Rock elastic parameter calculation method and device based on full stress-strain curve

Abstract

The application provides a rock elastic parameter calculation method and device based on a full stress-strain curve, equipment and a storage medium, comprising: filtering original full stress-strain curve data, determining a data calculation interval, and obtaining pretreated data; determining a constraint limit of a rock physical significance parameter, and obtaining Poisson's ratio processing data; adopting a locally optimal adaptive seed search method to perform linear search segment optimization on the pretreated data, and obtaining search method processing data; determining the data range of the linear segment of the full stress-strain curve according to the obtained Poisson's ratio processing data and the search method processing data; and calculating the rock elastic parameter. Through the pretreatment filtering and other operations on the curve, noise interference is reduced. At the same time, the determination of the linear segment through the constructed Poisson's ratio constraint method and the locally optimal adaptive seed search method greatly reduces the human selection error and improves the calculation accuracy of the rock elastic parameter.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration, and in particular to a method, apparatus, equipment and storage medium for calculating rock elastic parameters based on full stress-strain curves. Background Technology

[0002] This invention relates to the field of rock physics experimental data processing. It is a method for calculating rock elastic parameters based on the full stress-strain curves from uniaxial and triaxial compression deformation tests in rock mechanics. After preprocessing such as filtering, the linear elastic segment of the stress-strain curve is determined using a Poisson's ratio constraint method and a locally optimal adaptive seed search method. In other words, it is a method for calculating rock elastic parameters based on full stress-strain curves. Using this invention, rock elastic parameters in rock mechanics experiments can be calculated with relatively high accuracy.

[0003] The deformation, strength, and failure characteristics of rocks under force are called rock mechanical properties. Understanding the basic mechanical properties of rocks and obtaining their mechanical parameters generally requires rock mechanics tests. Rock mechanics tests primarily simulate the original stress state of rocks by applying loads to them using specialized loading devices, while simultaneously measuring the deformation produced under these loads. The measured load values ​​and corresponding deformation values ​​are then used to plot the load-deformation relationship curve. Based on the trends in the stress-strain curves, the mechanical properties of the rocks can be analyzed and studied, and deformation and strength parameters reflecting the rock's mechanical characteristics, such as elastic modulus, Poisson's ratio, and stress threshold value, can be calculated.

[0004] In the process of realizing this invention, the inventors discovered at least the following problems in the prior art:

[0005] Currently, the calculation of rock elastic parameters based on the full stress-strain curve typically determines Young's modulus and Poisson's ratio using data obtained at 40%-60% of the peak strength. However, this method cannot accurately represent the linear elastic range for curves of different rocks. Furthermore, in rock mechanics experiments, sensor noise can interfere with the full stress-strain curve data, leading to errors in the calculated results. Besides using the peak strength method, there is also a method of manually selecting the linear elastic segment of stress-strain. This manual selection is time-consuming and labor-intensive, and it also fails to effectively address the error interference caused by sensor noise. Therefore, it is necessary to develop a method for calculating rock elastic parameters that can solve the problem of determining the linear elastic range of the full stress-strain curve and reduce sensor interference errors. Summary of the Invention

[0006] To address the aforementioned issues, this application provides a method, apparatus, device, and storage medium for calculating rock elastic parameters based on the full stress-strain curve.

[0007] This application provides a method for calculating the elastic parameters of rock based on the full stress-strain curve, including:

[0008] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0009] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0010] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0011] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0012] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

[0013] In some embodiments, the filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters, and using a low-pass filter to filter out the high-frequency information of the analysis parameters while retaining the effective low-frequency information to obtain low-frequency data.

[0014] In some embodiments, determining the data calculation interval includes: detecting the maximum position of the axial and transverse extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval.

[0015] In some embodiments, the specific method of employing the locally optimal adaptive seed search method is as follows:

[0016] A search seed is set, assuming that the initial value, i.e., the position of half the stress peak, is within the linear segment of the full stress-strain curve of the preprocessed data. Starting from the position of half the stress peak, the search proceeds in two directions. If the slope difference between the two ends is less than the constraint value, it is considered to still be within the linear segment. This continues until the slope change rate on one side exceeds the constraint value, at which point it is considered to have reached the end of the linear segment. Then, the search proceeds only to the other side. The two ends at this point are considered to be the two ends of the linear segment. This method is used to determine the range of the linear segment of the full stress-strain curve of the preprocessed data, thus obtaining the data processed by the search method.

[0017] In some embodiments, determining the constraint limits of the rock physical significance parameters includes: calculating the circumferential axial change rate of the preprocessed data, which is the instantaneous Poisson's ratio; positions where the instantaneous Poisson's ratio is less than 0 are taken as the lower boundary of the constraint limits of the rock physical significance parameters, and positions where the instantaneous Poisson's ratio is greater than 0.5 are taken as the upper boundary of the constraint limits of the rock physical significance parameters.

[0018] In some embodiments, determining the data range of the linear segment of the full stress-strain curve based on the obtained Poisson's ratio processed data and the search method processed data specifically includes: comparing the upper and lower boundaries of the Poisson's ratio processed data and the search method processed data, and taking the value in the middle of the two, close to the direction of the initial search seed, as the two endpoints of the data range of the linear segment of the full stress-strain curve.

[0019] In some embodiments, the slope of the linear segment of the full stress-strain curve is the rock elastic modulus. A specific method for calculating the rock elastic modulus includes: determining the stress value at the starting point of the linear segment. and longitudinal strain and the final stress value and longitudinal strain The elastic modulus of the rock is calculated according to formula (1), and the elastic Poisson's ratio of the rock is calculated according to formula (2):

[0020] (1)

[0021] (2)

[0022] In the formula:

[0023] -----Rock elastic modulus, MPa;

[0024] -----Poisson's ratio of rock elasticity;

[0025] -----Stress value at the starting point of the straight line segment on the stress-axial strain curve;

[0026] -----The stress value at the end of the straight line segment on the stress-axial strain curve;

[0027] -----Stress is The longitudinal strain value at that time;

[0028] -----Stress is The longitudinal strain value at that time;

[0029] -----Stress is The circumferential strain value at that time;

[0030] -----Stress is The circumferential strain value at that time.

[0031] This application provides a device for calculating the elastic parameters of rock based on the full stress-strain curve, including:

[0032] Data preprocessing module: Filters the original full stress-strain curve data, determines the data calculation range based on the filtering results, and obtains the preprocessed data;

[0033] Poisson's ratio data processing module: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the Poisson's ratio processed data;

[0034] The search method data processing module: Based on the preprocessed data, the adaptive seed search method with local optimum is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0035] The data processing module for the linear segment of the full stress-strain curve: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is jointly determined;

[0036] Rock elastic parameter calculation module: Calculates rock elastic parameters based on the data range of the linear segment of the full stress-strain curve.

[0037] This application provides a rock elastic parameter calculation device based on the full stress-strain curve, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, performs any of the above-described rock elastic parameter calculation methods based on the full stress-strain curve.

[0038] This application provides a storage medium storing a computer program that can be executed by one or more processors and can be used to implement the rock elastic parameter calculation method based on the full stress-strain curve described above.

[0039] This application provides a method, apparatus, equipment, and storage medium for calculating rock elastic parameters based on the full stress-strain curve, which has the following beneficial effects:

[0040] This invention provides a method, apparatus, device, and storage medium for calculating rock elastic parameters based on the full stress-strain curve. The method, based on the full stress-strain curve in uniaxial and triaxial compression deformation tests in rock mechanics, aims to solve the problem of determining the linear elastic range of the full stress-strain curve and reduce interference errors caused by sensor noise. It is designed to efficiently obtain accurate rock elastic parameters. The method is simple, provides accurate data, and is cost-effective. Attached Figure Description

[0041] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings.

[0042] Figure 1 A flowchart illustrating a method for calculating rock elastic parameters based on a full stress-strain curve, provided for embodiments of this application;

[0043] Figures 2(a)-(c) are schematic diagrams illustrating the definitions of various elastic moduli provided in the embodiments of this application;

[0044] Figure 3 A rock mechanics test sample of shale provided in an embodiment of this application;

[0045] Figure 4 A full stress-strain curve of a triaxial compression test of shale provided for an embodiment of this application;

[0046] Figures 5(a)-(b) are spectral analysis diagrams of stress and strain data of shale provided in the embodiments of this application;

[0047] Figures 6(a)-(d) are schematic diagrams showing the determination of linear segments by the Poisson's ratio constraint method and the seed search method for shale provided in the embodiments of this application;

[0048] Figures 7(a)-(b) show the algorithm processing and analysis results of a triaxial compression test of shale provided in the embodiments of this application;

[0049] Figure 8 This is a schematic diagram of the apparatus provided in an embodiment of this application.

[0050] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0052] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0053] If the application documents contain similar descriptions such as "first, second, third", the following explanation shall be added: In the following description, the terms "first, second, third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0055] Before introducing the rock elastic parameter calculation method based on the full stress-strain curve provided in the embodiments of this application, the problems existing in the related technology are briefly introduced:

[0056] This invention provides a method for calculating the elastic parameters of rocks based on the full stress-strain curve, and more particularly a method for calculating the elastic parameters of rocks based on the full stress-strain curve in uniaxial and triaxial compression deformation tests of rock mechanics. This method mainly involves preprocessing the full stress-strain curve data, using the Poisson's ratio constraint method and the locally optimal adaptive seed search method to determine the range of the rock elastic segment data of the rock stress-strain curve, and finally combining the elastic parameter calculation formula to calculate the elastic parameters of the rock.

[0057] Calculation principle:

[0058] The main parameters characterizing rock deformation are the elastic modulus and Poisson's ratio. The elastic modulus of a rock is defined as the ratio of axial stress to longitudinal strain, while Poisson's ratio is defined as the ratio of transverse strain to longitudinal strain at a given stress level. For heterogeneous rocks with well-developed fractures and complex structures, the deformation generated during the increase of axial load includes not only elastic deformation but also irreversible plastic deformation. These deformations are manifested at different stages of the total stress-strain curve.

[0059] Based on the stress-strain curve of the rock before failure, the elastic modulus of the rock at different deformation stages can be determined, namely the initial elastic modulus, the tangential elastic modulus, and the secant elastic modulus.

[0060] The initial elastic modulus is the slope of the tangent line to the stress-strain curve at zero load, as shown in Figure 2(a).

[0061] The tangential modulus of elasticity is the slope of the straight segment of the stress-strain curve, as shown in Figure 2(b).

[0062] The secant modulus of elasticity is the slope of the line connecting the zero-load point of the stress-strain curve and the intersection point of a certain stress level (generally 50% of the uniaxial compressive strength), as shown in Figure 2(c).

[0063] In engineering, the tangential modulus of elasticity of rock is generally used to characterize its deformation characteristics; this is called the rock's elastic modulus. The secant modulus of elasticity at 50% uniaxial compressive strength is called the rock's deformation modulus. Poisson's ratio is the ratio of transverse strain to axial strain. The Poisson's ratios corresponding to the aforementioned elastic modulus and deformation modulus are called the rock's elastic Poisson's ratio and the corresponding Poisson's ratio, respectively.

[0064] The present invention is based on the characteristics of rock mechanics test data. These characteristics are preprocessed and analyzed to obtain suitable curve data for calculation. The upper and lower boundaries are solved using the Poisson's ratio constraint method, and a seed search method similar to a greedy algorithm is used to obtain the linear elastic segment. Finally, the corresponding rock elastic parameters are calculated using the formula for rock elastic parameters. Addressing the problems existing in related technologies, this application provides a method for calculating rock elastic parameters based on a full stress-strain curve. This method is applied to a rock elastic parameter calculation device based on a full stress-strain curve, which can be an electronic device, such as a computer or mobile terminal. The functions implemented by the rock elastic parameter calculation method based on a full stress-strain curve provided in this application can be achieved by the processor of an electronic device calling program code, which can be stored in a computer storage medium.

[0065] Example One

[0066] This application provides a method for calculating the elastic parameters of rock based on the full stress-strain curve. Figure 1 A flowchart illustrating a method for calculating rock elastic parameters based on a full stress-strain curve, as provided in this application embodiment, is shown below. Figure 1 As shown, it includes:

[0067] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0068] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0069] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0070] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0071] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

[0072] This application provides a method for calculating rock elastic parameters based on the full stress-strain curve, which can solve the problem of determining the linear elastic range of the full stress-strain curve and reduce the interference error caused by the noise of the sensor itself, aiming to efficiently obtain accurate rock elastic parameters.

[0073] Example Two

[0074] Based on the foregoing embodiments, this application further provides a method for calculating rock elastic parameters based on the full stress-strain curve, including:

[0075] The specific implementation steps are as follows:

[0076] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0077] Specific methods include:

[0078] S101: The filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters; filtering out high-frequency information of the analysis parameters through a low-pass filter, retaining effective low-frequency information to obtain low-frequency data, and removing data caused by the Gibbs effect due to low-pass filtering; in order to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0079] S102: Determining the data calculation interval includes: detecting the maximum position of the axial and lateral extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval. The axial and lateral extensometer values ​​should increase monotonically. If they decrease, it means that there is a problem with the subsequent data and it should be deleted. This is to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0080] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0081] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0082] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0083] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

[0084] In an embodiment of the rock elastic parameter calculation method based on the full stress-strain curve provided in this application, the problem of determining the linear elastic range of the full stress-strain curve and reducing the interference error caused by the noise of the sensor itself are solved, aiming to efficiently obtain accurate rock elastic parameters.

[0085] Example Three

[0086] Based on the foregoing embodiments, this application further provides a method for calculating rock elastic parameters based on the full stress-strain curve, including:

[0087] The specific implementation steps are as follows:

[0088] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0089] Specific methods include:

[0090] S101: The filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters; filtering out high-frequency information of the analysis parameters through a low-pass filter, retaining effective low-frequency information to obtain low-frequency data, and removing data caused by the Gibbs effect due to low-pass filtering; in order to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0091] S102: Determining the data calculation interval includes: detecting the maximum position of the axial and lateral extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval. The axial and lateral extensometer values ​​should increase monotonically. If they decrease, it means that there is a problem with the subsequent data and it should be deleted. This is to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0092] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0093] The determination of the constraint limits for rock physical parameters includes: calculating the circumferential axial variation rate of the preprocessed data, which is the instantaneous Poisson's ratio; the position where the instantaneous Poisson's ratio is less than 0 is taken as the lower boundary of the constraint limits for rock physical parameters, and the position where the instantaneous Poisson's ratio is greater than 0.5 is taken as the upper boundary of the constraint limits for rock physical parameters.

[0094] The Poisson's ratio should be controlled within the range of 0-0.5. A ratio less than 0 indicates that the sample is in a state of lattice compression, while a ratio greater than 0.5 indicates that cracks have appeared inside the sample. Using the position where the instantaneous Poisson's ratio is less than 0 as the lower boundary of the physical parameter constraint and the position where it is greater than 0.5 as the upper boundary is more reasonable. This approach can efficiently obtain accurate rock elastic parameters and reduce interference errors caused by sensor noise.

[0095] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0096] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0097] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

[0098] In an embodiment of the rock elastic parameter calculation method based on the full stress-strain curve provided in this application, the problem of determining the linear elastic range of the full stress-strain curve and reducing the interference error caused by the noise of the sensor itself are solved, aiming to efficiently obtain accurate rock elastic parameters.

[0099] Example Four

[0100] Based on the foregoing embodiments, this application further provides a method for calculating rock elastic parameters based on the full stress-strain curve, including:

[0101] The specific implementation steps are as follows:

[0102] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0103] Specific methods include:

[0104] S101: The filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters; filtering out high-frequency information of the analysis parameters through a low-pass filter, retaining effective low-frequency information to obtain low-frequency data, and removing data caused by the Gibbs effect due to low-pass filtering; in order to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0105] S102: Determining the data calculation interval includes: detecting the maximum position of the axial and lateral extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval. The axial and lateral extensometer values ​​should increase monotonically. If they decrease, it means that there is a problem with the subsequent data and it should be deleted. This is to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0106] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0107] The determination of the constraint limits for rock physical parameters includes: calculating the circumferential axial variation rate of the preprocessed data, which is the instantaneous Poisson's ratio; the position where the instantaneous Poisson's ratio is less than 0 is taken as the lower boundary of the constraint limits for rock physical parameters, and the position where the instantaneous Poisson's ratio is greater than 0.5 is taken as the upper boundary of the constraint limits for rock physical parameters.

[0108] The Poisson's ratio should be controlled within the range of 0-0.5. A ratio less than 0 indicates that the sample is in a state of lattice compression, while a ratio greater than 0.5 indicates that cracks have appeared inside the sample. Using the position where the instantaneous Poisson's ratio is less than 0 as the lower boundary of the physical parameter constraint and the position where it is greater than 0.5 as the upper boundary is more reasonable. This approach can efficiently obtain accurate rock elastic parameters and reduce interference errors caused by sensor noise.

[0109] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0110] The specific method is as follows:

[0111] A search seed is set, assuming that the initial value, i.e., the position of half the stress peak, is within the linear segment of the full stress-strain curve of the preprocessed data. Starting from the position of half the stress peak, the search proceeds in two directions. If the slope difference between the two ends is less than the constraint value, it is considered to still be within the linear segment. This continues until the slope change rate on one side exceeds the constraint value, at which point it is considered to have reached the end of the linear segment. Then, the search proceeds only to the other side. The two ends at this point are considered to be the two ends of the linear segment. This method is used to determine the range of the linear segment of the full stress-strain curve of the preprocessed data, thus obtaining the data processed by the search method.

[0112] The specific method for calculating the constraint value is as follows: Within a search step range approximately half the peak value, the average of the five values ​​at the lower end of the search is taken as the initial lower search value, and the average of the five values ​​at the upper end of the search is taken as the initial upper search value. The slope between the upper and lower values ​​is calculated, which is the initial slope. A 5% error in the initial slope is taken as the constraint value to limit the search process.

[0113] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0114] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

[0115] In an embodiment of the rock elastic parameter calculation method based on the full stress-strain curve provided in this application, the problem of determining the linear elastic range of the full stress-strain curve and reducing the interference error caused by the noise of the sensor itself are solved, aiming to efficiently obtain accurate rock elastic parameters.

[0116] Example Five

[0117] Based on the foregoing embodiments, this application further provides a method for calculating rock elastic parameters based on the full stress-strain curve, including:

[0118] The specific implementation steps are as follows:

[0119] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0120] Specific methods include:

[0121] S101: The filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters; filtering out high-frequency information of the analysis parameters through a low-pass filter, retaining effective low-frequency information to obtain low-frequency data, and removing data caused by the Gibbs effect due to low-pass filtering; in order to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0122] S102: Determining the data calculation interval includes: detecting the maximum position of the axial and lateral extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval. The axial and lateral extensometer values ​​should increase monotonically. If they decrease, it means that there is a problem with the subsequent data and it should be deleted. This is to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0123] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0124] The determination of the constraint limits for rock physical parameters includes: calculating the circumferential axial variation rate of the preprocessed data, which is the instantaneous Poisson's ratio; the position where the instantaneous Poisson's ratio is less than 0 is taken as the lower boundary of the constraint limits for rock physical parameters, and the position where the instantaneous Poisson's ratio is greater than 0.5 is taken as the upper boundary of the constraint limits for rock physical parameters.

[0125] The Poisson's ratio should be controlled within the range of 0-0.5. A ratio less than 0 indicates that the sample is in a state of lattice compression, while a ratio greater than 0.5 indicates that cracks have appeared inside the sample. Using the position where the instantaneous Poisson's ratio is less than 0 as the lower boundary of the physical parameter constraint and the position where it is greater than 0.5 as the upper boundary is more reasonable. This approach can efficiently obtain accurate rock elastic parameters and reduce interference errors caused by sensor noise.

[0126] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0127] The specific method is as follows:

[0128] A search seed is set, assuming that the initial value, i.e., the position of half the stress peak, is within the linear segment of the full stress-strain curve of the preprocessed data. Starting from the position of half the stress peak, the search proceeds in two directions. If the slope difference between the two ends is less than the constraint value, it is considered to still be within the linear segment. This continues until the slope change rate on one side exceeds the constraint value, at which point it is considered to have reached the end of the linear segment. Then, the search proceeds only to the other side. The two ends at this point are considered to be the two ends of the linear segment. This method is used to determine the range of the linear segment of the full stress-strain curve of the preprocessed data, thus obtaining the data processed by the search method.

[0129] The specific method for calculating the constraint value is as follows: Within a search step range approximately half the peak value, the average of the five values ​​at the lower end of the search is taken as the initial lower search value, and the average of the five values ​​at the upper end of the search is taken as the initial upper search value. The slope between the upper and lower values ​​is calculated, which is the initial slope. A 5% error in the initial slope is taken as the constraint value to limit the search process.

[0130] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0131] The specific method is as follows:

[0132] The process of determining the data range of the linear segment of the full stress-strain curve based on the obtained Poisson's ratio processed data and search method processed data includes: comparing the upper and lower boundaries of the Poisson's ratio processed data and the search method processed data, and taking the value in the middle of the two, close to the direction of the initial search seed, as the two endpoints of the data range of the linear segment of the full stress-strain curve.

[0133] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

[0134] In an embodiment of the rock elastic parameter calculation method based on the full stress-strain curve provided in this application, the problem of determining the linear elastic range of the full stress-strain curve and reducing the interference error caused by the noise of the sensor itself are solved, aiming to efficiently obtain accurate rock elastic parameters.

[0135] Example Six

[0136] Based on the foregoing embodiments, this application further provides a method for calculating rock elastic parameters based on the full stress-strain curve, including:

[0137] The specific implementation steps are as follows:

[0138] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0139] Specific methods include:

[0140] S101: The filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters; filtering out high-frequency information of the analysis parameters through a low-pass filter, retaining effective low-frequency information to obtain low-frequency data, and removing data caused by the Gibbs effect due to low-pass filtering; in order to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0141] S102: Determining the data calculation interval includes: detecting the maximum position of the axial and lateral extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval. The axial and lateral extensometer values ​​should increase monotonically. If they decrease, it means that there is a problem with the subsequent data and it should be deleted. This is to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0142] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0143] The determination of the constraint limits for rock physical parameters includes: calculating the circumferential axial variation rate of the preprocessed data, which is the instantaneous Poisson's ratio; the position where the instantaneous Poisson's ratio is less than 0 is taken as the lower boundary of the constraint limits for rock physical parameters, and the position where the instantaneous Poisson's ratio is greater than 0.5 is taken as the upper boundary of the constraint limits for rock physical parameters.

[0144] The Poisson's ratio should be controlled within the range of 0-0.5. A ratio less than 0 indicates that the sample is in a state of lattice compression, while a ratio greater than 0.5 indicates that cracks have appeared inside the sample. Using the position where the instantaneous Poisson's ratio is less than 0 as the lower boundary of the physical parameter constraint and the position where it is greater than 0.5 as the upper boundary is more reasonable. This approach can efficiently obtain accurate rock elastic parameters and reduce interference errors caused by sensor noise.

[0145] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0146] The specific method is as follows:

[0147] A search seed is set, assuming that the initial value, i.e., the position of half the stress peak, is within the linear segment of the full stress-strain curve of the preprocessed data. Starting from the position of half the stress peak, the search proceeds in two directions. If the slope difference between the two ends is less than the constraint value, it is considered to still be within the linear segment. This continues until the slope change rate on one side exceeds the constraint value, at which point it is considered to have reached the end of the linear segment. Then, the search proceeds only to the other side. The two ends at this point are considered to be the two ends of the linear segment. This method is used to determine the range of the linear segment of the full stress-strain curve of the preprocessed data, thus obtaining the data processed by the search method.

[0148] The specific method for calculating the constraint value is as follows: Within a search step range approximately half the peak value, the average of the five values ​​at the lower end of the search is taken as the initial lower search value, and the average of the five values ​​at the upper end of the search is taken as the initial upper search value. The slope between the upper and lower values ​​is calculated, which is the initial slope. A 5% error in the initial slope is taken as the constraint value to limit the search process.

[0149] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0150] The specific method is as follows:

[0151] The process of determining the data range of the linear segment of the full stress-strain curve based on the obtained Poisson's ratio processed data and search method processed data includes: comparing the upper and lower boundaries of the Poisson's ratio processed data and the search method processed data, and taking the value in the middle of the two, close to the direction of the initial search seed, as the two endpoints of the data range of the linear segment of the full stress-strain curve.

[0152] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve;

[0153] The specific method is as follows:

[0154] The slope of the linear segment of the full stress-strain curve represents the rock's elastic modulus. The specific method for calculating the rock's elastic modulus includes: determining the stress value at the starting point of the linear segment. and longitudinal strain and the final stress value and longitudinal strain The elastic modulus of the rock is calculated according to formula (1), and the elastic Poisson's ratio of the rock is calculated according to formula (2):

[0155] (1)

[0156] (2)

[0157] In the formula:

[0158] -----Rock elastic modulus, MPa;

[0159] -----Poisson's ratio of rock elasticity;

[0160] -----Stress value at the starting point of the straight line segment on the stress-axial strain curve;

[0161] -----The stress value at the end of the straight line segment on the stress-axial strain curve;

[0162] -----Stress is The longitudinal strain value at that time;

[0163] -----Stress is The longitudinal strain value at that time;

[0164] -----Stress is The circumferential strain value at that time;

[0165] -----Stress is The circumferential strain value at that time.

[0166] In an embodiment of the rock elastic parameter calculation method based on the full stress-strain curve provided in this application, the problem of determining the linear elastic range of the full stress-strain curve and reducing the interference error caused by the noise of the sensor itself are solved, aiming to efficiently obtain accurate rock elastic parameters.

[0167] Example Seven

[0168] Based on the foregoing embodiments, this application further provides a method for calculating rock elastic parameters based on the full stress-strain curve. The embodiments provided in this application are based on real data:

[0169] An algorithm was tested using full stress-strain data from triaxial compression mechanics tests on shale.

[0170] Figure 1 A flowchart illustrating a method for calculating rock elastic parameters based on a full stress-strain curve, provided as an embodiment of this application; Figure 1 As shown, specific methods for calculating rock elastic parameters based on the full stress-strain curve include:

[0171] S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data;

[0172] S2: Based on the preprocessed data, determine the constraint limits of the rock physical parameters to obtain the processed Poisson's ratio data;

[0173] S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0174] S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together;

[0175] S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

[0176] Figures 2(a)-(c) are schematic diagrams of various elastic modulus definitions provided in the embodiments of this application, namely, three elastic modulus schematic diagrams. As the focus of the study, the schematic diagrams of obtaining the corresponding different elastic moduli are given. The focus of this application is to obtain the tangential elastic modulus.

[0177] Figure 3 This is a sample image of a shale rock for rock mechanics testing.

[0178] like Figure 3 As shown, the rock sample numbered SZL-1 in this test is a cylindrical sample with a length of 90.66 mm and a diameter of 49.85 mm. The length and diameter meet the standards for rock mechanics testing.

[0179] Figure 4 This is a full stress-strain curve of a triaxial compression test on shale, with the horizontal axis representing strain and the vertical axis representing stress.

[0180] A uniaxial compression test with a confining pressure of 0 MPa was conducted on the sample, and the corresponding full stress-strain curve was obtained. It can be seen that the slope of the linear elastic segment of the signal changes after a certain value. In addition, the data after the peak does not extend further like a Type I curve. This may be due to the extensometer defect of the MTS mechanical testing instrument itself after the maximum pressure rupture, which prevents the acquisition of a complete post-peak curve.

[0181] Figure 5 shows the spectral analysis of stress and strain data for shale.

[0182] By combining the axial strain data in Figure 5(a) and the axial stress data in Figure 5(b) of shale, a spectral analysis can be performed. It can be seen that the recorded data contains high-frequency interference. This interference is generally introduced into the instrument recording by the sensor itself. Therefore, we need to perform low-pass filtering on the original signal.

[0183] At the same time, it can be seen that the frequency of the data after the peak has a greater impact. At this point, the curve is no longer in line with our research focus. We need to preprocess these curves to retain the calculation range of the linear elastic segment.

[0184] Figure 6 is a schematic diagram showing the determination of linear segments for shale using both the Poisson's ratio constraint method and the seed search method.

[0185] For the processed stress-strain curves, we need to determine the upper and lower limits of Poisson's ratio. This is achieved by calculating the circumferential axial change rate of the sample, which is the instantaneous Poisson's ratio. There should be constraints to control the Poisson's ratio within the range of 0-0.5. A ratio less than 0 indicates that the sample is in a lattice-compressed state, while a ratio greater than 0.5 indicates that cracks have appeared inside the sample. The star points in Figures 6(a), 6(b), and 6(c) represent the corresponding upper and lower endpoints of the Poisson's ratio constraints.

[0186] A seed search method is used, with the initial seed value set at half the peak intensity. The values ​​of the interval data with fixed step sizes to the left and right of the center position are calculated, and the interval data are averaged using five points for noise reduction. The data values ​​to the left and right of the center position are calculated as the slope of the initial linear segment. The search begins in two directions, and if the slope difference between the two ends is less than the constraint value, it is considered to still be within the linear segment. This continues until the slope change rate on one side exceeds the constraint value, at which point the side is considered to have reached the end of the linear segment, and the search begins only on the other side until that end. These two ends are then considered the two ends of the linear segment, thus defining the linear segment.

[0187] The specific method for calculating the constraint value is as follows: Within a search step range approximately half the peak value, the average of the five values ​​at the lower end of the search is taken as the initial lower search value, and the average of the five values ​​at the upper end of the search is taken as the initial upper search value. The slope between the upper and lower values ​​is calculated, which is the initial slope. A 5% error in the initial slope is taken as the constraint value to limit the search process.

[0188] Finally, the linear segment is determined by combining the upper and lower limits of Poisson's ratio and the search limit. The calculation results are shown in Figure 6(d).

[0189] Figure 7 shows the algorithm processing and analysis results of the triaxial compression test of shale.

[0190] Figure 7(a) shows the calculation results for shale sample SZL-1, and Figure 7(b) shows the calculation results for shale sample SZL-4. The shale sample SZL-4 underwent a mechanical test with a confining pressure of 60 MPa. It can be seen that the elastic modulus of the shale changes, and the linear elastic segment of the corresponding stress-strain elastic curve is more pronounced than the full stress-strain curve without confining pressure. Through testing with multiple samples, this method for calculating rock elastic parameters based on the full stress-strain curve is proven to be efficient and feasible.

[0191] Example Eight

[0192] Based on the foregoing embodiments, this application further provides a rock elastic parameter calculation device based on the full stress-strain curve, such as... Figure 8 As shown, it includes device 200:

[0193] Data preprocessing module 201: Filters the original full stress-strain curve data, determines the data calculation range based on the filtering results, and obtains the preprocessed data;

[0194] Specific methods include:

[0195] S101: The filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters; filtering out high-frequency information of the analysis parameters through a low-pass filter, retaining effective low-frequency information to obtain low-frequency data, and removing data caused by the Gibbs effect due to low-pass filtering; in order to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0196] S102: Determining the data calculation interval includes: detecting the maximum position of the axial and lateral extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval. The axial and lateral extensometer values ​​should increase monotonically. If they decrease, it means that there is a problem with the subsequent data and it should be deleted. This is to ensure the stability and reliability of the data, facilitate subsequent data analysis, remove noise, and ensure the results of subsequent steps.

[0197] Poisson's ratio data processing module 202: Based on the preprocessed data, determine the constraint limits of the rock physical parameters and obtain the Poisson's ratio processed data;

[0198] The determination of the constraint limits for rock physical parameters includes: calculating the circumferential axial variation rate of the preprocessed data, which is the instantaneous Poisson's ratio; the position where the instantaneous Poisson's ratio is less than 0 is taken as the lower boundary of the constraint limits for rock physical parameters, and the position where the instantaneous Poisson's ratio is greater than 0.5 is taken as the upper boundary of the constraint limits for rock physical parameters.

[0199] The Poisson's ratio should be controlled within the range of 0-0.5. A ratio less than 0 indicates that the sample is in a state of lattice compression, while a ratio greater than 0.5 indicates that cracks have appeared inside the sample. Using the position where the instantaneous Poisson's ratio is less than 0 as the lower boundary of the physical parameter constraint and the position where it is greater than 0.5 as the upper boundary is more reasonable. This approach can efficiently obtain accurate rock elastic parameters and reduce interference errors caused by sensor noise.

[0200] Search method data processing module 203: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data;

[0201] The specific method is as follows:

[0202] A search seed is set, assuming that the initial value, i.e., the position of half the stress peak, is within the linear segment of the full stress-strain curve of the preprocessed data. Starting from the position of half the stress peak, the search proceeds in two directions. If the slope difference between the two ends is less than the constraint value, it is considered to still be within the linear segment. This continues until the slope change rate on one side exceeds the constraint value, at which point it is considered to have reached the end of the linear segment. Then, the search proceeds only to the other side. The two ends at this point are considered to be the two ends of the linear segment. This method is used to determine the range of the linear segment of the full stress-strain curve of the preprocessed data, thus obtaining the data processed by the search method.

[0203] The specific method for calculating the constraint value is as follows: Within a search step range approximately half the peak value, the average of the five values ​​at the lower end of the search is taken as the initial lower search value, and the average of the five values ​​at the upper end of the search is taken as the initial upper search value. The slope between the upper and lower values ​​is calculated, which is the initial slope. A 5% error in the initial slope is taken as the constraint value to limit the search process.

[0204] Data processing module 204 for the linear segment of the full stress-strain curve: Based on the obtained Poisson's ratio processing data and search method processing data, the data range of the linear segment of the full stress-strain curve is jointly determined;

[0205] The specific method is as follows:

[0206] The process of determining the data range of the linear segment of the full stress-strain curve based on the obtained Poisson's ratio processed data and search method processed data includes: comparing the upper and lower boundaries of the Poisson's ratio processed data and the search method processed data, and taking the value in the middle of the two, close to the direction of the initial search seed, as the two endpoints of the data range of the linear segment of the full stress-strain curve.

[0207] Rock elastic parameter calculation module 205: Calculates rock elastic parameters based on the data range of the linear segment of the full stress-strain curve;

[0208] The specific method is as follows:

[0209] The slope of the linear segment of the full stress-strain curve represents the rock's elastic modulus. The specific method for calculating the rock's elastic modulus includes: determining the stress value at the starting point of the linear segment. and longitudinal strain and the final stress value and longitudinal strain The elastic modulus of the rock is calculated according to formula (1), and the elastic Poisson's ratio of the rock is calculated according to formula (2):

[0210] (1)

[0211] (2)

[0212] In the formula:

[0213] -----Rock elastic modulus, MPa;

[0214] -----Poisson's ratio of rock elasticity;

[0215] -----Stress value at the starting point of the straight line segment on the stress-axial strain curve;

[0216] -----The stress value at the end of the straight line segment on the stress-axial strain curve;

[0217] -----Stress is The longitudinal strain value at that time;

[0218] -----Stress is The longitudinal strain value at that time;

[0219] -----Stress is The circumferential strain value at that time;

[0220] -----Stress is The circumferential strain value at that time.

[0221] In one embodiment of the rock elastic parameter calculation method based on the full stress-strain curve provided in this application, the problem of determining the linear elastic range of the full stress-strain curve and reducing interference errors caused by sensor noise are addressed. The aim is to efficiently obtain accurate rock elastic parameters.

[0222] It should be noted that, in the embodiments of this application, if the above-described method for calculating rock elastic parameters based on the full stress-strain curve is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0223] Accordingly, this application provides a storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps in the rock elastic parameter calculation method based on the full stress-strain curve provided in the above embodiments.

[0224] Example Nine

[0225] This application provides a rock elastic parameter calculation device based on a full stress-strain curve, including a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor is configured to execute the program of the rock elastic parameter calculation method based on the full stress-strain curve stored in the memory, so as to implement the steps in the rock elastic parameter calculation method based on the full stress-strain curve provided in the above embodiment.

[0226] The descriptions of the display device and storage medium embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the computer device and storage medium embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0227] It should be noted that the descriptions of the storage medium and device embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0228] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0229] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0230] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0231] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0232] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0233] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0234] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a controller to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0235] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for calculating the elastic parameters of rock based on the full stress-strain curve, characterized in that, include: S1: Data preprocessing includes: filtering the original full stress-strain curve data, determining the data calculation interval based on the filtering results, and obtaining the preprocessed data; the filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters, and using a low-pass filter to filter out the high-frequency information of the analysis parameters while retaining the effective low-frequency information to obtain low-frequency data; S2: Based on the preprocessed data, determine the constraint limits of the rock physical significance parameters to obtain the Poisson's ratio processed data; the determination of the constraint limits of the rock physical significance parameters includes: calculating the circumferential axial change rate of the preprocessed data, which is the instantaneous Poisson's ratio, and taking the position where the instantaneous Poisson's ratio is less than 0 as the lower boundary of the constraint limits of the rock physical significance parameters, and taking the position where the instantaneous Poisson's ratio is greater than 0.5 as the upper boundary of the constraint limits of the rock physical significance parameters. S3: Based on the preprocessed data, the local optimum adaptive seed search method is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data; S4: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is determined together; S5: Calculate the rock elastic parameters based on the data range of the linear segment of the determined full stress-strain curve.

2. The method according to claim 1, characterized in that, The process of determining the data calculation interval includes: detecting the maximum position of the axial and transverse extensometers of the low-frequency data, and deleting all data after the maximum position to obtain the data calculation interval.

3. The method according to claim 2, characterized in that, The specific method of the locally optimal adaptive seed search method is as follows: A search seed is set, and the initial value, i.e., the position of half the stress peak, is considered to be within the linear segment of the full stress-strain curve of the preprocessed data. Starting from the position of half the stress peak, the search proceeds in two directions. If the slope difference between the two ends is less than the constraint value, it is considered to still be within the linear segment. This continues until the slope change rate on one side exceeds the constraint value, at which point it is considered to have reached the end of the linear segment. Then, only the other side is searched until the end. The two ends at this point are considered to be the two ends of the linear segment. This method is used to determine the range of the linear segment of the full stress-strain curve of the preprocessed data, thus obtaining the data processed by the search method.

4. The method according to claim 3, characterized in that, The process of determining the data range of the linear segment of the full stress-strain curve based on the obtained Poisson's ratio processed data and search method processed data includes: comparing the upper and lower boundaries of the Poisson's ratio processed data and the search method processed data, and taking the value in the middle of the two, close to the direction of the initial search seed, as the two endpoints of the data range of the linear segment of the full stress-strain curve.

5. The method according to claim 4, characterized in that, The slope of the linear segment of the full stress-strain curve represents the rock's elastic modulus. Specific methods for calculating the rock's elastic modulus include: determining the stress value at the starting point of the linear segment. and longitudinal strain and the final stress value and longitudinal strain The elastic modulus of the rock is calculated according to formula (1), and the elastic Poisson's ratio of the rock is calculated according to formula (2): （1） （2） In the formula: -----Rock elastic modulus, MPa; -----Poisson's ratio of rock elasticity; -----Stress value at the starting point of the straight line segment on the stress-axial strain curve; -----The stress value at the end of the straight line segment on the stress-axial strain curve; -----Stress is The longitudinal strain value at that time; -----Stress is The longitudinal strain value at that time; -----Stress is The circumferential strain value at that time; -----Stress is The circumferential strain value at that time.

6. A device for calculating the elastic parameters of rock based on the full stress-strain curve, characterized in that, include: Data preprocessing module: Filters the original full stress-strain curve data, determines the data calculation range based on the filtering results, and obtains the preprocessed data; The filtering process includes: performing spectral analysis on the waveform of the original full stress-strain curve data to obtain analysis parameters, and using a low-pass filter to filter out the high-frequency information of the analysis parameters while retaining the effective low-frequency information to obtain low-frequency data; Poisson's ratio data processing module: Based on the preprocessed data, determine the constraint limits of rock physical parameters to obtain Poisson's ratio processed data; the determination of the constraint limits of rock physical parameters includes: calculating the circumferential axial change rate of the preprocessed data, which is the instantaneous Poisson's ratio; the position where the instantaneous Poisson's ratio is less than 0 is taken as the lower boundary of the constraint limits of rock physical parameters, and the position where it is greater than 0.5 is taken as the upper boundary of the constraint limits of rock physical parameters. The search method data processing module: Based on the preprocessed data, the adaptive seed search method with local optimum is used to optimize the linear search segment of the preprocessed data to obtain the search method processed data; The data processing module for the linear segment of the full stress-strain curve: Based on the obtained Poisson's ratio processing data and the search method processing data, the data range of the linear segment of the full stress-strain curve is jointly determined; Rock elastic parameter calculation module: Calculates rock elastic parameters based on the data range of the linear segment of the full stress-strain curve.

7. A device for calculating the elastic parameters of rock based on the full stress-strain curve, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs the rock elastic parameter calculation method based on the full stress-strain curve as described in any one of claims 1 to 5.

8. A storage medium, characterized in that, The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the rock elastic parameter calculation method based on the full stress-strain curve as described in any one of claims 1 to 5.

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