Rock core three-dimensional crustal stress measurement system and method based on multi-source data

Abstract

The invention relates to the technical field of crustal stress measurement, in particular to a rock core three-dimensional crustal stress measurement system and method based on multi-source data. The method comprises the following steps: acquiring well wall damage information, and identifying a damage type in the well wall damage information; multiple sections of core samples are selected based on the well wall damage information, and overburden pressure parameters are determined based on the multiple sections of core samples; a rock mechanics experiment is conducted on the rock core sample, rock mechanics parameters are generated, and the rock mechanics parameters comprise the Poisson's ratio, the Young modulus, the uniaxial compressive strength value and the tensile strength value. According to the method, the difference value of the maximum stress and the minimum stress is combined with the multi-source coupling constraint principal stress interval, the intersection points are identified through the topological visualization graph, the numerical range of the maximum principal stress and the minimum principal stress can be accurately determined, and then the information of the three-dimensional crustal stress is obtained.

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 rock formation, which is relatively easy to measure; while for the maximum and minimum principal stresses in the horizontal direction, especially the accurate determination of the maximum principal stress, there are still many challenges in technology, and it is more complex under deep formation conditions. Traditional in-situ stress measurement methods mainly include hydraulic fracturing, image logging, stress relief, core anelastic strain recovery (ASR), and seismic wave method. Although borehole methods such as hydraulic fracturing are often used for on-site measurement, the measured maximum principal stress value is greatly affected by factors such as formation heterogeneity and fracture development, with a high error; core methods such as ASR have strict requirements for sample processing accuracy and complex experiments; 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 borehole wall imaging have gradually emerged. Such methods combine the analysis of borehole wall 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, with strong practicability and adaptability. However, the existing methods still have problems such as insufficient utilization of borehole wall information, unclear determination 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: Step S1: Obtain borehole wall failure information and identify the failure types in the borehole wall failure information; select multiple core samples based on the borehole wall failure information, and determine the overburden pressure parameter 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 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; Step S4: Construct a stress polygon model based on 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; Step S5: Based on the failure type, execute strength constitutive constraint principal stresses using the uniaxial compressive strength value or the tensile strength value; 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.

[0006] 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, by fully utilizing wellbore failure information, the ability to identify the formation stress state is improved, and the problem of low utilization rate of wellbore information in traditional methods is avoided. 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, a stress polygon model and a wellbore failure model are introduced to form a two-dimensional constraint system, which is combined with the constitutive relationship of rock strength to achieve 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, not only the intuitiveness and interpretability of the stress identification process are enhanced, but also the stability and accuracy of the determination of the maximum principal stress and the minimum principal stress range are effectively improved, providing a more reliable and popularizable technical path for deep in-situ stress research.

[0007] 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: A failure identification 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 overburden pressure parameters based on the multiple 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 multiple 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 overburden pressure parameters; construct a wellbore failure model based on failure types; establish a two-dimensional constraint system using the stress polygon model and the wellbore failure model, and execute multi-source coupled constraint principal stresses; A range constraint module, configured to execute strength constitutive constraint principal stresses based on the failure type using the uniaxial compressive strength value / tensile strength value; An intersection inversion module, configured 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 ranges of the maximum principal stress and the minimum principal stress.

[0008] The present invention integrates multi-source data and multi-dimensional constraint means through modular design, 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 implementing DCDA experiments, avoiding the uncertainties of traditional methods in heterogeneous or fractured formations. The stress modeling module uses a two-dimensional constraint method to perform multi-source coupled solution of 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 strength constitutive relations to limit stress boundaries, 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Other features, objects, and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments with reference to the following drawings: Figure 1 is a schematic flow chart of the steps of a three-dimensional in-situ stress measurement method for cores based on multi-source data according to the present invention; Figure 2 is Figure 1 a detailed schematic flow chart of step S1 in Figure 3 is Figure 1 a detailed schematic flow chart of step S2 in DETAILED DESCRIPTION OF THE EMBODIMENTS

[0010] 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 part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those skilled in the art within the scope of the present invention without creative work belong to the scope of protection of the present invention.

[0011] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus repeated descriptions thereof 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.

[0012] 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.

[0013] 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 core based on multi-source data, and the method includes the following steps: 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; 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 (DCDA) 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 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 execute multi-source coupled constraint of the principal stress; Step S5: Execute strength constitutive constraint of the principal stress using the uniaxial compressive strength value / tensile strength value based on the failure type; Step S6: Topologically visualize 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 ranges of the maximum principal stress and the minimum principal stress.

[0014] In the embodiment of the present invention, referring 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: 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; In the embodiment of the present invention, first, the wellbore 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 mm. Then, the wavelet transform method is used to remove the noise from the wellbore image data, and the histogram equalization technique is adopted to enhance the image. The signal-to-noise ratio after enhancement is increased by at least 20%. Then, the gray gradient analysis is used to extract the wellbore failure characteristic information, including the failure position, shape, and azimuth angle. According to the extracted characteristic information, the failure type is identified by judging the geometric characteristics of the failure shape (if it shows irregular blocky spalling, it is judged as caving; if it shows regular parallel longitudinal lines, it is judged as induced tensile cracks). Subsequently, based on the lithology change characteristics and failure distribution law shown in the wellbore image data, at least 3 representative core samples are selected in each failure zone. The core samples have a diameter of 25.4 mm and a length of 50.8 mm, ensuring that the sampling position strictly corresponds to the failure area. Finally, the core density values on the depth profile are obtained by using the acoustic logging data , and the density measurement accuracy is controlled within ±0.05 g / cm³. Combining 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. The core density value at each depth point 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.

[0015] 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; In the embodiment of the present invention, the selected core sample is firstly subjected to a physical size inspection to ensure that the diameter deviation does not exceed ±0.5mm and the length deviation does not exceed ±1.0mm, and then subjected to a standard shaping process by a high-precision diamond cutting machine to ensure that the parallelism deviation of the two end surfaces is less than 0.02mm and the verticality deviation is less than 0.05mm, so as to form a standard cylindrical test sample; then, P-wave (longitudinal wave) and S-wave (transverse wave) ultrasonic transducers are installed at both ends of the test sample, the frequency is set to 500kHz, and an ultrasonic detector is used to transmit and receive wave signals with a sampling accuracy of 5ns, the wave propagation time is recorded, and the longitudinal wave velocity is calculated. and shear wave velocity , accurate to 10m / s, and according to the formula Calculating Poisson's ratio , accurate to 0.01, according to the formula Calculating Young's modulus , accurate to 0.1GPa; then the sample to be tested is placed in the MTS815 hydraulic servo loading system for a standard uniaxial compression test, the loading rate is controlled at 0.5MPa / s, and the axial pressure is continuously applied until the sample is macroscopically damaged, and the maximum axial stress value at the time of damage is recorded as the uniaxial compressive strength value , the measurement accuracy is controlled at ±0.5MPa; then the Brazilian splitting test method is used to place the test sample in a special fixture, apply a radial compression load, and control the loading rate to 200N / s until the sample splits along the axial direction. According to the formula Calculate tensile strength value ,in is the breaking load value (unit: N), is the sample diameter (unit: mm), is the sample length (unit: mm), and the calculation result is accurate to 0.1MPa; 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.

[0016] Step S3: marking a smooth core sample from a plurality of core samples based on the failure type, and performing a core diameter deformation analysis (DCDA) experiment on the smooth core sample using Poisson's ratio and Young's modulus to obtain a difference between the maximum and minimum stresses; In the embodiment of the present invention, firstly, according to the type of damage (caving or induced tensile cracks), core samples with a surface smoothness of For the core samples, the KEYENCE LK-G10 laser displacement meter was used to measure once every 15° along the circumferential direction on the cross-section of the smooth core samples, with a total of 24 points measured, and the measurement accuracy was controlled within the range of ±0.001 mm; subsequently, the original diameter distribution data of the smooth core samples under the condition of no external force (i.e., zero stress state) was recorded , accurate to 0.001 mm; then, the MTS816 hydraulic servo loading system was used to apply an axial pressure to the smooth core samples, the loading value was set to 20 MPa, the loading rate was controlled at 0.2 MPa / s, and it was constantly maintained for 120 seconds to ensure that the samples were fully deformed; after the loading state was stable, the laser displacement meter was used again to measure the diameter change of the smooth core samples at the same 24 angular positions to obtain the deformed radial dimension data , accurate to 0.001 mm; then, the maximum value of the diameter after loading was determined through data analysis (corresponding angle ), and the minimum value (corresponding angle ), and it was verified whether the difference between these two angles was about 90° ± 5° (verifying the anisotropic characteristics of the stress field). Subsequently, the Young's modulus value (unit: GPa) and the Poisson's ratio value were substituted into the differential deformation stress analysis (DCDA) formula: Calculate the difference between the maximum and minimum stresses (unit: MPa). During the calculation process, the unit consistency needed to be maintained, Take the average value of the 24 measured points. The ambient temperature during the whole measurement process was controlled at 23 ± 2 °C, and the laboratory relative humidity was controlled at 50% ± 10%. The calculation result was accurate to 0.1 MPa. At the same time, the azimuth angles corresponding to the maximum deformation and the minimum deformation needed to be recorded and . The entire DCDA experiment was repeated 3 times for each smooth core sample, and the arithmetic mean value was taken as the final result.

[0017] Step S4: Construct a stress polygon model based on the overburden pressure parameters; 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 execute multi-source coupled constraint principal stresses; In the embodiment of the present invention, first, the RFT repeated formation tester was used to collect pore pressure data once every 20 meters at the target measurement section. The pressure collection range was 0 - 70 MPa, and the accuracy was controlled within ±0.1 MPa. After the collected data was filtered to remove outliers, the average value was taken as the representative value; subsequently, based on the overburden pressure parameters , combined with the friction coefficient with a value of 0.75, substitute into three groups of inequalities: ; Construct a stress polygon model and calculate The value is approximately 3.1. Solve the inequality group to obtain the preliminary numerical range of the maximum principal stress and the minimum principal stress ; Then, based on the failure type, construct a wellbore failure model. The specific operation is as follows: Record the drilling fluid pressure (measured using a drilling fluid pressure gauge with an accuracy of ±0.5 MPa), and substitute the expression of the effective stress around the wellbore in the cylindrical coordinate system: ; into the calculation; When the failure type is caving, apply the shear failure criterion , the internal friction angle is taken as 30°, is the uniaxial compressive strength value; When the failure type is induced tensile cracks, apply the tensile failure criterion , is the tensile strength value; Then, establish a two-dimensional rectangular coordinate system in the MATLAB R2023a environment. The horizontal axis represents the minimum principal stress (unit: MPa), and the vertical axis represents the maximum principal stress (unit: MPa). Plot the constraint conditions of the stress polygon model as a closed region (stress polygon constraint region), plot the constraint conditions of the wellbore failure model as a boundary curve, perform grid processing after superimposing the two graphs (grid density 0.1 MPa×0.1 MPa), extract the point set of the intersection region that satisfies both constraint conditions, and obtain the multi-source coupled constraint principal stress interval. The interval boundary is accurate to 0.1 MPa; During this process, substitute the measured wellbore failure angle (obtained through wellbore image analysis in step S1) into the calculation, and take the wellbore radius as the standard size of 83.3 mm to finally obtain the multi-source coupled constraint principal stress interval.

[0018] Step S5: Use the uniaxial compressive strength value / tensile strength value based on the failure type to perform strength constitutive constraint on the principal stress; In the embodiment of the present invention, first, judge the failure type through the wellbore failure information obtained by the failure recognition module. When the failure type is caving, apply the uniaxial compressive strength value measured by the mechanical testing module to the shear failure criterion, that is, the calculation formula , where is the core internal friction angle, and the value range is from 25° to 35°. Different core types take different fixed values; Substitute each point in the multi-source coupled constraint principal stress interval into this formula for verification. When , combination satisfies When the conditions are met, mark this point as a feasible solution; otherwise, mark it as an infeasible solution, thus forming the distribution of the feasible solution region and the infeasible solution region. Subsequently, eliminate the infeasible solution region to obtain the interval of the principal stress of the strength constitutive constraint that satisfies the core shear limit condition. When the failure type is induced tensile cracks, the system conducts a thermal stress perturbation analysis to calculate the additional tensile stress value generated during the cooling process. The calculation formula is , where is the coefficient of thermal expansion, and its value range is , 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 interval to obtain a more accurate interval of the principal stress of the strength constitutive constraint. The system transmits the corrected interval of the principal stress of the strength constitutive constraint to the intersection inversion module for regional overlap determination with the difference between the maximum and minimum stresses.

[0019] Step S6: Topologically visualize the multi-source coupled constraint principal stress and the principal stress of the strength constitutive constraint, and conduct a regional overlap determination between 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] In the embodiment of the present invention, the intersection inversion module first converts the difference between the maximum and minimum stresses obtained by the stress difference measurement module through the DCDA experiment into a stress difference constraint line, and the expression is , where is the maximum stress value, is the minimum stress value. This constraint line presents 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 , and its value range is 10 MPa to 100 MPa, and defines the ordinate as the maximum principal stress , and its value range is 20 MPa to 150 MPa. Then, plot the multi-source coupled constraint principal stress interval (represented as a closed polygon region in the two-dimensional coordinate system) and the principal stress interval of the strength constitutive constraint (represented as a further restriction on the polygon region) in this two-dimensional coordinate system, and at the same time plot the stress difference constraint line Overlay them on the same coordinate system to form a complete topological visualization map of caving / induced tensile fractures; the intersection inversion module identifies the exact intersection coordinates of the stress difference constraint line and the boundary of the constraint region through numerical calculation. When the intersection is 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 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 2,500 meters, the topological visualization analysis results obtained by this method show that the minimum principal stress is in the numerical range of 45.7 MPa to 52.3 MPa, and the maximum principal stress is in the 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, thus determining the complete three-dimensional in-situ stress state at this depth.

[0021] 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 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 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, 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 the determination of the maximum principal stress and minimum principal stress ranges, providing a more reliable and popularizable technical path for deep in-situ stress research.

[0022] Preferably, step S1 includes the following steps: Step S11: Collect the 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: , where, is the overburden pressure parameter, is the depth of the core at the location, is the acceleration due to gravity, is the core depth.

[0023] In the embodiment of the present invention, the failure identification module uses a STAR-II type borehole resistivity imaging logging tool. The logging tool is equipped with 8 microelectrode arms, and each arm carries 12 microelectrodes, with a total of 96 measurement points. It performs a 360° omnidirectional scan on the measurement section in the well at a uniform lifting rate of 2 cm / s. The sampling interval is 5 mm, the radial measurement accuracy of the electrode is 0.1 mm, and the azimuth measurement accuracy is 2°. High-resolution wellbore image data is obtained; the collected wellbore image data is digitally filtered. The Gaussian filter is used to eliminate random noise, and the filter radius is set to 3 pixels. Subsequently, image enhancement is performed through histogram equalization, and the enhanced contrast parameter is set to 1.5. The wellbore failure information, including the position of the fracture zone, fracture width, fracture depth, and azimuth angle, is extracted through the FMI image processing workstation to form a wellbore failure feature data set; the failure type is identified based on the wellbore failure feature data set. When the wellbore shows a symmetric fan-shaped failure area and the azimuth is consistent with the direction of the minimum horizontal principal stress, it is determined as caving. When the wellbore 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 failure feature parameters are recorded; the core sampling depth and position are determined according to the wellbore failure information. Priority is given to selecting sections with obvious failure phenomena and uniform lithology. At least 5 different lithology core samples, 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, ensuring that the length-diameter ratio is 2:1. The core sampling depth, lithology, color, density, etc. are 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. The continuous integral is discretized into by the trapezoidal integration method. In the formula is the The thickness of the layer, the integration step length is set to 5 m, and the overburden pressure parameter is finally calculated , with the unit of MPa.

[0024] Through the high-precision image acquisition and intelligent analysis process, the present invention effectively improves the scientificity and pertinence of the extraction of wellbore failure information and the selection of core samples, and has significant beneficial effects. First, the micro-resistivity imaging logging technology is used to obtain high-resolution wellbore images, enhancing the perception ability of the microstructural changes around the wellbore and providing a rich data basis for subsequent analysis. The image processing and enhancement steps improve the recognizability of the failure characteristics, making the extraction of wellbore failure information more accurate and reliable, and effectively reducing the information omission or misjudgment caused by noise interference. The identification of the failure type realizes the classification and judgment of typical failure modes such as caving and tensile fractures, providing an important prior condition for the subsequent stress state derivation. At the same time, through the identification and analysis of the core distribution law, representative core samples can be selected specifically, significantly improving the adaptability of the samples and the credibility of the mechanical parameter test. In addition, by calculating the overburden pressure parameter in combination with the wellbore failure information, not only the accuracy of the stress input data is improved, but also the characterization ability of the formation vertical stress field is enhanced, providing an important support for constructing a more reasonable in-situ stress model. Overall, this solution shows good adaptability and engineering application value in complex formation environments.

[0025] Preferably, step S2 includes the following steps: Step S21: Conduct physical size inspection and standard shaping on the core sample to obtain the sample to be tested; Step S22: Deploy ultrasonic transducers at both ends of the sample to be tested, measure the longitudinal wave velocity and the transverse wave velocity respectively, and calculate the Poisson's ratio and Young's modulus; Step S23: Conduct a standard uniaxial compression test on the sample to be tested, gradually apply pressure until the sample to be tested fails, and record the maximum axial stress value when the sample to be tested fails, which is the uniaxial compressive strength value; Step S24: Apply a radial compression load on the core cylindrical sample of the sample to be tested, and calculate the tensile strength value according to the fracture load and size of the sample to be tested; Step S25: Record the Poisson's ratio, Young's modulus, uniaxial compressive strength value and tensile strength value as the rock mechanical parameters.

[0026] In the embodiment 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, and the length-diameter ratio is 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, and then 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 St 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, value range 20 - 200 MPa) and tensile strength value (Unit: MPa, value range: 2-20MPa) 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.

[0027] 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 strengths, and provides key constitutive parameter support for the inversion of geostress states. 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 geostress analysis under complex geological structures and deep formation conditions.

[0028] Preferably, step S3 comprises the following steps: 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; Step S32: recording the original diameter distribution data of the smooth core sample under the condition of no external force; 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; 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; 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: ; in is the difference between the maximum and minimum stresses, is the maximum stress value, is the minimum stress value, is Young's modulus, is Poisson's ratio, is the maximum diameter after loading, is the minimum diameter after loading, is the original diameter distribution data.

[0029] In the embodiment of the present invention, cylindrical core samples with a surface integrity, no micro-cracks, and a diameter error less than 0.02 mm are selected from a variety of core samples that have undergone fracture 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 value of each measurement point under the condition of no external force is recorded to generate a complete original diameter distribution data table, which includes the measurement angle and the corresponding diameter value (unit: mm, accurate to 0.001 mm). The smooth core sample is installed on the loading platform 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 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 radial dimension distribution table under the loading state is recorded. 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 ) where the change amount is the largest 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). Ensure unit consistency during the calculation process, and finally obtain the difference between the maximum and minimum stresses accurate to 0.1 MPa. This difference directly reflects the magnitude of the principal stress difference in the surrounding rock stress field.

[0030] Through high-precision deformation measurement of smooth core samples under different loading states, the present invention effectively improves the acquisition accuracy and physical interpretability of the maximum and minimum principal stress differences, with 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 at multiple angles around 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 dimension changes before and after loading, the stress response differences of the material in different directions can be intuitively reflected, thereby accurately identifying the maximum and minimum deformation directions and further 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, especially 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.

[0031] Preferably, constructing the stress polygon model based on the overburden pressure parameter in step S4 includes: Repeatedly collecting the pore pressure of the measurement section by the bottom tester; Constructing the stress polygon model, and the specific construction process is: ; Wherein, is the friction coefficient, with a value range between 0.6 and 1, dimensionless, is the overburden pressure parameter, which can be approximately equal to the vertical stress, is the maximum principal stress, is the minimum principal stress, is the pore pressure.

[0032] In the embodiment of the present invention, first, the RFT repeated bottom tester conducts in-situ pore pressure measurement in the measurement section. The pressure sensor sensitivity of the tester is 0.01 MPa, and pore pressure data at 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, in combination with the overburden pressure parameter , and the friction sliding equilibrium principle in Anderson's fault theory, three inequality relationships of the stress polygon are established: ; where the friction coefficient 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 construct a stress polygon graph 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 . Convert the three inequalities into three boundary lines on the coordinate plane respectively, and take the closed area enclosed by the three boundary lines and the straight line as the stress polygon constraint area. 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, mark the position of the overburden pressure value at the current depth on the stress polygon graph, and perform grid processing on the stress polygon area. The grid size is 0.5 MPa × 0.5 MPa, and the completed stress polygon model data is stored in the relational array, including the maximum principal stress and minimum principal stress value pairs corresponding to each grid point.

[0033] 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 an 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, so as to provide 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 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 higher-precision stress state inversion.

[0034] Preferably, the wellbore failure model constructed based on the failure type in step S4 includes:[[]] Construct a wellbore failure model, and the specific construction process is as follows: ; Among them, are the effective stresses around the wellbore in the cylindrical coordinate system, , are the variables 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; 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 fracture, select the tensile failure criterion: ; 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.

[0035] 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.

[0036] In the embodiment of the present invention, when the caving failure type is identified, the system uses the conversion formula from the regular hexahedron rectangular coordinate system to the cylindrical coordinate system to calculate the effective stress distribution around the wellbore. Specifically, ; For the caving 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, and the vertical axis represents the maximum principal stress numerical range; when the failure type is caving, based on the radial effective stress , circumferential effective stress , axial effective stress and tangential stress According to the calculation results of , circumferential effective stress , axial effective stress and tangential stress , the stress conditions restricted by the shear failure criterion are superimposed on the stress polygon constraint region; when the failure type is induced tensile cracks, based on the radial effective stress and minimum principal stress to obtain the precise numerical range.

[0037] The method for constructing the 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 evaluation 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 caused by different failure types (such as sloughing or induced tensile cracks) of the wellbore. 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, the model can calculate the circumferential and radial stresses of the wellbore systemically and compare them with the failure strength range of the core, and can predict in advance whether the wellbore will fail, greatly enhancing the practicability and forward-looking of the 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.

[0038] Preferably, in step S4, a two-dimensional constraint system is established by using the stress polygon model and the wellbore failure model, and the multi-source coupled constrained principal stresses include: The numerical ranges of the maximum principal stress and the minimum principal stress that meet the constraint conditions of the stress polygon model are plotted as a closed area 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 ; Based on the failure type, the corresponding wellbore failure model is selected for regional superposition; If the failure type is caving, the shaft wall failure model restricted by the shear failure criterion is superimposed on the stress polygon constraint region; If the failure type is induced tensile crack, the shaft wall failure model restricted by the tensile failure criterion is superimposed on the stress polygon constraint region; After superposition, an additional boundary line is formed to obtain a two-dimensional constraint region; Perform superposition region analysis on the two-dimensional constraint region, extract the intersection region, and obtain the multi-source coupling constraint principal stress interval.

[0039] 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 to ensure that the pressure data error does not exceed ±0.05 MPa, and then 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), the following mathematical expression is used to construct the two-dimensional stress polygon boundary: , where is the maximum principal stress, is the minimum principal stress. This inequality group is plotted on a two-dimensional coordinate graph by setting as the vertical axis and as the horizontal axis to draw a continuous boundary curve, 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 crack) output by the shaft wall failure model, and superimpose the boundary line data on 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 shaft wall failure model is calculated by the shear strength envelope expression , where ranges from 28° to 35°; then generate point sets that satisfy this expression at a step size of 0.1 MPa and map them to the two-dimensional plane; the overlapping part of the two regional boundaries 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 shaft wall 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.

[0040] The present invention utilizes 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, by combining the constraint conditions of the stress polygon model and the wellbore failure model, the numerical ranges of the maximum principal stress and the minimum principal stress can be comprehensively covered, presented as a closed area in a two-dimensional coordinate system, clearly defining the stress change range, and enhancing the visualization and operability of the stress state. Then, through 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 area to form a more accurate two-dimensional constraint area. This process not only ensures the close coupling of the wellbore failure strength and the stress state, but also effectively limits the change range of the principal stress 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 area, 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.

[0041] Preferably, 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 principal stress interval of multi-source coupled constraint obtained by using the shear failure criterion, take the uniaxial compressive strength value as the failure constraint parameter; Among them, 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 principal stress interval of multi-source coupled constraint obtained by using the shear failure criterion, form the graphical distribution of the feasible solution area and the infeasible solution area, and remove the infeasible solution area; If the failure type is induced tensile cracks, after performing thermal stress disturbance analysis on the principal stress interval of multi-source coupled constraint obtained by using the tensile failure criterion, take the tensile strength value as the failure constraint parameter; Among them, the specific thermal stress disturbance analysis is that 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 Young's modulus, and use the additional tensile stress to correct the principal stress interval of multi-source coupled constraint obtained by using the tensile failure criterion; Apply the constraint parameters to the principal stress interval of multi-source coupled constraint to obtain the principal stress interval of strength constitutive constraint.

[0042] In the embodiments of the present invention, based on the obtained multi-source coupled constrained principal stress interval, first, the stress constraint path is 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 coupled constrained principal stress interval. The specific operation is as follows: Using 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, and using the Mohr-Coulomb failure condition expression to conduct point-by-point inspection on all pairs of principal stress values in the principal stress interval. In the two-dimensional coordinate graph, all data points that do not meet this failure condition are removed, and only the combinations of principal stress values 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 adopted, and combined with the tensile strength value (unit: MPa, range: 2 MPa to 8 MPa), thermal stress disturbance analysis is carried out. 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), and the additional tensile stress is added to the minimum principal stress direction. After point-by-point superposition and correction in the multi-source coupled constrained principal stress interval, 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, this pair of stress values is regarded as the failure state and excluded. Finally, all pairs of principal stress values that meet the strength boundary are retained to form the strength constitutive constrained principal stress interval.

[0043] The method of the present invention for determining the constraint parameters based on the failure type and further correcting the multi-source coupled constrained 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 excluding the infeasible solution region through the judgment of 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 of induced tensile cracks, the multi-source coupled constrained 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 wall. The correction of the additional tensile stress enables the stress interval to more accurately reflect the stress changes in the actual environment, improving 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.

[0044] Preferably, step S6 includes: The difference between the maximum and minimum stresses It is represented 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 coupling constraint principal stress interval, and the strength constitutive constraint principal stress interval in the two-dimensional coordinate system to obtain a caving / induced tensile fracture topology visualization diagram; Based on the caving / induced tensile fracture 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; If the intersection point is an interval, the intersection point forms a banded area; if the intersection point is a single point, the point is the exact stress solution; otherwise, it is a set of numerical pairs , and at the same time satisfy the boundary conditions of the polygon and the strength limit area.

[0045] In the embodiment of the present invention, first, the difference between the maximum and minimum stresses is expressed as a linear function relationship , where is the maximum principal stress, is the minimum principal stress, and in the two-dimensional coordinate system, with as the horizontal axis and as the vertical axis, plot a stress difference constraint line with a slope of 1 and a vertical intercept of . 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, plot the multi-source coupling constraint principal stress interval and the strength constitutive constraint principal stress interval in the same coordinate system respectively. These two parts of data are both principal stress numerical pairs stored in tabular form. Each principal stress pair point is marked with a different color, representing the results of multi-source coupling constraint and strength constraint respectively. Then, introduce the stress difference constraint line in the drawing area, cross-compare this line with the point sets of the two principal stress intervals, and screen all the data points that fall on the line or within the line segment banded area 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, the interval is the numerical banded range of the maximum principal stress and the minimum principal stress; if only a single point falls at the intersection of the three types of constraint graphs, the point is the exact stress solution; if there are multiple discontinuous intersection points, extract all the coordinate pairs that satisfy the stress difference relationship and are at the same time within the aforementioned two principal stress intervals 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.

[0046] 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, the multi-source coupling constraint, and the strength constitutive constraint. This method can effectively visualize the stress state of caving and induced tensile fractures, helping to intuitively identify the intersection points of the stress difference constraint line and other constraint regions, thereby accurately determining the numerical range of the maximum principal stress and the minimum principal stress. When the intersection point is a banded region, 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 accurate 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 more accurate and reliable stress analysis results. By using this topological visualization diagram, 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.

[0047] 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: A failure identification module for obtaining wellbore failure information and identifying the failure type in the wellbore failure information; selecting a variety of core samples based on the wellbore failure information, and determining the overburden pressure parameter based on the variety of core samples; A mechanical test module for 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; A stress difference measurement module for marking smooth core samples from a variety of core samples based on the failure type, and performing DCDA experiments 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 for constructing a stress polygon model based on the overburden pressure parameter; constructing a wellbore failure model based on the failure type; establishing a two-dimensional constraint system using the stress polygon model and the wellbore failure model, and performing multi-source coupling constraint on the principal stress; A range constraint module for performing strength constitutive constraint on the principal stress using the uniaxial compressive strength value / tensile strength value based on the failure type; An intersection inversion module for topologically visualizing the multi-source coupling constraint principal stress and the strength constitutive constraint principal stress, and performing 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.

[0048] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is not defined by the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be encompassed within the present invention.

[0049] 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 invented herein.

Claims

1. A method for measuring three-dimensional core stress based on multi-source data, characterized in that: The following steps are involved: Step S1: obtaining well wall damage information and identifying the damage type in the well wall damage information; Select multiple core samples based on wellbore damage information, and determine overburden pressure parameters based on the multiple core samples; Step S2: performing rock mechanics experiments on the core samples to generate rock mechanics parameters, wherein the rock mechanics parameters include Poisson's ratio, Young's modulus, uniaxial compressive strength value and tensile strength value; Step S3: marking a smooth core sample from a plurality of core samples based on the failure type, and performing a core diameter deformation analysis experiment on the smooth core sample using Poisson's ratio and Young's modulus to obtain the difference between the maximum and minimum stresses; Step S4: constructing a stress polygon model based on the overburden pressure parameters; Construct wellbore damage model based on damage type; Use stress polygon model and wellbore failure model to plan two-dimensional constraint area and implement multi-source coupling constraint principal stress; Step S5: executing strength constitutive constraint principal stress based on the failure type using uniaxial compressive strength value or tensile strength value; Step S6: Topologically visualize the multi-source coupling constrained principal stress and the strength constitutive constrained principal stress, and make a regional overlap judgment between 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.

2. The method for measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: collecting wellbore wall image data of the measurement section by using a well perimeter microresistivity imaging logging instrument; Step S12: removing noise and enhancing the image data of the borehole wall in the measurement section, and extracting the borehole wall damage information; Step S13: identifying the damage type based on the wellbore damage information, wherein the damage type includes collapse and induced tensile cracks; Step S14: identifying the core distribution law based on the wellbore damage information, and selecting multiple core samples based on the core distribution law; Step S15: Calculate the overburden pressure parameters of various core samples based on the well wall damage information. The specific calculation process is as follows: ， in, is the overburden pressure parameter, For Depth The density of the core, is the acceleration due to gravity, is the core depth.

3. The method for measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: Perform physical size inspection and standard shaping on the core sample to obtain the sample to be tested; Step S22: deploying ultrasonic transducers at both ends of the sample to be tested, respectively measuring the longitudinal wave velocity and the transverse wave velocity, and calculating the Poisson's ratio and Young's modulus; Step S23: Perform a standard uniaxial compression test on the test sample, gradually increase the pressure until the test sample is destroyed, and record the maximum axial stress value when the test sample is destroyed, which is the uniaxial compressive strength value; Step S24: applying a radial compression load to the core cylindrical sample of the test sample, and calculating the tensile strength value according to the fracture load and size of the test sample; Step S25: Record the Poisson's ratio, Young's modulus, uniaxial compressive strength value and tensile strength value as rock mechanics parameters.

4. The method for measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: Step S3 includes the following steps: 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; Step S32: recording the original diameter distribution data of the smooth core sample under the condition of no external force; 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; 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; 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: , in is the difference between the maximum and minimum stresses, is the maximum stress value, is the minimum stress value, is Young's modulus, is 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 measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: In step S4, constructing a stress polygon model based on the overburden pressure parameter includes: The pore pressure of the measuring section is collected by repeated bottom layer tester; Construct a stress polygon model. The specific construction process is as follows: ； in, is the friction coefficient, ranging from 0.6 to 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 measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: In step S4, the wellbore failure model is constructed based on the failure type, including: Construct the well wall failure model. The specific construction process is as follows: ； in, are the effective stress around the wellbore wall in the cylindrical coordinate system, , is the variable of the ground stress field in the rectangular coordinate system, is the drilling fluid pressure, is the pore pressure, is Poisson's ratio, is the well wall failure angle; Select the corresponding failure criterion based on the failure type; If the failure type is collapse, select the shear failure criterion: ; If the failure type is induced tensile cracks, select the tensile failure criterion: ; in 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; According to the effective stress around the wellbore in the cylindrical coordinate system, combined with the drilling fluid pressure and pore pressure, the circumferential and radial stresses of the wellbore are calculated to determine whether they exceed the core failure strength range.

7. The method for measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: In step S4, a two-dimensional constraint system is established using the stress polygon model and the wellbore failure model, and the multi-source coupling constraint principal stress is executed, including: The maximum principal stress that meets the constraints of the stress polygon model Minimum principal stress The numerical range of is plotted as a closed area under a two-dimensional coordinate system to obtain the stress polygon constraint area, where the horizontal axis is the minimum principal stress , the vertical axis is the maximum principal stress ; Select the corresponding wellbore damage model based on the damage type for regional superposition; If the failure type is collapse, the wellbore failure model restricted by the shear failure criterion is superimposed on the stress polygon constraint area; If the failure type is induced tensile cracks, the wellbore failure model restricted by the tensile failure criterion is superimposed on the stress polygon constraint area; After superposition, additional boundary lines are formed, and a two-dimensional constraint area is obtained; The superposition area analysis is performed on the two-dimensional constraint area, the intersection area is extracted, and the multi-source coupling constraint principal stress interval is obtained.

8. The method for measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: Step S5 includes: Determine constraint parameters based on the damage type; If the failure type is collapse, the core shear limit condition is judged for the multi-source coupling constrained principal stress interval obtained by the shear failure criterion, and the uniaxial compressive strength value is used as the failure constraint parameter; The core shear limit condition is judged specifically by substituting the shear failure formula point by point based on the rock mechanics parameters and the multi-source coupling constrained principal stress interval obtained by using the shear failure criterion, forming a graphical distribution of feasible solution areas and infeasible solution areas, and removing the infeasible solution areas; If the failure type is induced tensile cracks, the tensile strength value is used as the failure constraint parameter after thermal stress perturbation analysis is performed on the multi-source coupling constrained principal stress interval obtained by using the tensile failure criterion; The thermal stress disturbance analysis is as follows: when the core temperature drops, the additional tensile stress generated on the borehole wall of the measuring section is calculated based on Poisson's ratio and Young's modulus, and the multi-source coupling constrained principal stress interval obtained by using the tensile failure criterion is corrected using the additional tensile stress; The constraint parameters are applied to the multi-source coupling constrained principal stress interval to obtain the strength constitutive constrained principal stress interval.

9. The method for measuring three-dimensional core stress based on multi-source data according to claim 1, characterized in that: Step S6 includes: The difference between the maximum and minimum stresses Expressed as a functional relationship line, the stress difference constraint line with a slope of 1 is obtained, that is, ; Construct a two-dimensional coordinate system, with the horizontal axis representing the minimum stress value , the vertical axis represents the maximum stress value ; The stress difference constraint line, multi-source coupling constraint principal stress interval and strength constitutive constraint principal stress interval are plotted in a two-dimensional coordinate system to obtain a topological visualization diagram of collapse / induced tensile cracks; Based on the topological visualization of collapse / induced tensile cracks, the intersection of the stress difference constraint line and the constraint graph is identified to obtain the numerical range of the maximum principal stress and the minimum principal stress; If the intersection is an interval, the intersection forms a strip area; if the intersection is a single point, the point is the exact stress solution; otherwise, it is a set of The value pair , and at the same time satisfy the boundary conditions of the polygon and the intensity restriction area.

10. A three-dimensional core stress measurement system based on multi-source data, characterized in that: Used to perform the core three-dimensional in-situ stress measurement method based on multi-source data according to claim 1, the core three-dimensional in-situ stress measurement system based on multi-source data comprises: A damage identification module is used to obtain wellbore damage information and identify the damage type in the wellbore damage information; select multiple core samples based on the wellbore damage information, and determine the overburden pressure parameters based on the multiple core samples; Mechanical testing module, used to conduct rock mechanics experiments on core samples and generate rock mechanics parameters, including Poisson's ratio, Young's modulus, uniaxial compressive strength and tensile strength; Stress difference measurement module, used to mark smooth core samples from multiple core samples based on the type of damage, and use Poisson's ratio and Young's modulus to perform core diameter deformation analysis experiments on smooth core samples to obtain the difference between the maximum and minimum stresses; Stress modeling module, used to build stress polygon model based on overburden pressure parameters; build wellbore damage model based on damage type; establish a two-dimensional constraint system using stress polygon model and wellbore damage model, and perform multi-source coupling to constrain principal stress; Range constraint module for performing strength constitutive constraint principal stresses based on failure type using uniaxial compressive strength values / tensile strength values; The intersection inversion module is used to topologically visualize the multi-source coupled constrained principal stress and the strength constitutive constrained principal stress, and to make regional overlap judgments based on the difference between the maximum and minimum stresses and the topological visualization results to determine the numerical range of the maximum and minimum principal stresses.

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