i is the standard deviation of the i-th parameter; μ i is the average value of the i-th parameter; r ij is the sample matrix of the i-th parameter evaluation index.

7. A multi-parameter fusion shale compressibility evaluation method according to claim 1, characterized in that: The weights are multiplied by the normalized evaluation parameters and added in sequence, and the results are used as the formation compressibility evaluation index; the calculation formula is as follows: Where: I CF is the formation compressibility evaluation index; x i is the i-th evaluation index after normalization; w i The i-th weight of the eight parameters determined by the coefficient of variation method.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a multi-parameter fusion shale compressibility evaluation method according to any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a multi-parameter fusion shale compressibility evaluation method according to any one of claims 1 to 7 are implemented.

10. A multi-parameter fusion shale compressibility evaluation system, characterized in that: include: The rock porosity and permeability compressibility evaluation index calculation module is configured to: calculate the rock porosity compressibility evaluation index through core description and logging curve, wherein the rock porosity compressibility evaluation index is obtained by using the multivariate regression equation of acoustic wave time difference, density, organic carbon content, mudstone index and porosity, and the permeability is obtained by the flow unit method; The Young's modulus and Poisson's ratio calculation module is configured to: calculate the Young's modulus and Poisson's ratio of the rock based on the results of conventional well logging interpretation and statistical elastic rock mechanics parameters; The brittle index compressibility evaluation index calculation module is configured to: calculate the brittle index compressibility evaluation index based on the calculated Young's modulus and Poisson's ratio to obtain the brittle index compressibility evaluation index; The fracture toughness index calculation module is configured as follows: based on the analysis of reservoir and mechanical parameters, a multivariate regression fitting function is obtained by function regression using shale density, gamma, and acoustic time difference logging data as independent variables, and the type I and type II fracture toughness indexes of each fracturing interval are calculated; The tensile strength index compressibility evaluation index calculation module is configured as follows: taking the tensile strength index compressibility evaluation index as the target function and taking the shale density and the conventional logging data of the longitudinal wave velocity as the independent variables to perform function regression, thereby obtaining the tensile strength index compressibility evaluation index; The calculation module of comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio is configured as follows: the comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio are calculated; the normalization processing module is configured as follows: the eight parameters are normalized by using the range transformation method, and the parameters with different units and dimensions are divided into positive indicators and negative indicators, and all become positive indicators after normalization; the eight parameters include rock porosity, permeability Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-liquid ratio, slickwater ratio, and medium sand and above ratio; The shale compressibility evaluation module is configured as follows: the weights of eight parameters, including rock porosity, permeability Young's modulus, brittleness index, fracture toughness index, tensile strength, comprehensive sand-to-liquid ratio, slick water ratio, and medium sand and above ratio, are calculated using the coefficient of variation method; the weights are multiplied by the normalized evaluation parameters and added in sequence; the results are used as the formation compressibility evaluation index to complete the shale compressibility evaluation.

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