A method for quantitatively evaluating compressive resistance of interlayer in combined development area of tight oil and shale oil

Abstract

The application relates to a method for quantitatively evaluating the compression resistance of a tight oil and shale oil superimposed development zone, and relates to the technical field of oil and gas field exploration and development. The method first uses well logging curve interpretation to interpret the lithology and thickness, and then obtains the rock mechanics parameters of the reservoir and the barrier, and on this basis, the quantitative evaluation of the compression resistance of the barrier is carried out, so that the pressure bearing capacity and fracture blocking capacity of the barrier between the target layer and the adjacent development zone are effectively characterized. According to the evaluation result of the compression resistance of the barrier, the fracturing construction parameters and the fracturing scale of the tight oil or the shale oil can be further optimized, so that the fracturing fracture expansion is controlled within the pressure bearing range of the barrier, the fracturing fracture is prevented from penetrating the barrier and communicating with the adjacent water injection development zone, and thus the water production problem in the oil testing and production process is effectively prevented. Meanwhile, on the basis of ensuring that the target reservoir is effectively transformed, the optimization design of the fracturing scheme is realized, the reservoir transformation effect and the single well production are improved, and finally the development benefit of the tight oil or the shale oil is maximized.

Description

Technical Field

[0001] This invention relates to the fields of oil and gas field exploration and development, rock physical property analysis, and quantitative evaluation of interlayer compressive strength, and in particular to a method for quantitative evaluation of interlayer compressive strength in tight oil and shale oil superimposed development areas. Background Technology

[0002] In the field of oil and gas geological exploration and development, reservoir stimulation in tight oil and shale oil superimposed development areas typically relies on large-scale volumetric fracturing technology to improve the permeability and single-well productivity of low-permeability, tight reservoirs. However, in actual development, conventional oil layers or other development layers that have already entered the water injection development stage often exist above or below the target tight oil or shale oil layer. Due to the large scale of fracturing operations and the long fracture propagation distance, fracturing fractures are very likely to break through the barrier between the target layer and the development area, extending upwards or downwards and connecting with adjacent water injection development areas. Once the fractures connect with the water injection development area, two adverse effects will occur: First, the fracturing energy and the range of fracture network stimulation will dissipate to non-target layers, resulting in the inability to effectively stimulate the target tight oil or shale oil reservoir, leading to low single-well production and poor development results; Second, after the fractures connect with water bodies in the development area, injected water enters the target layer along the fractures, easily leading to a large amount of water production during oil testing or production, seriously affecting oil and gas recovery and economic benefits.

[0003] Therefore, the compressive strength of the interlayer between the target layer and the adjacent development area has become a key parameter for evaluating the controllability of fracturing and the stability of the interlayer seal. Current research on the compressive strength of interlayers in composite development areas is mostly at the qualitative analysis stage, lacking a quantitative evaluation method applicable to tight oil or shale oil composite development areas. Therefore, it is necessary to establish a quantitative evaluation method for the compressive strength of the interlayer between the target layer and the development area. By calculating the compressive strength of the interlayer, a reasonable fracturing scheme for tight oil or shale oil can be formulated, achieving synergistic optimization of effective reservoir stimulation and prevention of water channeling. Summary of the Invention

[0004] To address the lack of quantitative methods for evaluating the compressive strength of interlayers in existing technologies, which hinders effective guidance for optimizing fracturing strategies in combined tight oil and shale oil development areas, this invention provides a quantitative evaluation method for the compressive strength of interlayers in combined tight oil and shale oil development areas. This method comprehensively utilizes well logging interpretation data, rock mechanics parameters, and lithological characteristics to establish a Compressive Strength Index (CRI) for interlayers in combined development areas, achieving a quantitative evaluation of the interlayer's compressive strength and providing a basis for optimizing fracturing parameters.

[0005] The technical problem solved by this invention is achieved by the following technical solution: A method for quantitatively evaluating the compressive strength of interlayers in a combined development zone of tight oil and shale oil includes the following steps;

[0006] Step (1) Using the SH mud content curve in the conventional logging data of each well, the lithology of the formation between the target fracturing layer and the adjacent developed layer is identified. Based on the mud content, mudstone, silty mudstone, muddy siltstone and sandstone lithology types are classified, and the thickness of each lithology is counted to establish a layer lithology and thickness parameter system.

[0007] Step (2) Based on the lithology type determined in step (1), read the depth information corresponding to each data sampling point in the well logging data, match the depth information with the lithology identification results, and obtain the depth location and distribution range corresponding to each lithology; extract the P-wave transit time of the well logging data corresponding to each lithology. By obtaining the density DEN parameter, acoustic and density characteristics corresponding to different lithologies are obtained, providing basic data for subsequent calculation of rock mechanical parameters;

[0008] Step (3) In response to the lack of shear wave time difference data in conventional logging data, an empirical regression relationship model between shear wave time difference and longitudinal wave time difference is established using array acoustic logging data of the study area. The shear wave time difference is calculated based on the longitudinal wave time difference to realize the compensation calculation of shear wave parameters.

[0009] Step (4) Based on the longitudinal wave transit time, transverse wave transit time and density parameters, calculate the Young's modulus and Poisson's ratio rock mechanical parameters of the interlayered rocks to characterize the elastic deformation capacity and mechanical characteristics of rocks of different lithologies.

[0010] Step (5) In order to eliminate the influence of the differences in the dimensions and numerical ranges of different evaluation parameters on the evaluation results, Young's modulus and Poisson's ratio are dimensionless, and the brittleness index BI is calculated using the standardized parameters to characterize the brittleness characteristics and crack propagation tendency of different lithologies.

[0011] Step (6) Based on the differences in the sealing capacity and mechanical characteristics of different lithologies, establish a lithology weight coefficient system and assign different weights to mudstone, silty mudstone, silty mudstone and sandstone respectively to reflect the degree of contribution of different lithologies to the compressive strength of the interlayer.

[0012] Step (7) comprehensively considers the lithology, thickness, Young's modulus, brittleness index and lithology weight factors of the interlayer to construct the compressive strength index (CRI) of the interlayer in the superimposed development area, and obtains the comprehensive compressive strength evaluation results of the interlayer between the target layer and the adjacent developed layer through quantitative calculation.

[0013] In step (3) above, an empirical relationship model between shear wave time difference and p-wave time difference is established; regression analysis shows that the shear wave time difference and p-wave time difference satisfy the following relationship: =1.8809 -21.695.

[0014] In step (4) above, based on the P-wave transit time and density data obtained in step (2) and the S-wave transit time data calculated in step (3), Young's modulus E and Poisson's ratio are calculated. The formulas are as follows:

[0015]

[0016] Where: E is Young's modulus, in units of 10. 6 GPa; This represents the density of the rock, expressed in g / cm³. The longitudinal wave time difference is expressed in μs / m. The transverse wave time difference is expressed in μs / m. It is Poisson's ratio, dimensionless.

[0017] In step (5) above, the range standardization method is used to standardize Young's modulus E and Poisson's ratio. After dimensionless processing, the calculation formula is as follows:

[0018]

[0019] Where: Enorm is the standardized Young's modulus; E is the actual calculated Young's modulus; Emax is the maximum value of Young's modulus in the study area; Emin is the minimum value of Young's modulus in the study area, in units of 10. 6 Gpa;

[0020]

[0021] in: norm The standardized Poisson's ratio; This refers to the Poisson's ratio obtained from actual calculations. max This represents the maximum Poisson's ratio in the study area. min The minimum Poisson's ratio for the study area is dimensionless.

[0022] In step (6) above, the standardized Young's modulus obtained in step (5) and standardized Poisson ratio The formula for calculating the interlayer brittleness index BI is as follows:

[0023] .

[0024] The formula for calculating the compressive strength index in step (7) above is:

[0025]

[0026] Where: CRI is the comprehensive compressive strength index, with units of GPa·m; Ti E represents the cumulative thickness of the i-th lithology, in meters (m). i The average Young's modulus of the i-th lithology is expressed in GPa; W. i BI is the weighting coefficient for the i-th lithology; i Σ is the brittleness index of the i-th lithology; Σ is the summation over all lithology types.

[0027] This technical solution first utilizes well logging curves to interpret lithology and thickness, thereby obtaining the rock mechanical parameters of the reservoir and interlayers. Based on this, a quantitative evaluation of the interlayer's compressive strength is conducted, effectively characterizing the pressure-bearing capacity and fracture-blocking ability of the interlayer between the target layer and adjacent development areas. According to the interlayer compressive strength evaluation results, the fracturing operation parameters and fracturing scale for tight oil or shale oil can be further optimized, ensuring that fracturing fracture propagation is controlled within the interlayer's pressure-bearing range, preventing fracturing fractures from penetrating the interlayer and connecting to adjacent water injection development areas, thus effectively preventing water production problems during oil testing and production. Simultaneously, while ensuring effective stimulation of the target reservoir, the optimized design of the fracturing scheme improves reservoir stimulation effects and single-well production, ultimately maximizing the development benefits of tight oil or shale oil.

[0028] The above technical solution mainly solves the following technical problems: 1. It solves the problem that the existing technology's evaluation method for the compressive strength of the interlayer has relatively simple parameters, making it difficult to effectively characterize the interlayer's ability to block the propagation of fracturing fractures across layers. 2. It solves the problem that the existing technology lacks quantitative evaluation indicators and relies on experience-based judgment, leading to highly subjective evaluation results. 3. It solves the problem that the existing technology lacks a basis for optimizing fracturing construction parameters and fracturing scale based on the compressive strength of the interlayer, which can easily lead to fracturing fractures communicating with adjacent development areas.

[0029] Compared with the prior art, this application has the following advantages:

[0030] 1. This application provides more comprehensive parameter acquisition and a more reliable evaluation basis: Existing technologies mostly rely on a single indicator for qualitative judgment, which is difficult to fully reflect the true compressive strength of the interlayer. This technical solution obtains multiple parameters through a professional software system, providing a more comprehensive and reliable data basis for the evaluation of the compressive strength of the interlayer, and avoiding evaluation bias caused by parameter omissions.

[0031] 2. This application constructs a comprehensive evaluation index to achieve quantitative characterization of compressive strength: Existing technologies mainly rely on human experience for qualitative or semi-quantitative judgments, which are highly subjective and inconsistent. This technical solution constructs a compressive strength evaluation index (CRI) for the interlayer, which integrates multiple parameters into a single quantitative indicator through mathematical relationships, thereby quantifying the compressive strength of the interlayer and improving the objectivity and repeatability of the evaluation results.

[0032] 3. This application ensures interlayer isolation during stratified water injection, supporting refined reservoir utilization: In stratified water injection development, existing technologies often lead to interlayer crossflow due to the inability to accurately evaluate the pressure-bearing capacity of the interlayers. This technical solution provides a scientific basis for the design of stratified water injection schemes by quantitatively evaluating the pressure resistance performance of the interlayers, ensuring independent isolation of each layer during water injection and avoiding interlayer interference. Attached Figure Description

[0033] Figure 1 This is a cross-sectional diagram of transverse and longitudinal waves in an embodiment of this application. Detailed Implementation

[0034] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Example 1: A method for quantitatively evaluating the compressive strength of interlayers in a combined tight oil and shale oil development zone, comprising the following steps:

[0036] Step (1): Identify the lithology and thickness between the fractured and developed sections using the SH (shale content) logging curves of each well.

[0037] Obtain the SH (shale content) curve data and its thickness from the conventional well logging interpretation results of the target well in the study area. The SH is the shale content parameter obtained from well logging interpretation, which can be directly read from the conventional well logging interpretation results, and its value ranges from 0% to 100%. Taking the formation between the fracturing target layer and the adjacent developed layer as the research object, read the SH values ​​at corresponding depths point by point, and identify the lithology at each depth point according to the pre-established lithological classification standard and record its corresponding thickness. The lithological classification standard according to the national standard GB / T17412.2-1998 "Rock Classification and Nomenclature Scheme Part 2: Sedimentary Rock Classification and Nomenclature Scheme" is as follows:

[0038] (1) When SH≥75%, the lithology at this depth point is determined to be mudstone; (2) When 50%≤SH<75%, the lithology at this depth point is determined to be silty mudstone; (3) When 25%≤SH<50%, the lithology at this depth point is determined to be silty mudstone; (4) When SH<25%, the lithology at this depth point is determined to be sandstone.

[0039] Based on this, the lithology of the interlayer between the target fracturing layer and the adjacent developed layer was determined, and the thickness was directly read from the conventional logging interpretation results. The results are shown in Table 1.

[0040] Step (2): Obtain the P-wave time difference (DEN) parameters: Based on the depth of the lithology and comparing it with existing data, the corresponding P-wave transit time and density are read out for each lithology:

[0041] Based on the lithology types determined in the preceding steps, depth information corresponding to each data sampling point is read from the well logging data. This depth information is then matched with the lithology identification results to obtain the depth location and distribution range corresponding to each lithology. The P-wave transit time in the well logging interpretation results for this depth range is then extracted. (AC) and density (DEN) data. The P-wave transit time and density data are derived from conventional well logging interpretation results, and the logging parameter values ​​at the corresponding depth points can be directly read. Based on the top and bottom boundary depths of the formation, the P-wave transit time and density data at each sampling point within the well section were statistically analyzed, and the results are shown in Table 1.

[0042] Table 1 Calculation Table of Well Area Layer Data

[0043]

[0044] Step (3): Establish a conversion model between transverse wave time difference and longitudinal wave time difference.

[0045] Because conventional well logging data typically only includes P-wave time difference. The data is needed, and the P-wave time difference needs to be obtained simultaneously during subsequent parameter calculations. and transverse wave time difference Therefore, it is necessary to establish the conversion relationship between shear wave time difference and p-wave time difference. To establish this conversion relationship, typical wells with complete array sonic logging data within the study area were selected as sample wells. The data used were derived from array sonic logging interpretation results, including p-wave time difference... With transverse wave time difference Both are processed logging parameters corresponding to the same logging depth point.

[0046] During data processing, well depth was used as the unique matching identifier to pair P-wave and S-wave time differences point by point, forming the original dataset. To ensure data quality, outlier data points affected by instrument noise, abnormal curve abrupt changes, and obvious dispersion were removed, ultimately obtaining a valid sample dataset.

[0047] Based on valid sample data, the P-wave time difference at the same depth point With transverse wave time difference To rendezvous, see attached. Figure 1 The least squares linear regression method was used to analyze the P-wave time difference. With transverse wave time difference A fitting analysis was conducted to examine the relationship between the two. A regression model was established with P-wave time difference as the independent variable and S-wave time difference as the dependent variable to obtain the empirical transformation relationship between them. The fitting results were evaluated using the coefficient of determination R², which characterizes the goodness of fit of the model. The final empirical relationship model between S-wave time difference and P-wave time difference is as follows:

[0048] =1.8809 -21.695

[0049] Using the aforementioned empirical formulas, the corresponding shear wave time difference can be calculated from the P-wave time difference data in conventional logging data, thereby obtaining the basic parameters required for subsequent parameter calculations. This model is used to predict shear wave time difference parameters using P-wave time difference when shear wave logging data is unavailable.

[0050] Table 2. Array acoustic logging data

[0051]

[0052] Step (4): Calculate Young's modulus E and Poisson's ratio .

[0053] Based on the P-wave transit time and density data obtained in step (2) and the S-wave transit time data calculated in step (3), calculate Young's modulus E and Poisson's ratio. The calculation formula is as follows, and the results are shown in Table 3.

[0054]

[0055] Where: E is Young's modulus, in units of 10. 6 GPa; This represents the density of the rock, expressed in g / cm³. The longitudinal wave time difference is expressed in μs / m. The transverse wave time difference is expressed in μs / m. It is Poisson's ratio, dimensionless.

[0056] Step (5): Young's modulus E and Poisson's ratio Standardize:

[0057] Because Young's modulus and Poisson's ratio differ in dimensions and numerical range, to eliminate the influence of dimensional inconsistencies between different evaluation parameters on the compressive strength evaluation results of the composite zone, Young's modulus and Poisson's ratio need to be standardized before constructing the composite zone compressive strength index (CRI). The range standardization method is used to standardize Young's modulus E and Poisson's ratio. The dimensionless processing was performed, and the results are shown in Table 3. The calculation formula is as follows:

[0058]

[0059] in: E represents the standardized Young's modulus; E is the actual calculated Young's modulus; Emax is the maximum Young's modulus in the study area; Emin is the minimum Young's modulus in the study area, in units of 10. 6 GPa.

[0060]

[0061] in: norm The standardized Poisson's ratio; This refers to the Poisson's ratio obtained from actual calculations. max This represents the maximum Poisson's ratio in the study area. min The minimum Poisson's ratio for the study area is dimensionless.

[0062] Step (6): Calculate the brittleness index BI.

[0063] Based on the standardized Young's modulus obtained in step (5) and standardized Poisson ratio The brittleness index BI of the interlayer is calculated using the following formula, and the results are shown in Table 3.

[0064]

[0065] Step (7): Determine the weighting coefficients Wi for different lithologies.

[0066] Based on the lithology types identified in step (1), corresponding weight coefficients Wi are assigned to different lithologies to reflect the differences in their compressive strength. The lithologies include mudstone, silty mudstone, argillaceous siltstone, and sandstone. A lithology weight coefficient system is established based on the differences in the mechanical properties and containment capabilities of each lithology. Lithologies with stronger containment capabilities are assigned larger weight coefficients, while those with weaker containment capabilities are assigned smaller weight coefficients. The weight coefficients for mudstone, silty mudstone, argillaceous siltstone, and sandstone are 1, 0.85, 0.6, and 0.4, respectively.

[0067] Step (8): Calculate the compressive strength index (CRI) of the composite partition layer.

[0068] Based on the lithology and thickness parameters obtained in step (1), the brittleness index BI calculated in step (6), and the lithology weighting coefficient Wi determined in step (7), the compressive strength index CRI of the interlayer in the composite development area is constructed. The thickness T corresponding to each lithology is then... i Brittleness Index (BI) i and weighting coefficient W i Substitute into the formula for calculating the compressive strength index of the composite partition layer:

[0069]

[0070] Wherein: T i The cumulative thickness of the i-th lithology is obtained by superimposing the thicknesses of the same lithological segment in the single-well logging interpretation results. It is accumulated for continuous lithological segments based on the logging depth, and its unit is m.

[0071] E i Let be the average Young's modulus of the i-th lithology, obtained from the elastic parameter inversion results, and arithmetically averaged for the same lithology type. Its unit is 10. 6 GPa.

[0072] Wi is the weighting coefficient of the i-th lithology, which is determined by a normalization method to ensure that the weighting coefficients of each lithology satisfy ΣWi = 1. It is used to characterize the relative contribution of different lithologies to the compressive strength of the interlayer.

[0073] BI i The brittleness index for the i-th lithology is calculated from well logging elastic parameters such as P-wave velocity and density, and is standardized to a value range of 0 to 1. It is used to characterize the rock's tendency to fracture.

[0074] The calculation results are shown in Table 3, which summarizes the calculation results of each lithological parameter and CRI.

[0075] Taking the silty mudstone of well H223 as an example, its cumulative thickness T i =2141.63−2141.13=0.50m, Ei=0.47, Wi=0.85,

[0076] Substituting BIi=0.48 into the CRI formula, we get CRI=0.104.

[0077] Table 3. Calculation Table of Compressive Strength Data for Partition Layers

[0078]

[0079] In existing technologies, the evaluation of the sealing capacity and compressive strength of interlayers mainly relies on a single parameter, such as mudstone thickness, Young's modulus, Poisson's ratio, or brittleness index. Since the compressive strength of an interlayer is influenced by multiple factors, including lithological composition, thickness characteristics, and rock mechanical properties, a single parameter cannot fully reflect the true compressive strength of the interlayer and its ability to prevent the propagation of hydraulic fractures. Therefore, the evaluation results are highly subjective and limited.

[0080] This application comprehensively considers parameters such as interlayer lithology, thickness, Young's modulus, Poisson's ratio, and brittleness index, and achieves a quantitative evaluation of the interlayer compressive strength by constructing the Compressive Strength Index (CRI) for the composite development area. When only the interlayer thickness is used for evaluation, the interlayer thicknesses of the two wells are 12.3m and 11.8m, respectively, and the evaluation results show that their sealing capabilities are similar. However, further calculations revealed significant differences in the lithological composition and rock mechanical properties of the interlayers of the two wells. Actual fracturing operation results showed that the well with the higher CRI value did not experience fracture penetration, while the well with the lower CRI value showed obvious interlayer communication and water production.

[0081] The results show that it is difficult to identify the quality difference of the interlayer when using only the thickness parameter for evaluation, while the CRI constructed in this application can effectively reflect the comprehensive compressive strength of the interlayer.

[0082] This application has broad application prospects, mainly reflected in the following aspects:

[0083] 1. Efficient development of tight oil composite development zones:

[0084] my country possesses abundant tight oil reserves, with a wide distribution of overlapping development zones. Interlayer compressibility is a key limiting factor determining the effectiveness of water injection development. This technology can accurately evaluate the compressibility of interlayers under water injection pressurization conditions, providing a quantitative basis for optimizing water injection parameters, effectively preventing oil and gas migration and resource loss due to interlayer fracturing, and significantly improving tight oil recovery. As tight oil becomes an important area for increasing crude oil production in my country, the demand for this technology will continue to grow.

[0085] 2. Technology promotion under similar geological conditions:

[0086] This technical method is universally applicable, not only to tight oilfield development zones but also to the evaluation and development of unconventional oil and gas reservoirs such as shale oil and gas and tight sandstone gas. In shale oil and gas development, the stability evaluation of interlayer barriers is equally crucial; in deep coalbed methane development, the compressive strength evaluation of the roof and floor aquitards directly affects development safety. This technology can provide mature technical support for these fields.

[0087] 3. Engineering safety assurance for oil and gas field development:

[0088] Interlayer fracturing not only causes oil and gas loss but may also trigger engineering risks such as formation water channeling and inter-well interference. This technology, by quantitatively evaluating the compressive strength of interlayers, can identify high-risk formations in advance, guide well placement plans and injection-production parameter design, reduce potential safety hazards during development, and improve the overall safety of oil and gas field development.

[0089] 4. Economic and social benefits:

[0090] Promoting the application of this technology can reduce the ineffective loss of oil and gas resources, increase single-well production and ultimate recovery rate, and bring significant economic benefits. At the same time, by optimizing water injection development schemes, ineffective water injection can be reduced, saving water resources and energy consumption, which aligns with the development direction of green and low-carbon development.

Claims

1. A method for quantitatively evaluating the compressive strength of interlayers in a combined development zone of tight oil and shale oil, characterized in that, Includes the following steps; Step (1) Using the SH mud content curve in the conventional logging data of each well, the lithology of the formation between the target fracturing layer and the adjacent developed layer is identified. Based on the mud content, mudstone, silty mudstone, muddy siltstone and sandstone lithology types are classified, and the thickness of each lithology is counted to establish a layer lithology and thickness parameter system. Step (2) Based on the lithology type determined in step (1), read the depth information corresponding to each data sampling point in the well logging data, match the depth information with the lithology identification results, and obtain the depth location and distribution range corresponding to each lithology; extract the P-wave transit time of the well logging data corresponding to each lithology. By obtaining the density DEN parameter, acoustic and density characteristics corresponding to different lithologies are obtained, providing basic data for subsequent calculation of rock mechanical parameters; Step (3) In response to the lack of shear wave time difference data in conventional logging data, an empirical regression relationship model between shear wave time difference and longitudinal wave time difference is established using array acoustic logging data of the study area. The shear wave time difference is calculated based on the longitudinal wave time difference to realize the compensation calculation of shear wave parameters. Step (4) Based on the longitudinal wave transit time, transverse wave transit time and density parameters, calculate the Young's modulus and Poisson's ratio rock mechanical parameters of the interlayered rocks to characterize the elastic deformation capacity and mechanical characteristics of rocks of different lithologies. Step (5) In order to eliminate the influence of the differences in the dimensions and numerical ranges of different evaluation parameters on the evaluation results, Young's modulus and Poisson's ratio are dimensionless, and the brittleness index BI is calculated using the standardized parameters to characterize the brittleness characteristics and crack propagation tendency of different lithologies. Step (6) Based on the differences in the sealing capacity and mechanical characteristics of different lithologies, establish a lithology weight coefficient system and assign different weights to mudstone, silty mudstone, silty mudstone and sandstone respectively to reflect the degree of contribution of different lithologies to the compressive strength of the interlayer. Step (7) comprehensively considers the lithology, thickness, Young's modulus, brittleness index and lithology weight factors of the interlayer to construct the compressive strength index (CRI) of the interlayer in the superimposed development area, and obtains the comprehensive compressive strength evaluation results of the interlayer between the target layer and the adjacent developed layer through quantitative calculation.

2. The method for quantitatively evaluating the compressive strength of interlayers in tight oil and shale oil composite development zones according to claim 1, characterized in that: In step (3), an empirical relationship model between the transverse wave time difference and the longitudinal wave time difference is established; regression analysis shows that the transverse wave time difference and the longitudinal wave time difference satisfy the following relationship: =1.8809 -21.

695.

3. The method for quantitatively evaluating the compressive strength of interlayers in tight oil and shale oil composite development zones according to claim 1, characterized in that: In step (4), based on the P-wave transit time and density data obtained in step (2) and the S-wave transit time data calculated in step (3), Young's modulus E and Poisson's ratio are calculated. The formulas are as follows: Where: E is Young's modulus, in units of 10. 6 GPa; This represents the density of the rock, expressed in g / cm³. The longitudinal wave time difference is expressed in μs / m. The transverse wave time difference is expressed in μs / m. It is Poisson's ratio, dimensionless.

4. The method for quantitatively evaluating the compressive strength of interlayers in tight oil and shale oil composite development zones according to claim 1, characterized in that: In step (5), the range standardization method is used to evaluate Young's modulus E and Poisson's ratio. After dimensionless processing, the calculation formula is as follows: Where: Enorm is the standardized Young's modulus; E is the actual calculated Young's modulus; Emax is the maximum value of Young's modulus in the study area; Emin is the minimum value of Young's modulus in the study area, in units of 10. 6 Gpa; in: norm The standardized Poisson's ratio; This refers to the Poisson's ratio obtained from actual calculations. max This represents the maximum Poisson's ratio in the study area. min The minimum Poisson's ratio for the study area is dimensionless.

5. The method for quantitatively evaluating the compressive strength of interlayers in tight oil and shale oil composite development zones according to claim 1, characterized in that: In step (6), the standardized Young's modulus obtained in step (5) is used. and standardized Poisson ratio The formula for calculating the interlayer brittleness index BI is as follows: 。 6. The method for quantitatively evaluating the compressive strength of interlayers in tight oil and shale oil composite development zones according to claim 1, characterized in that: The formula for calculating the compressive strength index in step (7) is: Where: CRI is the comprehensive compressive strength index, with units of GPa·m; T i E represents the cumulative thickness of the i-th lithology, in meters (m). i The average Young's modulus of the i-th lithology is expressed in GPa; W. i BI is the weighting coefficient for the i-th lithology; i Σ is the brittleness index of the i-th lithology; Σ is the summation over all lithology types.

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