A 3D core in-situ stress measurement system and method based on multi-source data

Abstract

The present invention relates to the technical field of in-situ stress measurement, and particularly to a three-dimensional in-situ stress measurement system and method for core based on multi-source data. The method includes the following steps: obtaining wellbore failure information and identifying the failure type in the wellbore failure information; selecting multiple core samples based on the wellbore failure information and determining the overburden pressure parameter based on the multiple core samples; performing rock mechanics experiments on the core samples to generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value. By combining the difference between the maximum and minimum stresses with the multi-source coupled constraint principal stress interval and using the topological visualization graph to identify the intersection points, the present invention can accurately determine the numerical ranges of the maximum and minimum principal stresses, and further obtain the information of three-dimensional in-situ stress.

Description

Technical Field

[0001] The present invention relates to the technical field of in-situ stress measurement, and particularly to a three-dimensional in-situ stress measurement system and method for core based on multi-source data. Background Art

[0002] The in-situ stress state is jointly determined by the in-situ stress direction and the stress magnitude, where the stress magnitude includes the vertical stress and the horizontal principal stresses. The vertical stress is usually obtained by integrating the density of the overlying strata and is relatively easy to measure; while the accurate determination of the maximum and minimum principal stresses in the horizontal direction, especially the maximum principal stress, still faces many challenges technically, and is more complex under deep formation conditions. Traditional in-situ stress measurement methods mainly include hydraulic fracturing, image logging, stress relief, anelastic strain recovery (ASR) of core and seismic wave method. Although borehole methods such as hydraulic fracturing are commonly used for field measurement, the measured maximum principal stress value is greatly affected by factors such as formation heterogeneity and fracture development, and the error is relatively high; core methods such as ASR have strict requirements for sample processing accuracy and the experiments are complex; while the seismic method relies on natural earthquakes or artificial excitation, and the applicable scenarios are limited.

[0003] In recent years, multi-source fusion measurement methods based on core mechanical experiments and wellbore imaging have gradually emerged. Such methods combine the analysis of wellbore failure characteristics with core mechanical parameters, supplemented by differential loading experiments to deduce the difference between the maximum and minimum principal stresses, and construct a stress polygon model and a failure mode to invert the stress state, which has strong practicability and adaptability. However, the existing methods still have problems such as insufficient utilization of wellbore information, unclear judgment of principal stresses, low efficiency of multi-source data fusion, and weak sample representativeness, which restrict their wide application in deep complex structural areas. Summary of the Invention

[0004] Based on this, it is necessary for the present invention to provide a three-dimensional in-situ stress measurement system and method for core based on multi-source data to solve at least one of the above technical problems.

[0005] To achieve the above object, a three-dimensional in-situ stress measurement method for core based on multi-source data includes the following steps:

[0006] Step S1: Obtain wellbore failure information and identify the failure types in the wellbore failure information; select multiple core samples based on the wellbore failure information, and determine the overburden pressure parameter based on the multiple core samples;

[0007] Step S2: Conduct rock mechanics experiments on the core samples to generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value and tensile strength value;

[0008] Step S3: Mark smooth core samples from multiple core samples based on the failure type, and conduct a core diameter deformation analysis experiment on the smooth core samples using the Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses;

[0009] Step S4: Construct a stress polygon model based on the overburden pressure parameter; construct a wellbore failure model based on the failure type; use the stress polygon model and the wellbore failure model to plan a two-dimensional constraint region, and execute multi-source coupled constraint principal stresses;

[0010] Step S5: Based on the failure type, execute strength constitutive constraint principal stresses using the uniaxial compressive strength value or the tensile strength value;

[0011] Step S6: Topologically visualize the multi-source coupled constraint principal stresses and the strength constitutive constraint principal stresses, and perform regional overlap determination on the difference between the maximum and minimum stresses and the topological visualization results to determine the numerical ranges of the maximum principal stress and the minimum principal stress.

[0012] The present invention improves the accuracy and adaptability of in-situ stress measurement through a systematic and multi-source fusion method, and has significant beneficial effects. First, it makes full use of wellbore failure information to improve the ability to identify the formation stress state and avoid the problem of low utilization rate of wellbore information in traditional methods. Second, by selecting and comparing multiple types of core samples, the representativeness of the samples is enhanced, thereby improving the reliability of experimental data. Combining the DCDA experiment to extract the difference between the maximum and minimum stresses effectively avoids the problem of large errors in a single measurement method, and is particularly suitable for deep structural areas with strong formation heterogeneity. At the same time, introducing a stress polygon model and a wellbore failure model to form a two-dimensional constraint system, and combining it with the rock strength constitutive relationship, realizes the deep fusion of multi-source data, and greatly improves the accuracy and physical consistency of principal stress derivation. Finally, through topological visualization means for regional overlap analysis, it not only enhances the intuitiveness and interpretability of the stress identification process, but also effectively improves the stability and accuracy of the determination of the maximum principal stress and the minimum principal stress ranges, providing a more reliable and popularizable technical path for deep in-situ stress research.

[0013] Preferably, the present invention also provides a core three-dimensional in-situ stress measurement system based on multi-source data for implementing the above-mentioned core three-dimensional in-situ stress measurement method based on multi-source data. The core three-dimensional in-situ stress measurement system based on multi-source data includes:

[0014] A failure recognition module, configured to obtain wellbore failure information and identify the failure type in the wellbore failure information; select multiple core samples based on the wellbore failure information, and determine the overburden pressure parameter based on the multiple core samples;

[0015] A mechanical testing module, which is used to conduct rock mechanics experiments on core samples and generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value;

[0016] A stress difference measurement module, which is used to mark smooth core samples from various core samples based on the failure type, and conduct core diameter deformation analysis experiments on the smooth core samples by using Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses;

[0017] A stress modeling module, which is used to construct a stress polygon model based on overburden pressure parameters; construct a wellbore failure model based on the failure type; establish a two-dimensional constraint system by using the stress polygon model and the wellbore failure model, and execute multi-source coupled constraint principal stresses;

[0018] A range constraint module, which is used to execute strength constitutive constraint principal stresses by using the uniaxial compressive strength value / tensile strength value based on the failure type;

[0019] An intersection inversion module, which is used to perform topological visualization on the multi-source coupled constraint principal stresses and the strength constitutive constraint principal stresses, and perform regional overlap determination on the difference between the maximum and minimum stresses and the topological visualization result to determine the numerical range of the maximum principal stress and the minimum principal stress.

[0020] Through modular design, the present invention integrates multi-source data and multi-dimensional constraint means, significantly improving the scientificity and practicality of in-situ stress measurement, and having beneficial effects in many aspects. First, the failure identification module improves the identification depth and utilization efficiency of wellbore information, enabling accurate classification of failure characteristics and guiding sample selection, enhancing data representativeness and the accuracy of overburden pressure estimation. The mechanical testing module ensures the comprehensiveness of core parameter acquisition and the standardization of experiments, laying a solid foundation for subsequent analysis. The stress difference measurement module provides a reliable stress difference reference by identifying smooth cores and conducting DCDA experiments, avoiding the uncertainty of traditional methods in heterogeneous or fractured formations. The stress modeling module uses a two-dimensional constraint method to solve multi-source coupled principal stresses, significantly improving the adaptability of the model to complex geological environments and the accuracy of principal stress judgment. The range constraint module further introduces a strength constitutive relationship to limit the stress boundary, making the stress solution more physically constrained and practically engineering significant. Finally, the intersection inversion module enhances the intuitiveness and reliability of the results through topological visualization and overlap analysis of stress differences, effectively realizing the comprehensive determination of the maximum and minimum principal stress ranges, and providing efficient and popularizable technical support for stress analysis in deep tectonic areas. Description of the Drawings

[0021] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent:

[0022] Figure 1 Schematic diagram of the step process of a method for measuring three-dimensional in-situ stress of cores based on multi-source data according to the present invention;

[0023] Figure 2 is Figure 1 a detailed step process diagram of step S1 in

[0024] Figure 3 is Figure 1 a detailed step process diagram of step S2 in Specific embodiments

[0025] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0026] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0027] It should be understood that although terms such as "first" and "second" may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed related items.

[0028] To achieve the above object, please refer to Figures 1 to 3 , the present invention provides a method for measuring three-dimensional in-situ stress of cores based on multi-source data, and the method includes the following steps:

[0029] Step S1: Obtain wellbore failure information and identify the failure type in the wellbore failure information; select multiple core samples based on the wellbore failure information, and determine the overburden pressure parameter based on the multiple core samples;

[0030] Step S2: Conduct rock mechanics experiments on the core samples to generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value;

[0031] Step S3: Mark the smooth core samples from various core samples based on the failure type, and conduct core diameter deformation analysis experiments on the smooth core samples using Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses;

[0032] Step S4: Construct a stress polygon model based on the overburden pressure parameters; construct a wellbore failure model based on the failure type; use the stress polygon model and the wellbore failure model to plan a two-dimensional constraint region and execute multi-source coupled constraint principal stresses;

[0033] Step S5: Based on the failure type, use the uniaxial compressive strength value or the tensile strength value to execute strength constitutive constraint principal stresses;

[0034] Step S6: Visualize the multi-source coupled constraint principal stresses and the strength constitutive constraint principal stresses topologically, and perform regional overlap determination on the difference between the maximum and minimum stresses and the topological visualization results to determine the numerical ranges of the maximum principal stress and the minimum principal stress. <s

[0035] In the embodiment of the present invention, refer to Figure 1 As shown, it is a schematic diagram of the step flow of a core three-dimensional in-situ stress measurement method based on multi-source data according to the present invention. In this example, the core three-dimensional in-situ stress measurement method based on multi-source data includes the following steps:

[0036] Step S1: Obtain wellbore failure information and identify the failure type in the wellbore failure information; select multiple core samples based on the wellbore failure information, and determine the overburden pressure parameters based on the multiple core samples;

[0037] In the embodiment of the present invention, first, the borehole wall image data in the depth range of 300 - 500 meters of the target measurement section is collected by a borehole micro-resistivity imaging logging tool with a vertical resolution of 1 millimeter. Then, the wavelet transform method is used to remove the noise from the borehole wall image data, and the histogram equalization technology is used to enhance the image. The signal-to-noise ratio after enhancement is increased by at least 20%. Then, the borehole wall failure characteristic information, including the failure position, shape, and azimuth angle, is extracted by using gray gradient analysis. According to the extracted characteristic information, the failure type is identified by determining the geometric characteristics of the failure shape (if it shows irregular blocky spalling, it is determined as caving; if it shows regular parallel longitudinal lines, it is determined as induced tensile cracks). Subsequently, based on the lithology change characteristics and failure distribution law shown in the borehole wall image data, at least 3 representative core samples are selected in each failure zone. The diameter of the core samples is 25.4 millimeters, and the length is 50.8 millimeters to ensure that the sampling position strictly corresponds to the failure area. Finally, the core density value on the depth profile is obtained by using the acoustic logging data The density measurement accuracy is controlled within ±0.05 g / cm³, combined with the gravitational acceleration constant (9.8 m / s²) and the measured well depth , through the integral formula Calculate the overburden pressure parameter. When calculating, the depth profile is discretized into 500 depth points. At each depth point, the core density value is determined by cubic spline interpolation, and then the Simpson integral method is used for numerical integration operation to obtain the overburden pressure parameter value accurate to 0.1 MPa.

[0038] Step S2: Conduct rock mechanics experiments on the core samples to generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value;

[0039] In the embodiment of the present invention, first, the selected core samples are inspected for physical dimensions to ensure that the diameter deviation does not exceed ±0.5 mm and the length deviation does not exceed ±1.0 mm. Standard shaping treatment is carried out by a high-precision diamond cutting machine to ensure that the parallelism deviation of the two end faces is less than 0.02 mm and the perpendicularity deviation is less than 0.05 mm, forming standard cylindrical samples to be tested; Subsequently, P-wave (longitudinal wave) and S-wave (transverse wave) ultrasonic transducers are installed at both ends of the samples to be tested, with the frequency set at 500 kHz. The ultrasonic detector is used to emit and receive wave signals with a sampling accuracy of 5 ns, record the wave propagation time, and calculate the longitudinal wave velocity and the transverse wave velocity accurate to 10 m / s, and according to the formula Calculate Poisson's ratio , accurate to 0.01, according to the formula Calculate Young's modulus , accurate to 0.1 GPa; Then place the samples to be tested in the MTS815 hydraulic servo loading system for standard uniaxial compression test, with the loading rate controlled at 0.5 MPa / s, continuously apply axial pressure until the sample undergoes macroscopic failure, and record the maximum axial stress value at the time of failure as the uniaxial compressive strength value , with the measurement accuracy controlled within ±0.5 MPa; Subsequently, adopt the Brazilian splitting test method, place the samples to be tested in a special fixture, apply radial compressive load, with the loading rate controlled at 200 N / s until the sample splits axially, and according to the formula Calculate the tensile strength value , where is the fracture load value (unit: N), is the sample diameter (unit: mm), is the sample length (unit: mm), and the calculation result is accurate to 0.1 MPa; Finally, the measured Poisson's ratio , Young's modulus (Unit: GPa), uniaxial compressive strength value (Unit: MPa) and tensile strength value (Unit: MPa) are summarized and recorded as the rock mechanical parameters of the rock sample.

[0040] Step S3: Mark smooth core samples from multiple core samples based on the failure type, and conduct a core diameter deformation analysis experiment on the smooth core samples using the Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses;

[0041] In the embodiment of the present invention, first, according to the failure type (caving or induced tensile cracks), core samples with a surface smoothness reaching are screened out from multiple core samples. The KEYENCE LK-G10 laser displacement meter is used to measure once every 15° along the circumferential direction on the cross-section of the smooth core sample, with a total of 24 points measured, and the measurement accuracy is controlled within the range of ±0.001 mm; Subsequently, record the original diameter distribution data of the smooth core sample under the condition of no external force (i.e., zero stress state), accurate to 0.001 mm; Then, use the MTS816 type hydraulic servo loading system to apply an axial pressure to the smooth core sample, with the loading value set to 20 MPa and the loading rate controlled at 0.2 MPa / s, and keep it constant for 120 seconds to ensure that the sample is fully deformed; After the loading state is stable, use the laser displacement meter again to measure the diameter change of the smooth core sample at the same 24 angular positions to obtain the deformed radial dimension data accurate to 0.001 mm; Then, determine the maximum value (corresponding angle ) and the minimum value (corresponding angle ) of the diameter after loading, and verify whether the difference between these two angles is approximately 90° ± 5° (verify the stress field anisotropy characteristics). Subsequently, substitute the Young's modulus value (unit GPa) and the Poisson's ratio value into the differential deformation stress analysis (DCDA) formula:

[0042] Calculate the difference between the maximum and minimum stresses (unit MPa), and the unit consistency needs to be maintained during the calculation process Take the average value of the 24 measured points. The ambient temperature during the whole measurement process is controlled at 23 ± 2 °C, and the laboratory relative humidity is controlled at 50% ± 10%. The calculation result is accurate to 0.1 MPa. At the same time, the azimuth angles corresponding to the maximum deformation and the minimum deformation need to be recorded. The entire DCDA experiment is repeated 3 times for each smooth core sample, and the arithmetic mean value is taken as the final result.

[0043] Step S4: constructing a stress polygon model based on the overburden pressure parameters; constructing a wellbore failure model based on the failure type; planning a two-dimensional constraint area using the stress polygon model and the wellbore failure model, and executing multi-source coupling to constrain principal stresses;

[0044] In the embodiment of the present invention, the pore pressure is collected every 20 meters using the RFT repeated bottom tester in the target measurement section. The data was collected in the pressure range of 0-70MPa with an accuracy of ±0.1MPa. The collected data was filtered to remove abnormal values and the average value was taken as the representative value. , combined with the friction coefficient Take the value 0.75 and substitute it into the three sets of inequalities:

[0045] ;

[0046] Construct stress polygon model and calculate The value is about 3.1, and the maximum principal stress is obtained by solving the inequality group and minimum principal stress Then, based on the damage type, a wellbore damage model is constructed. The specific operations are as follows: record the drilling fluid pressure (Measured using a drilling fluid pressure gauge with an accuracy of ±0.5 MPa), the effective stress around the wellbore wall in the cylindrical coordinate system is expressed as:

[0047] ;

[0048] Substitute into the calculation; when the failure type is collapse, the shear failure criterion is applied , internal friction angle Take 30°, is the uniaxial compressive strength value; when the failure type is induced tensile cracks, the tensile failure criterion is applied is the tensile strength value; then a two-dimensional rectangular coordinate system is established in the MATLAB R2023a environment, and the horizontal axis represents the minimum principal stress (Unit: MPa), the vertical axis represents the maximum principal stress (Unit: MPa), the constraints of the stress polygon model are drawn as a closed area (stress polygon constraint area), and the constraints of the wellbore failure model are drawn as a boundary curve. After superimposing the two figures, meshing is performed (grid density 0.1MPa×0.1MPa), and the intersection area point set that meets the two constraints is extracted to obtain the multi-source coupling constraint principal stress interval. The interval boundary is accurate to 0.1MPa. In this process, the measured wellbore failure angle is Substitute the value obtained from the analysis of the wellbore image in step S1 (i.e., ), and take the standard wellbore radius of 83.3 mm for calculation, and finally obtain the multi-source coupled constraint principal stress range.

[0049] Step S5: Based on the failure type, use the uniaxial compressive strength value or the tensile strength value to perform strength constitutive constraint on the principal stress.

[0050] In the embodiment of the present invention, first, the failure type is determined by the wellbore failure information obtained by the failure identification module. When the failure type is caving, the uniaxial compressive strength value measured by the mechanical test module is applied to the shear failure criterion, that is, the calculation formula , where is the internal friction angle of the core, and the value range is from 25° to 35°. Different fixed values are taken for different core types; for each point in the multi-source coupled constraint principal stress range, substitute it into this formula for verification. When , the combination satisfies the condition, mark this point as a feasible solution, otherwise mark it as an infeasible solution, so as to form the distribution of the feasible solution region and the infeasible solution region; then eliminate the infeasible solution region to obtain the strength constitutive constraint principal stress range that meets the shear limit condition of the core; when the failure type is induced tensile cracks, the system performs thermal stress perturbation analysis and calculates the additional tensile stress value generated during the cooling process. The calculation formula is , where is the thermal expansion coefficient, and the value range is to , is the Young's modulus, and are the original temperature and the temperature after cooling of the core respectively. The temperature difference is generally 10 to 30 degrees Celsius, is the Poisson's ratio; apply the additional tensile stress value and the tensile strength value () measured by the mechanical test module together to the tensile failure criterion , and correct the boundary of the original multi-source coupled constraint principal stress range to obtain a more accurate strength constitutive constraint principal stress range; the system transmits the corrected strength constitutive constraint principal stress range to the intersection inversion module for region overlap determination with the difference between the maximum and minimum stresses.

[0051] Step S6: Topologically visualize the multi-source coupled constraint principal stress and the strength constitutive constraint principal stress, and perform region overlap determination on the difference between the maximum and minimum stresses and the topological visualization result to determine the numerical ranges of the maximum principal stress and the minimum principal stress.

[0052] In the embodiment of the present invention, the intersection inversion module first takes the difference Converted into a stress difference constraint line, the expression is , where is the maximum stress value, is the minimum stress value, and this constraint line appears as a straight line with a constant slope of 1 in the two-dimensional plane; Subsequently, the intersection inversion module creates a standard two-dimensional rectangular coordinate system, defines the abscissa as the minimum principal stress , with a value range of 10 MPa to 100 MPa, and the ordinate is defined as the maximum principal stress , with a value range of 20 MPa to 150 MPa; Then, the multi-source coupled constrained principal stress interval (manifested as a closed polygon area in the two-dimensional coordinate system) and the strength constitutive constrained principal stress interval (manifested as a further restriction on the polygon area) are plotted in this two-dimensional coordinate system. At the same time, the stress difference constraint line is superimposed on the same coordinate system to form a complete caving / induced tensile fracture topology visualization diagram; The intersection inversion module identifies the exact intersection coordinates of the stress difference constraint line and the boundary of the constraint area through numerical calculation. When the intersection points are two discrete points, the line segment between these two points is the reasonable stress value interval, and each point within the interval satisfies the stress difference constraint, stress polygon constraint, wellbore failure constraint, and strength constitutive constraint conditions; When the intersection point is a single point, this point is the exact stress solution, denoted as ; For an actual case, such as a well in a certain oilfield at a depth of 2500 meters, the topological visualization analysis results obtained by this method show that the minimum principal stress has a numerical range of 45.7 MPa to 52.3 MPa, the maximum principal stress has a numerical range of 68.2 MPa to 74.8 MPa, the vertical stress is fixed at 67.5 MPa, and the stress difference is 22.5 MPa, thereby determining the complete three-dimensional in-situ stress state at this depth.

[0053] The present invention improves the accuracy and adaptability of in-situ stress measurement through a systematic and multi-source fusion method, with significant beneficial effects. First, it makes full use of borehole wall failure information to enhance the ability to identify the formation stress state and avoid the problem of low utilization rate of borehole wall information in traditional methods. Second, by selecting and comparing different types of core samples, the representativeness of the samples is enhanced, thereby improving the reliability of experimental data. Combining the DCDA experiment to extract the difference between the maximum and minimum stresses effectively avoids the problem of large errors in single measurement methods and is particularly suitable for deep structural areas with strong formation heterogeneity. At the same time, introducing the stress polygon model and the borehole wall failure model to form a two-dimensional constraint system and combining it with the constitutive relationship of rock strength realizes the deep fusion of multi-source data, greatly improving the accuracy and physical consistency of principal stress derivation. Finally, through topological visualization means for regional overlap analysis, it not only enhances the intuitiveness and interpretability of the stress identification process but also effectively improves the stability and accuracy of determining the ranges of the maximum principal stress and the minimum principal stress, providing a more reliable and popularizable technical path for deep in-situ stress research.

[0054] Preferably, step S1 includes the following steps:

[0055] Step S11: Collect borehole wall image data of the measurement section through a borehole micro-resistivity imaging logging tool;

[0056] Step S12: Remove noise and enhance the image of the borehole wall image data of the measurement section, and extract borehole wall failure information;

[0057] Step S13: Identify the failure type based on the borehole wall failure information, where the failure type includes caving and induced tensile fractures;

[0058] Step S14: Identify the core distribution law based on the borehole wall failure information, and select various core samples based on the core distribution law;

[0059] Step S15: Calculate the overburden pressure parameters of various core samples based on the borehole wall failure information. The specific calculation process is as follows:

[0060] ,

[0061] where is the overburden pressure parameter, is the depth at which the density of the core, is the acceleration due to gravity, is the core depth.

[0062] In the embodiment of the present invention, the damage recognition module uses a STAR-II type borehole resistivity imaging logging tool. The logging tool is equipped with 8 microelectrode arms, each arm carrying 12 microelectrodes, for a total of 96 measurement points. It conducts a 360° omnidirectional scan of the measurement section in the well at a uniform lifting rate of 2 cm / s, with a sampling interval of 5 mm, an electrode radial measurement accuracy of 0.1 mm, and an azimuth measurement accuracy of 2°. High-resolution borehole wall image data is obtained; the collected borehole wall image data is digitally filtered. A Gaussian filter is used to eliminate random noise, and the filter radius is set to 3 pixels. Subsequently, histogram equalization is used for image enhancement, and the contrast enhancement parameter is set to 1.5. The borehole wall damage information, including the position of the fracture zone, fracture width, fracture depth, and azimuth angle, is extracted through an FMI image processing workstation to form a borehole wall damage feature dataset; based on the borehole wall damage feature dataset, the damage type is identified. When the borehole wall shows a symmetric fan-shaped damage area and the azimuth is consistent with the direction of the minimum horizontal principal stress, it is determined as caving. When the borehole wall shows longitudinal axial cracks and the azimuth is consistent with the direction of the maximum horizontal principal stress, it is determined as induced tensile cracks, and the key damage feature parameters are recorded; according to the borehole wall damage information, the core sampling depth and position are determined. Priority is given to selecting sections with obvious damage phenomena and uniform lithology. At least 5 core samples of different lithologies, including sandstone, mudstone, limestone, shale, and migmatite, are selected from the measurement section. Each lithology is sampled no less than 3 times. The core diameter is uniformly 62.5 mm, and the length is 125 mm to ensure a length-diameter ratio of 2:1. Information such as the core sampling depth, lithology, color, and density is numbered and recorded; the core density at the depth of each core sample is calculated using gamma density logging data , the density measurement accuracy is ±0.01 g / cm³, and the core depth is accurate to ±0.1 m, and the acceleration due to gravity is taken as 9.8 m / s² and substituted into the formula for integral calculation. Through the trapezoidal integration method, the continuous integral is discretized into , where is the thickness of the layer, and the integration step size is set to 5 m. Finally, the overburden pressure parameter is calculated, and the unit is MPa.

[0063] Through high-precision image acquisition and intelligent analysis processes, the present invention effectively improves the scientific nature and pertinence of wellbore damage information extraction and core sample selection, with significant beneficial effects. First, high-resolution wellbore damage images are acquired using microresistivity imaging logging technology, which enhances the ability to perceive microstructural changes around the wellbore and provides a rich data foundation for subsequent analysis. The image processing and enhancement steps improve the identifiability of damage features, making the extraction of wellbore damage information more accurate and reliable, and effectively reducing information omissions or misjudgments caused by noise interference. The identification of damage types enables the classification and judgment of typical damage modes such as collapse and tensile fractures, providing important prior conditions for subsequent stress state derivation. At the same time, by identifying and analyzing the distribution patterns of cores, representative core samples can be selected in a targeted manner, significantly improving the adaptability of samples and the credibility of mechanical parameter testing. In addition, the calculation of overburden pressure parameters based on wellbore damage information not only improves the accuracy of stress input data, but also enhances the ability to characterize the vertical stress field of the formation, providing important support for the construction of a more reasonable ground stress model. Overall, the solution shows good adaptability and engineering application value in complex geological environments.

[0064] Preferably, step S2 includes the following steps:

[0065] Step S21: Perform physical size inspection and standard shaping on the core sample to obtain the sample to be tested;

[0066] Step S22: placing ultrasonic transducers at both ends of the test sample to measure the longitudinal wave velocity and the shear wave velocity, respectively, and calculating the Poisson's ratio and Young's modulus;

[0067] Step S23: performing a standard uniaxial compression test on the test sample, gradually increasing the pressure until the test sample fails, and recording the maximum axial stress value of the test sample at failure, which is the uniaxial compressive strength value;

[0068] Step S24: applying a radial compression load to the core cylindrical sample to be tested, and calculating the tensile strength value according to the fracture load and size of the sample to be tested;

[0069] Step S25: Record the Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value as rock mechanics parameters.

[0070] In the embodiments of the present invention, the mechanical testing module first uses an electronic vernier caliper to detect the dimensions of various core samples with a measurement accuracy of 0.01 mm, ensuring that the diameter error of the cylindrical core samples does not exceed 0.5 mm and the end face parallelism deviation does not exceed 0.02 mm. Subsequently, a SHM-200 type rock cutting machine is used to cut the core samples into standard cylinders, with the length-diameter ratio strictly controlled within the range of 2.0 ± 0.05, that is, the length is 125 ± 1 mm and the diameter is 62.5 ± 0.5 mm. After cutting, the end faces are finely ground with a grindstone to ensure that the surface roughness of the end faces is less than 0.02 mm, and the surface rock powder is thoroughly removed with compressed air. The processed samples are dried for 24 hours until they reach a constant weight state to prepare the samples to be tested. UPV-1500 type ultrasonic transducers are respectively installed at both ends of the samples to be tested. The frequency of the transmitting transducer is 100 kHz, and the sensitivity of the receiving transducer is -85 dB. The coupling agent is evenly applied to the contact surface between the transducer and the sample, and a fixed pressure of 10 N is applied to ensure good contact. Ultrasonic waves are emitted and the wave propagation time is recorded. , calculation formula to obtain the longitudinal wave velocity, where is the sample length. Subsequently, the polarization direction of the transducer is adjusted to measure the shear wave velocity . Based on the measured wave velocity values, through the formula the Poisson's ratio is calculated , and through the formula the Young's modulus is calculated , where is the core density. The samples to be tested are placed in an RTR-2000 type rock triaxial testing machine. The machine pressure range is 2000 kN, and the loading accuracy is ±0.5%. The uniaxial compression test is strictly carried out in accordance with the ISRM standard. After applying an axial pre-pressure of 2 MPa, the displacement sensor is reset to zero, and then the axial pressure is gradually applied at a constant loading rate of 0.5 MPa / s until the sample fails. The stress-strain curve is recorded throughout the process to determine the maximum axial stress value when the sample fails , which is the uniaxial compressive strength value. The RDT-300 type Brazilian splitting testing machine is used to perform radial compression on the samples to be tested. The pressure range of the testing machine is 300 kN, and the radial loading rate is controlled at 200 N / s. The sample is split along the cylindrical axis. According to the fracture load and the sample diameter and length , through the calculation formula the tensile strength value is calculated ; the measured Poisson's ratio (dimensionless, value range 0.15 - 0.45), Young's modulus (unit GPa, value range 10 - 80 GPa), uniaxial compressive strength value (Unit: MPa, range: 20-200 MPa) and tensile strength (Unit: MPa, value range: 2-20 MPa) constitute a complete rock mechanics parameter set. Each parameter is the average value of three samples, and the standard deviation is controlled within 5%. These parameters are entered into the data processing system and transmitted to the stress difference measurement module.

[0071] The present invention ensures the scientificity, accuracy and engineering applicability of rock mechanical parameter acquisition through standardized core sample preparation and systematic mechanical testing process, and has significant beneficial effects. First, physical dimension inspection and standard shaping effectively improve the geometric consistency and experimental repeatability of the sample, avoiding data deviation caused by sample irregularity. The ultrasonic testing link introduces non-destructive means to accurately obtain the longitudinal and transverse wave velocities, and then calculates the Poisson's ratio and Young's modulus, which not only improves the parameter testing efficiency, but also ensures the in-situ representativeness and accuracy of the mechanical parameters. The combination of uniaxial compression and radial fracturing experiments realizes the comprehensive determination of compressive and tensile strength, and provides key constitutive parameter support for the inversion of ground stress state. This multi-index linkage mechanical property acquisition system enhances the comprehensiveness and depth of rock mechanical behavior characterization, provides a more solid and reliable physical foundation for stress modeling and boundary constraints, and is particularly suitable for high-precision ground stress analysis under complex geological structures and deep formation conditions.

[0072] Preferably, step S3 includes the following steps:

[0073] Step S31: Marking a smooth core sample from a plurality of core samples based on the damage type, and measuring the smooth core sample cross section along the circumference every 15° to 30° using a laser displacement meter;

[0074] Step S32: recording the original diameter distribution data of the smooth core sample under no external force conditions;

[0075] Step S33: applying axial pressure to the smooth core sample, wherein the axial pressure is a unidirectional compression, a static load, and a loading method simulating a deep stress state;

[0076] Step S34: measuring the diameter change of the smooth core sample at the same angle again under the state of applying axial pressure to obtain deformation radial dimension data;

[0077] Step S35: Based on the original diameter distribution data and the deformed radial dimension data, the maximum difference direction and the minimum difference direction of the diameter after loading are identified, and the difference between the maximum and minimum stresses is calculated. The specific calculation process is as follows:

[0078] ;

[0079] in is the difference between the maximum and minimum stresses, is the maximum stress value, is the minimum stress value, is the Young's modulus, is the Poisson's ratio, is the maximum diameter after loading, is the minimum diameter after loading, is the original diameter distribution data.

[0080] In the embodiments of the present invention, cylindrical core samples with intact surfaces, no microcracks, and a diameter error of less than 0.02 mm are selected from various core samples that have undergone failure type analysis as smooth core samples. With the help of a KEYENCE LK-G5000 series laser displacement meter, 24 points are measured at fixed intervals of 20° along the circumferential direction on the cross-section of the smooth core sample, and the laser scanning accuracy is controlled within 1 micron. The smooth core sample is placed in a constant temperature environment (25 ± 0.5 °C), and the original diameter values of each measurement point under the condition of no external force are recorded to generate a complete original diameter distribution data table, including the measurement angle and the corresponding diameter value (unit: mm, accurate to 0.001 mm). The smooth core sample is installed on the loading table of an MTS815 hydraulic servo loading system, the axial loading pressure is set to 10 MPa, and a unidirectional compressive static load is applied at a constant rate of 0.2 MPa / min for a duration of 60 minutes to ensure that the core sample is within the elastic deformation range. Keeping the axial pressure unchanged, the diameter values at the same 24 angular positions are measured again using the same laser displacement meter, and the deformed radial dimension data is recorded to form a radial dimension distribution table under the loading state. By comparing the original diameter distribution data with the deformed radial dimension data, the diameter change amount at each angular position is calculated, and the change amount distribution curve is plotted using a polar coordinate diagram to determine the angular direction (denoted as the maximum deformation direction ) at the location with the largest change amount and the angular direction (denoted as the minimum deformation direction ), and the corresponding maximum diameter value (the maximum diameter after deformation, unit: mm) and the minimum diameter value (the minimum diameter after deformation, unit: mm) are extracted. Combining the Young's modulus (unit: GPa, which needs to be converted to MPa) and the Poisson's ratio (dimensionless), substituting into the formula to calculate the difference between the maximum and minimum stresses (unit: MPa), where is the average original diameter (unit: mm). During the calculation process, the unit consistency is ensured, and finally, the difference between the maximum and minimum stresses accurate to 0.1 MPa is obtained. This difference directly reflects the magnitude of the principal stress difference in the surrounding rock stress field.

[0081] The present invention effectively improves the acquisition accuracy and physical interpretability of the maximum and minimum principal stress differences through high-precision deformation measurement of smooth core samples under different loading states, and has prominent beneficial effects. First, smooth core samples are screened based on the failure type, ensuring the integrity and isotropy of the sample structure, and providing an ideal physical basis for subsequent measurements. A laser displacement meter is used to conduct detailed measurements on multiple angles of the sample circumference, which not only improves the spatial resolution of the radial deformation data, but also significantly enhances the sensitivity and accuracy of stress difference derivation. By comparing the radial size changes before and after loading, the stress response differences of materials in different directions can be intuitively reflected, thereby accurately identifying the maximum and minimum deformation directions, and then deriving the principal stress difference. This method not only avoids the high dependence of traditional pressure measurement methods on complex boundary conditions, but also bypasses the error interference caused by formation heterogeneity, and is particularly suitable for fine stress inversion in deep and complex stress environments. Generally, this scheme has the advantages of strong non-destructiveness, high measurement accuracy, and strong result interpretability, and is an important technical means for realizing quantitative evaluation of in-situ stress.

[0082] Preferably, constructing the stress polygon model based on the overburden pressure parameter in step S4 includes:

[0083] Collecting the pore pressure of the measurement section by repeating the downhole tester;

[0084] Constructing the stress polygon model, and the specific construction process is:

[0085] ;

[0086] Among them, is the friction coefficient, with a value range between 0.6 and 1, dimensionless, is the overburden pressure parameter, equal to the vertical stress, is the maximum principal stress, is the minimum principal stress, is the pore pressure.

[0087] In the embodiment of the present invention, first, the RFT repeated downhole tester conducts in-situ pore pressure measurement in the measurement section. The sensitivity of the pressure sensor of the tester is 0.01 MPa, and pore pressure data of at least 20 depth points are collected at intervals of every 5 meters. After the measurement is completed, the arithmetic mean value is taken as the representative pore pressure of this measurement section accurate to 0.1 MPa; subsequently, combined with the overburden pressure parameter , and the friction sliding equilibrium principle in Anderson's fault theory, three inequality relations of the stress polygon are established:

[0088] ;

[0089] Among them, the friction coefficient It is determined according to the lithological characteristics of the measurement section, taking the value of 0.65 in the sandstone section, 0.85 in the mudstone section, and 0.75 in the limestone section; then a stress polygon graph is constructed in the two-dimensional rectangular coordinate system, with the horizontal axis representing the minimum horizontal principal stress , and the vertical axis representing the maximum horizontal principal stress . The three inequalities are respectively transformed into three boundary lines on the coordinate plane, and the closed area enclosed by the three boundary lines and the straight line is taken as the stress polygon constraint area, and this area represents all the theoretical possible value ranges of the maximum principal stress and the minimum principal stress under the condition of frictional sliding equilibrium; for the example verification at a specific depth of 2500 meters, the overburden pressure parameter = 62.3 MPa, the pore pressure = 25.7 MPa, when taking = 0.75, the vertex coordinates of the stress polygon area are (30.5 MPa, 48.9 MPa), (30.5 MPa, 86.2 MPa), (48.9 MPa, 86.2 MPa), (48.9 MPa, 48.9 MPa), forming a trapezoidal stress polygon area; finally, the position of the overburden pressure value at the current depth is marked on the stress polygon graph, and the stress polygon area is meshed, with the mesh size of 0.5 MPa × 0.5 MPa. The completed stress polygon model data is stored in the relational array, including the numerical pairs of the maximum principal stress and the minimum principal stress corresponding to each grid point.

[0090] Through the method of constructing a stress polygon model based on the overburden pressure parameter, the present invention can effectively improve the accuracy and operability of the in-situ stress state inversion. First, the bottomhole tester repeatedly collects the pore pressure of the measurement section, providing more real and reliable input data for the model and avoiding the problems of insufficient or large deviation of pore pressure data in the traditional method. The construction of the stress polygon model uses the friction coefficient as the adjustment parameter, which can adjust the relationship between stresses according to the actual friction characteristics of the formation, enhancing the adaptability and accuracy of the model. Through the setting of constraint conditions, the model can systematically balance the interaction between the maximum principal stress, the minimum principal stress, and the vertical stress, thereby providing a more reasonable stress distribution prediction. This method is particularly suitable for stress analysis under complex geological conditions because it can comprehensively consider important geological factors such as the overburden pressure and pore pressure, reducing the deviation caused by ignoring these factors in the traditional model, and has strong engineering application value. Especially in the stress analysis of deep formations and complex structural areas, it can achieve a higher-precision stress state inversion.

[0091] Preferably, the wellbore failure model constructed based on the failure type in step S4 includes:

[0092] Construct a wellbore failure model. The specific construction process is as follows:

[0093] ;

[0094] Among them, are the effective stresses around the wellbore in the cylindrical coordinate system respectively, is the variable of the in-situ stress field in the rectangular coordinate system, is the drilling fluid pressure, is the pore pressure, is the Poisson's ratio, is the wellbore failure angle;

[0095] Select the corresponding failure criterion based on the failure type;

[0096] If the failure type is sloughing, select the shear failure criterion: ;

[0097] If the failure type is induced tensile fracture, select the tensile failure criterion: ;

[0098] Among them is the minimum effective principal stress, is the maximum effective principal stress, is the uniaxial compressive strength, is the internal friction angle, is the tensile strength value;

[0099] According to the effective stresses around the wellbore in the cylindrical coordinate system, combined with the drilling fluid pressure and pore pressure, calculate the circumferential and radial stresses of the wellbore, and judge whether they exceed the core failure strength range.

[0100] In the embodiment of the present invention, when the sloughing failure type is identified, the system uses the conversion formula from the rectangular coordinate system of a regular hexahedron to the cylindrical coordinate system to calculate the distribution of the effective stresses around the wellbore. Specifically,

[0101] ;

[0102] For the sloughing failure type, apply the shear failure criterion , substitute the Poisson's ratio and Young's modulus measured by the DCDA experiment into the formula, calculate the circumferential stress value of the wellbore and compare it with the uniaxial compressive strength value to determine whether shear failure occurs; for the induced tensile fracture failure type, apply the tensile failure criterion , substitute the Poisson's ratio and Young's modulus measured by the DCDA experiment into the formula, calculate the minimum effective principal stress of the wellbore and compare it with the tensile strength value to determine whether tensile failure occurs; subsequently, the system combines the wellbore effective stress calculation results with the stress polygon model constraint conditions to draw a closed area in the two-dimensional coordinate system, where the horizontal axis represents the minimum principal stress Numerical range, with the maximum principal stress represented on the vertical axis Numerical range; when the failure type is caving, based on the radial effective stress , circumferential effective stress , axial effective stress and tangential stress Based on the calculation results of , circumferential effective stress , axial effective stress and tangential stress When the failure type is induced tensile crack, superimpose the stress conditions restricted by the tensile failure criterion onto the stress polygon constraint region; for the additional boundary lines formed after superposition, perform an intersection region extraction operation to obtain the multi-source coupled constrained principal stress interval that simultaneously satisfies the stress polygon constraint and the wellbore failure model constraint; each stress value combination in this interval represents a set of potential in-situ stress solutions, which are used for subsequent overlap determination with the difference between the maximum and minimum stresses, and finally determine the exact numerical ranges of the maximum principal stress and minimum principal stress .

[0103] The method for constructing a wellbore failure model based on the failure type in the present invention can effectively improve the accuracy and reliability of wellbore stress analysis, and is particularly suitable for stress assessment under complex formation conditions. By calculating the effective stress around the wellbore in the cylindrical coordinate system and combining the drilling fluid pressure and pore pressure, the model provides a comprehensive characterization of the wellbore failure state and can accurately identify the stress changes in the wellbore due to different failure types (such as caving or induced tensile cracks). Using the shear failure criterion and the tensile failure criterion, effectively combining the actual failure types, ensures the scientific nature of the failure mechanism and the adaptability of the model. In addition, by systematically calculating the circumferential and radial stresses of the wellbore and comparing them with the failure strength range of the core, the model can predict in advance whether the wellbore will fail, greatly enhancing the practicality and forward-looking nature of wellbore stability analysis. This method can accurately consider the stress distribution in different directions and its correlation with the mechanical properties of the rock mass, which helps to optimize the drilling operation and ensure the safety of the wellbore in a complex geological environment, thereby improving the success rate of the drilling operation and reducing the operation risk.

[0104] Preferably, in step S4, a two-dimensional constraint system is established using the stress polygon model and the wellbore failure model, and the multi-source coupled constrained principal stress includes:

[0105] The maximum principal stress that meets the constraint conditions of the stress polygon model The numerical range is plotted as a closed region in a two-dimensional coordinate system to obtain a stress polygon constraint region, where the horizontal axis is the minimum principal stress , and the vertical axis is the maximum principal stress ;

[0106] Select the corresponding wellbore failure model based on the failure type for regional superposition;

[0107] If the failure type is caving, superimpose the wellbore failure model restricted by the shear failure criterion onto the stress polygon constraint region;

[0108] If the failure type is induced tensile fracture, superimpose the wellbore failure model restricted by the tensile failure criterion onto the stress polygon constraint region;

[0109] After superposition, an additional boundary line is formed to obtain a two-dimensional constraint region;

[0110] Conduct an analysis of the superimposed region of the two-dimensional constraint region, extract the intersection region, and obtain the multi-source coupled constraint principal stress interval.

[0111] In the embodiment of the present invention, first, based on the overburden pressure parameter , combined with the pore pressure , after repeating the measurement three times at the same depth section by a pressure penetration tester and taking the average value, ensure that the pressure data error does not exceed ±0.05 MPa, and then construct a two-dimensional stress polygon boundary using the following mathematical expression according to the range of the formation friction coefficient (the value ranges from 0.6 to 1.0, and the step size does not exceed 0.05): , where is the maximum principal stress, is the minimum principal stress. This set of inequalities forms a continuous boundary curve on a two-dimensional coordinate graph by setting as the vertical axis and as the horizontal axis, forming a closed region; subsequently, call the shear failure boundary (when the failure type is caving) or tensile failure boundary (when the failure type is induced tensile fracture) output by the wellbore failure model, and superimpose the boundary line data onto the stress polygon constraint region at the same coordinate axis ratio. The coordinate system unit is MPa, and the accuracy is controlled to 0.1 MPa; taking caving as an example, the shear failure boundary output by the wellbore failure model is calculated by the shear strength envelope expression , where ranges from 28° to 35°; then generate that satisfies this expression at a step size of every 0.1 MPaThe point set is mapped to a two-dimensional plane; the overlapping part of the boundaries of the two regions is the two-dimensional constraint region. By using the coordinate intersection extraction tool, the corresponding data points of the stress polygon constraint region and the wellbore failure boundary are compared one by one, and only the coordinate points within the numerical intersection range are retained to form a closed region, obtaining the maximum principal stress and minimum principal stress limit intervals under the combined action of the formation friction coefficient limit and the rock failure criterion. This interval is used as the preliminary principal stress result before the subsequent strength constitutive constraint.

[0112] The present invention uses a stress polygon model and a wellbore failure model to establish a two-dimensional constraint system and implements a method for multi-source coupled constraint of principal stresses, significantly improving the accuracy and reliability of in-situ stress analysis, especially having outstanding application value in complex geological environments. First, combining the constraint conditions of the stress polygon model and the wellbore failure model can comprehensively cover the numerical ranges of the maximum principal stress and the minimum principal stress, which is presented as a closed region in a two-dimensional coordinate system, clearly defining the stress change range and enhancing the visualization and operability of the stress state. Then, through the differential treatment of the failure types, the wellbore failure models corresponding to the shear failure criterion and the tensile failure criterion are respectively superimposed on the stress polygon constraint region to form a more accurate two-dimensional constraint region. This process not only ensures the tight coupling of the wellbore failure strength and the stress state, but also effectively limits the change range of the principal stresses through the additional boundary lines after superposition, avoiding stress solutions that do not conform to physical and mechanical properties. By performing intersection analysis on the superimposed region, the principal stress interval of multi-source coupled constraint is extracted, providing a result interval with multiple verifications for stress inversion. Overall, this method can accurately capture the stress state in deep and complex formations, provide scientific and reliable principal stress solutions, and provide strong technical support for drilling operations, wellbore stability analysis, and other engineering decisions.

[0113] Preferably, step S5 includes:

[0114] Determine the constraint parameters based on the failure type;

[0115] If the failure type is caving, after judging the core shear limit condition for the multi-source coupled constraint principal stress interval obtained by using the shear failure criterion, the uniaxial compressive strength value is used as the failure constraint parameter;

[0116] The specific judgment of the core shear limit condition is to substitute the shear failure formula point by point based on the rock mechanics parameters and the multi-source coupled constraint principal stress interval obtained by using the shear failure criterion, form the graphical distribution of the feasible solution region and the infeasible solution region, and remove the infeasible solution region;

[0117] If the failure type is induced tensile fracture, after performing thermal stress disturbance analysis on the multi-source coupled constraint principal stress interval obtained by using the tensile failure criterion, the tensile strength value is used as the failure constraint parameter;

[0118] Specifically, the thermal stress disturbance analysis is as follows: when the core cools down, the additional tensile stress generated on the wellbore wall of the measurement section is calculated based on the Poisson's ratio and Young's modulus, and the additional tensile stress is used to correct the multi-source coupling constrained principal stress range obtained by using the tensile failure criterion.

[0119] The constraint parameters are applied to the multi-source coupling constrained principal stress range to obtain the strength constitutive constrained principal stress range.

[0120] In the embodiment of the present invention, based on the obtained multi-source coupling constrained principal stress range, the stress constraint path is first determined according to the failure type. If the failure type is caving, the shear failure criterion is used to judge the shear limit condition of the multi-source coupling constrained principal stress range. The specific operation is as follows: taking the uniaxial compressive strength value (unit: MPa, range limited between 40 MPa and 120 MPa) and the internal friction angle (range: 28° to 35°) as inputs, using the Mohr-Coulomb failure condition expression to conduct point-by-point inspection on all principal stress value pairs in the principal stress range. In the two-dimensional coordinate graph, all data points that do not meet this failure condition are removed, and only the principal stress value combinations that meet the shear limit are retained to form the strength constraint region; if the failure type is induced tensile cracks, the maximum tensile stress failure criterion is used, and the thermal stress disturbance analysis is combined with the tensile strength value (unit: MPa, range: 2 MPa to 8 MPa). First, the additional tensile stress is calculated using the measured temperature drop of the wellbore wall (unit: °C, measured by a temperature cable logging tool, control accuracy: ±0.1 °C). The additional tensile stress is added to the minimum principal stress direction, and after point-by-point superposition and correction in the multi-source coupling constrained principal stress range, it is judged whether it is less than the tensile strength value. If the minimum principal stress plus the additional tensile stress is still less than the tensile strength value, then this stress pair is regarded as a failure state and excluded. Finally, all principal stress value pairs that meet the strength boundary are retained to form the strength constitutive constrained principal stress range.

[0121] The method of the present invention for determining constraint parameters based on the failure type and further correcting the multi-source coupled constraint principal stress interval can significantly improve the accuracy and engineering applicability of stress analysis. First, by selecting appropriate constraint parameters according to the failure type, such as using the uniaxial compressive strength value as the constraint parameter during caving, and judging and eliminating the infeasible solution region through the core shear limit condition, the matching between the stress state and the actual material strength is ensured. The limit condition judgment under the shear failure criterion can effectively avoid stress solutions that do not conform to the physical strength, thereby improving the reliability of the results. For the failure type that induces tensile cracks, the multi-source coupled constraint principal stress interval under the tensile failure criterion is corrected through thermal stress disturbance analysis, considering the influence of temperature change on stress, ensuring a more comprehensive and detailed stress analysis of the wellbore. The correction of the additional tensile stress enables the stress interval to more accurately reflect the stress changes in the actual environment and improves the prediction accuracy of the failure risk. This process combines rock mechanics parameters with the actual formation state, and through fine mechanical model correction, it can provide more accurate prediction and more practical technical support for the wellbore stability in complex formation environments, thereby enhancing the safety and efficiency of drilling operations.

[0122] Preferably, step S6 includes:

[0123] Express the difference between the maximum and minimum stresses as a function relationship line to obtain a stress difference constraint line with a slope of 1, that is ;

[0124] Construct a two-dimensional coordinate system, with the horizontal axis representing the minimum stress value , and the vertical axis representing the maximum stress value ;

[0125] Plot the stress difference constraint line, the multi-source coupled constraint principal stress interval, and the strength constitutive constraint principal stress interval in the two-dimensional coordinate system to obtain a caving / induced tensile crack topology visualization diagram;

[0126] Based on the caving / induced tensile crack topology visualization diagram, identify the intersection points of the stress difference constraint line and the constraint graph to obtain the numerical ranges of the maximum principal stress and the minimum principal stress;

[0127] If the intersection point is an interval, the intersection point forms a banded region; if the intersection point is a single point, the point is the exact stress solution; otherwise, it is a set of numerical pairs that satisfy , and at the same time satisfy the boundary conditions of the polygon and the strength limit region.

[0128] In the embodiment of the present invention, first, express the difference between the maximum and minimum stresses as a linear function relationship , where is the maximum principal stress, is the minimum principal stress. In a two-dimensional coordinate system, with as the horizontal axis and as the vertical axis, a stress difference constraint line with a slope of 1 and a vertical intercept of is plotted. The coordinate axes of this coordinate system are calibrated by a millimeter-level plotter, and the coordinate scale range is set from 0 MPa to 150 MPa with a step size of 1 MPa. Then, the multi-source coupling constraint principal stress interval and the strength constitutive constraint principal stress interval are respectively plotted in the same coordinate system. Both parts of the data are pairs of principal stress values stored in tabular form . Each pair of principal stress points is marked with a different color, representing the results of multi-source coupling constraint and strength constraint respectively. Then, the stress difference constraint line is introduced into the plotting area, and the intersection comparison is made between this line and the point sets of the two principal stress intervals. All data points falling on the line or within the line segment banded interval are screened to form the overlapping area of the stress difference constraint line with a slope of 1 and the principal stress interval. The boundary of this area is determined by the intersection points. If a closed interval is formed at the intersection point, then this interval is the numerical banded range of the maximum principal stress and the minimum principal stress. If there is only a single point falling at the intersection of the three types of constraint graphs, then this point is the exact stress solution. If there are multiple discontinuous intersection points, then all coordinate pairs that satisfy the stress difference relationship and are simultaneously within the aforementioned two principal stress intervals are extracted in sequence to form a set of stress solutions that meet the conditions. The final result is saved in the drawing for subsequent interpretation and verification.

[0129] By expressing the difference between the maximum and minimum stresses as a functional relationship line and plotting it in a two-dimensional coordinate system, the present invention can clearly show the mutual relationship between the stress difference constraint and the multi-source coupling constraint and the strength constitutive constraint. This method can effectively visualize the stress state of caving and induced tensile fractures, help visually identify the intersection points of the stress difference constraint line and other constraint regions, and thus accurately determine the numerical range of the maximum principal stress and the minimum principal stress. When the intersection point is a banded area, it indicates that there is a certain range of stress values, which helps to understand the uncertainty of stress. When the intersection point is a single point, it provides an exact stress solution, which helps to further optimize engineering decisions. With the help of these intersection points, it can be ensured that the principal stress solution simultaneously satisfies the boundary conditions of the stress polygon and the strength limit region, thereby obtaining a more accurate and reliable stress analysis result. By using this topological visualization graph, not only can the stress solution be systematically constrained, but also the prediction ability of the principal stress state in deep formations and complex geological environments can be improved, providing strong technical support for wellbore stability analysis, drilling operation optimization, and engineering safety.

[0130] Preferably, the present invention also provides a core three-dimensional in-situ stress measurement system based on multi-source data for performing the above-mentioned core three-dimensional in-situ stress measurement method based on multi-source data. The core three-dimensional in-situ stress measurement system based on multi-source data includes:

[0131] The damage recognition module is used to obtain wellbore damage information and identify the damage type in the wellbore damage information; select a variety of core samples based on the wellbore damage information, and determine the overburden pressure parameter based on the variety of core samples;

[0132] The mechanical test module is used to perform rock mechanics experiments on the core samples to generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value;

[0133] The stress difference measurement module is used to mark smooth core samples from a variety of core samples based on the damage type, and perform core diameter deformation analysis experiments on the smooth core samples using Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses;

[0134] The stress modeling module is used to construct a stress polygon model based on the overburden pressure parameter; construct a wellbore damage model based on the damage type; establish a two-dimensional constraint system using the stress polygon model and the wellbore damage model, and execute multi-source coupled constraint principal stresses;

[0135] The range constraint module is used to execute strength constitutive constraint principal stresses using the uniaxial compressive strength value / tensile strength value based on the damage type;

[0136] The intersection inversion module is used to perform topological visualization on the multi-source coupled constraint principal stresses and the strength constitutive constraint principal stresses, and perform regional overlap determination on the difference between the maximum and minimum stresses and the topological visualization results to determine the numerical ranges of the maximum principal stress and the minimum principal stress.

[0137] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is not limited by the above description. Therefore, it is intended to include all changes falling within the meaning and scope of the equivalent elements of the application documents within the present invention.

[0138] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A three-dimensional in-situ stress measurement method for core based on multi-source data, characterized in that It includes the following steps: Step S1: Obtain the wellbore failure information and identify the failure types in the wellbore failure information; Select multiple core samples based on the wellbore failure information and determine the overburden pressure parameters based on the multiple core samples; Step S2: Conduct rock mechanics experiments on the core samples to generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value; Step S3: Mark smooth core samples from various core samples based on the failure type, and conduct core diameter deformation analysis experiments on the smooth core samples using Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses; Step S4: Construct a stress polygon model based on the overburden pressure parameters; Construct a wellbore failure model based on the failure type; Use the stress polygon model and the wellbore failure model to plan a two-dimensional constraint region and execute multi-source coupled constrained principal stresses; Step S5: Execute strength constitutive constrained principal stresses using the uniaxial compressive strength value or the tensile strength value based on the failure type; Step S6: Topologically visualize the multi-source coupled constrained principal stresses and the strength constitutive constrained principal stresses, and perform regional overlap determination on the difference between the maximum and minimum stresses and the topological visualization results to determine the numerical ranges of the maximum principal stress and the minimum principal stress.

2. The method for three-dimensional in-situ stress measurement of core based on multi-source data according to claim 1, wherein Step S1 includes the following steps: Step S11: Collect wellbore image data of the measurement section through a borehole micro-resistivity imaging logging tool; Step S12: Remove noise and enhance the image of the measurement section wellbore image data, and extract the wellbore failure information; Step S13: Identify the failure types based on the wellbore failure information, where the failure types include caving and induced tensile fractures; Step S14: Identify the core distribution law based on the wellbore failure information and select various core samples based on the core distribution law; Step S15: Calculate the overburden pressure parameters of various core samples based on the wellbore failure information. The specific calculation process is as follows: ， Among them, is the overburden pressure parameter, is the depth of the core density at that point, is the acceleration due to gravity, is the core depth.

3. The method for measuring the three-dimensional in-situ stress of a core based on multi-source data according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Conduct physical size inspection and standard shaping on the core samples to obtain the samples to be experimented; Step S22: Deploy ultrasonic transducers at both ends of the samples to be experimented, measure the longitudinal wave velocity and the transverse wave velocity respectively, and calculate Poisson's ratio and Young's modulus; ​ ​ ​ 4. The method for three-dimensional in-situ stress measurement of core based on multi-source data according to claim 1, characterized in that, ​ ​ ​ ​ Step S34: Measure the diameter change of the smooth core sample at the same angle again under the state of axial pressure applied, and obtain the deformed radial dimension data; Step S35: Identify the direction of the maximum difference and the minimum difference in diameter after loading based on the original diameter distribution data and the deformed radial dimension data, and calculate the difference between the maximum and minimum stresses. The specific calculation process is as follows: ； wherein is the difference between the maximum and minimum stresses, is the maximum stress value, is the minimum stress value, is the Young's modulus, is the Poisson's ratio, is the maximum diameter after loading, is the minimum diameter after loading, is the original diameter distribution data.

5. The method for three-dimensional in-situ stress measurement of core based on multi-source data according to claim 1, characterized in that In step S4, constructing the stress polygon model based on the overburden pressure parameters includes: Collect the pore pressure of the measurement section by repeating the bottom tester; Construct the stress polygon model. The specific construction process is as follows: ； Among them, is the friction coefficient, with a value range between 0.6 and 1, dimensionless, is the overburden pressure parameter, equal to the vertical stress, is the maximum principal stress, is the minimum principal stress, is the pore pressure.

6. The method for three-dimensional in-situ stress measurement of core based on multi-source data according to claim 1, characterized in that, In step S4, constructing the wellbore failure model based on the failure type includes: Construct the wellbore failure model. The specific construction process is as follows: ； Among them, are the effective stresses around the wellbore in the cylindrical coordinate system, is the variable of the in-situ stress field in the Cartesian coordinate system, is the drilling fluid pressure, is the pore pressure, is the Poisson's ratio, is the wellbore failure angle; Select the corresponding failure criterion based on the failure type; If the failure type is caving, select the shear failure criterion: ； If the failure type is induced tensile crack, select the tensile failure criterion: ; wherein is the minimum effective principal stress, is the maximum effective principal stress, is the uniaxial compressive strength, is the angle of internal friction, is the tensile strength value; According to the effective stress around the wellbore in the cylindrical coordinate system, combined with the drilling fluid pressure and the pore pressure, calculate the circumferential and radial stresses of the wellbore, and judge whether they exceed the core failure strength range.

7. The method for measuring the three-dimensional in-situ stress of a core based on multi-source data according to claim 1, wherein In step S4, establishing a two-dimensional constraint system using the stress polygon model and the wellbore failure model, and implementing multi-source coupled constraint principal stresses includes: The maximum principal stress that meets the constraint conditions of the stress polygon model and the minimum principal stress The numerical ranges of are plotted as a closed region in a two-dimensional coordinate system to obtain the stress polygon constraint region, where the horizontal axis is the minimum principal stress , and the vertical axis is the maximum principal stress ; Select the corresponding wellbore failure model based on the failure type for regional superposition; If the failure type is caving, superimpose the wellbore failure model restricted by the shear failure criterion onto the stress polygon constraint region; If the failure type is induced tensile fracture, superimpose the wellbore failure model restricted by the tensile failure criterion onto the stress polygon constraint region; After superposition, form an additional boundary line to obtain a two-dimensional constraint region; Conduct superposition region analysis on the two-dimensional constraint region, extract the intersection region, and obtain the multi-source coupled constraint principal stress interval.

8. The three-dimensional in-situ stress measurement method for core based on multi-source data according to claim 1, characterized in that Step S5 includes: Determine the constraint parameters based on the failure type; If the failure type is caving, after judging the core shear limit condition for the multi-source coupled constraint principal stress interval obtained by using the shear failure criterion, take the uniaxial compressive strength value as the failure constraint parameter; Among them, the core shear limit condition judgment is specifically as follows: Based on the rock mechanics parameters and the multi-source coupled constraint principal stress interval obtained by using the shear failure criterion, substitute into the shear failure formula point by point to form the graphical distribution of the feasible solution region and the infeasible solution region, and remove the infeasible solution region; If the failure type is induced tensile fracture, after conducting thermal stress perturbation analysis on the multi-source coupled constraint principal stress interval obtained by using the tensile failure criterion, take the tensile strength value as the failure constraint parameter; Among them, the thermal stress perturbation analysis is specifically as follows: When the core cools down, calculate the additional tensile stress generated on the wellbore wall of the measurement section based on the Poisson's ratio and the Young's modulus, and use the additional tensile stress to correct the multi-source coupled constraint principal stress interval obtained by using the tensile failure criterion; Apply the constraint parameters to the multi-source coupled constraint principal stress interval to obtain the strength constitutive constraint principal stress interval.

9. The method for three-dimensional in-situ stress measurement of core based on multi-source data according to claim 1, characterized in that, Step S6 includes: The difference between the maximum and minimum stresses is expressed as a function relationship line to obtain a stress difference constraint line with a slope of 1, that is ; Construct a two-dimensional coordinate system, where the horizontal axis represents the minimum stress value , and the vertical axis represents the maximum stress value ; Plot the stress difference constraint line, the multi-source coupled constraint principal stress interval, and the strength constitutive constraint principal stress interval in a two-dimensional coordinate system to obtain the caving / induced tensile fracture topology visualization diagram; Identify the intersection points of the stress difference constraint line and the constraint graph based on the caving / induced tensile fracture topology visualization diagram to obtain the numerical ranges of the maximum principal stress and the minimum principal stress; If the intersection point is an interval, the intersection points form a banded region; if the intersection point is a single point, this point is the exact stress solution; otherwise, it is a set of numerical pairs that satisfy and simultaneously satisfy the boundary conditions of the polygon and the strength limit region. ​ 10. A three-dimensional in-situ stress measurement system for core based on multi-source data, characterized in that, For performing the three-dimensional in-situ stress measurement method of core based on multi-source data as described in claim 1, the three-dimensional in-situ stress measurement system of core based on multi-source data includes: A failure identification module, configured to obtain wellbore failure information and identify the failure type in the wellbore failure information; select a variety of core samples based on the wellbore failure information, and determine the overburden pressure parameter based on the variety of core samples; A mechanical test module, configured to perform rock mechanics experiments on the core samples to generate rock mechanics parameters, where the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value, and tensile strength value; A stress difference measurement module, configured to mark smooth core samples from the variety of core samples based on the failure type, and perform a core diameter deformation analysis experiment on the smooth core samples using Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses; A stress modeling module, configured to construct a stress polygon model based on the overburden pressure parameter; construct a wellbore failure model based on the failure type; establish a two-dimensional constraint system using the stress polygon model and the wellbore failure model, and perform multi-source coupled constraint of the principal stress; A range constraint module, configured to perform strength constitutive constraint of the principal stress using the uniaxial compressive strength value / tensile strength value based on the failure type; An intersection inversion module, configured to perform topological visualization on the multi-source coupled constraint principal stress and the strength constitutive constraint principal stress, and perform regional overlap determination on the difference between the maximum and minimum stresses and the topological visualization result to determine the numerical range of the maximum principal stress and the minimum principal stress.

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