46 results about "Rock breakage" patented technology

The invention provides a deep-buried tunnel TBM vibration and excavation unloading fracture micro-seismic discrimination method and system, and relates to the technical field of tunnel construction, and the method comprises the steps: obtaining micro-seismic event data in a target area; spatial classification is carried out according to the micro-seismic event data, and the influence range of the excavation unloading effect is obtained; performing region division according to the influence range to obtain a rock fracture signal after noise reduction; performing multi-layer decomposition on the rock fracture signal by using wavelet transform to obtain a characteristic parameter set; performing energy grading according to the characteristic parameter set to obtain a grading result; constructing a discrimination standard according to the grading result to obtain the discrimination standard; and performing discrimination based on the discrimination standard to obtain a discrimination result. According to the method, the dynamic model is constructed based on the multi-energy-level discrimination standard, main control factor classification is performed on the real-time micro-seismic event, real-time dynamic discrimination of TBM vibration and excavation unloading fracture in the construction process is achieved, and the early warning timeliness of time-delay rock burst is remarkably improved.

The invention relates to the technical field of rock mechanical tests and safety monitoring, and discloses a rock fracture prediction method based on acoustic emission and surface strain cooperative monitoring, and the method comprises the steps: building a monitoring system comprising acoustic emission and an industrial camera array, and building a unified timestamp of each subsystem through a GPS time service module; through load triggering logic, a synchronous trigger is utilized to synchronously acquire an acoustic emission signal and a sample surface image sequence, and evolution characteristics of three-dimensional coordinates of an acoustic emission source and surface full-field strain data are solved. And on the basis, calculating a main strain field variation coefficient, and performing cross-correlation analysis on the resampled energy rate and strain rate. And finally, according to multi-parameter coupling criteria of acoustic emission time sequence parameters, positioning events and surface strain, identifying rock fracture precursor types, and predicting fracture moments and areas by combining a Voight model inverse velocity method and a seismic source projection technology.

The invention discloses a rock fracture prediction method and system based on a resistivity data assimilation algorithm, and the method comprises the steps: building a numerical model for simulating the asymptotic fracture process of a rock mass under the load effect according to the boundary conditions and initial conditions of the rock mass; simulating the stress damage process of the rock mass by using a numerical calculation method to obtain prediction data of stress field and fracture damage field distribution of the rock mass; monitoring the damage process of the rock mass sample in real time by using a high-density electrical method to obtain observation data; rock mass fracture damage distribution is obtained based on observation data; an assimilation algorithm is adopted, information of observation data and information of prediction data are combined, and initial conditions or parameters of the numerical model are corrected; and then corrected rock fracture prediction data is obtained. Through the data assimilation algorithm, different data and model simulation results are fused in the power frame of rock fracture, the model track is automatically adjusted continuously depending on observation, the analysis result with higher precision and more consistency is obtained, and the prediction precision and predictability of the model are improved.

The invention relates to the technical field of underground geotechnical engineering and tunnel construction monitoring, in particular to a shield tunneling rock stratum real-time judgment method. The method comprises the steps that according to signals of neutron radiation characteristics released when different lithologic samples are fractured under a shield tunneling stress path simulated in a laboratory, a knowledge base of the neutron radiation characteristics of a rock stratum is constructed; deploying an on-site multi-source data acquisition system, and acquiring data of neutron radiation characteristics and shield tunneling parameters; jointly forming a fusion feature vector according to the data of the neutron radiation features and the shield tunneling parameters; the method has the advantages that signals of neutron radiation characteristics released in the rock fracture process are directly monitored, the signals are fused with shield tunneling parameters in a multi-source mode, a machine learning model is combined, and the lithology classification probability and the rock mass integrity index are obtained. Real-time and accurate discrimination of lithology and integrity of a front rock stratum is realized, physical characteristics of a rock mass are reflected, and a discrimination effect is continuously optimized.

This disclosure relates to a rock thermal shock experimental apparatus, experimental method, and rock fracture evaluation method. The rock thermal shock experimental apparatus includes a true triaxial system, a liquid supply system, and a temperature measurement system. The true triaxial system is used for triaxial confining pressure loading and heating of the rock sample. Thermal shock boreholes and temperature measurement boreholes are drilled on the rock sample. The liquid supply system includes an inlet pipeline for injecting liquid into the thermal shock boreholes and a supply pump connected to the inlet pipeline, as well as an outlet pipeline for discharging the liquid. The temperature measurement system includes multiple temperature measuring devices, with temperature measuring devices arranged at least inside the thermal shock boreholes and inside the temperature measurement boreholes. The rock thermal shock experimental apparatus of this disclosure can realistically simulate the impact of underground fluids on rocks, achieving the thermal shock effect by creating an effective temperature difference between the heated rock sample and the injected cold liquid. The rock fracture evaluation method can quantitatively analyze the relationship between temperature and rock fracture under thermal shock.

The invention relates to the technical field of rock mass fracture identification, in particular to a rock fracture acoustic emission signal intelligent identification method under the action of high and low temperature cycling, which comprises the following steps: making a rock test piece, and obtaining acoustic emission data in the rock fracture process; dividing the acoustic emission data into a temperature damage stage and a stress fracturing stage on the basis of the corresponding relationship between acoustic emission count, amplitude frequency and energy in the acoustic emission data and stress; performing wavelet packet transformation and Hilbert-Huang transformation on waveforms in the acoustic emission data set after stage division, and extracting to obtain waveform modal features; preprocessing waveform modal features; a multi-modal recognition model based on an Inceptionv3 branch network structure is constructed, and the multi-modal recognition model is trained and tested; and inputting acoustic emission data collected in real time under different high and low temperature difference cycles into the tested multi-modal recognition model, and further evaluating the classification performance of the model. According to the method, accurate classification of the rock fracture acoustic emission signals in the temperature damage stage and the stress fracturing stage is realized.

The invention discloses a rock material tension-shear failure simulation method and equipment based on a dynamic dual-phase field model. The method comprises the following steps: establishing a stress tensor physical model corresponding to a rock material constitutive relationship; respectively introducing a tension phase field and a shear phase field, and establishing a dynamic double-phase field model corresponding to the rock tension-shear failure physical process; deducing an energy functional of the dynamic double-phase field model; establishing a crack surface local coordinate system, and judging a crack contact state according to a frictional contact phase field theory; switching a stress tensor decomposition mode according to the contact state, and calculating a phase field evolution driving force; rock material tension-shear failure simulation based on the dynamic two-phase field model is achieved, and rock fracture form evolution data are output and used for evaluating rock slope stability.

This invention belongs to the field of petroleum exploration and discloses a quantitative characterization method for structural fracture parameters based on the coupling of the minimum energy consumption and minimum action principle. To overcome the shortcomings of existing technologies in achieving quantitative prediction of structural fractures from qualitative description, this invention first calculates the energy consumption of fracture rupture through rock mechanics experiments; then, it couples the minimum energy consumption principle and the minimum action principle to establish a rock fracture criterion; based on this, it derives and establishes quantitative characterization models for fracture aperture, volumetric density, and linear density; subsequently, it constructs a heterogeneous mechanical parameter volumetric model and performs elastoplastic geostress field simulation; finally, it achieves batch prediction of structural fracture parameters through programming, and verifies the reliability of the prediction results using core, imaging logging, and production dynamic data. This invention, starting from the physical essence of energy distribution and path selection, provides a unified theoretical framework for rock fracture and significantly improves the prediction accuracy of fracture "sweet spots."

This invention discloses a real-time monitoring and early warning system for rock fracture induced by disturbance in deep fluidized bed mining, comprising: a multimodal sensor array for synchronously acquiring acoustic emission / microseismic signals from deep rock masses and key environmental disturbance parameters during fluidized bed mining; a data acquisition and transmission module; an environmental noise modeling and feature characterization module; a context-aware signal separation and enhancement module; and a rock fracture feature extraction and event recognition module. This invention relates to the field of mine safety monitoring technology. This real-time monitoring and early warning system for rock fracture induced by disturbance in deep fluidized bed mining provides rich contextual information through the multimodal sensor array. Combined with environmental noise modeling and a deep learning-based context-aware signal separation and enhancement module, this invention can effectively identify and suppress the complex and dynamic background noise unique to deep fluidized bed mining, ensuring that weak rock fracture signals are no longer drowned out.

This invention provides an artificial intelligence-based multiphysics monitoring method for predicting rock fractures, comprising: conducting indoor rock physical hydraulic fracturing experiments and performing multiphysics monitoring; constructing a training dataset: performing the experiments on different rock samples to obtain data, forming a total dataset; constructing a fracture prediction module based on a sequence-to-sequence framework; training a detection network using the training dataset; performing the same preprocessing steps on all data obtained from actual monitoring, inputting observation data before the current time t, and obtaining the predicted fracture result at time t+1; and updating the dataset and the fracture prediction module. This invention's artificial intelligence-based multiphysics monitoring method for predicting rock fractures adaptively integrates and analyzes multiphysics monitoring results to predict the rock fracture development process and the fracture process itself.

The present invention pertains to a system and method to determine rock fracturing during the breaking process, specifically when using rock breakers in the mining industry. More precisely, the present invention relates to a system and a method that, using sensory information composed of images, point clouds, or both, automatically determines, in real time, whether a rock which a rock breaker is attempting to break is fractured or not.

The invention belongs to the field of oil exploration, and discloses a quantitative characterization method for tectonic fracture parameters based on minimum energy consumption-minimum action principle coupling. In order to overcome the defect of difficulty in realizing qualitative description to quantitative prediction of a tectonic fracture in the prior art, the method comprises the following steps: firstly, calculating fracture energy consumption through a rock mechanics experiment; coupling a minimum energy consumption principle and a minimum action quantity principle, and establishing a rock fracture criterion; on the basis, a quantitative characterization model of the fracture opening, the volume density and the linear density is deduced and established; then constructing a heterogeneous mechanical parameter body model and carrying out elastic-plastic crustal stress field simulation; and finally, batch prediction of tectonic fracture parameters is realized through programming, and reliability verification is carried out on a prediction result by using rock core, imaging logging and production dynamic data. According to the method, a unified theoretical framework is provided for rock fracture from the physical essence of energy distribution and path selection, and the prediction precision of the crack sweet spot area is remarkably improved.

The application discloses a rock fracture prediction method and system based on a resistivity data assimilation algorithm, and comprises the following steps: establishing a numerical model for simulating the gradual fracture process of a rock mass under load action according to the boundary conditions and initial conditions of the rock mass; simulating the stress failure process of the rock mass by using a numerical calculation method to obtain prediction data of the stress field and the fracture damage field distribution of the rock mass; monitoring the failure process of the rock mass pattern in real time by using a high-density electrical method to obtain observation data; obtaining the fracture damage distribution of the rock mass based on the observation data; combining the information of the observation data and the prediction data by using an assimilation algorithm to correct the initial conditions or parameters of the numerical model; and further obtaining the corrected rock fracture prediction data. The application fuses different data and model simulation results in the dynamic framework of rock fracture by using the data assimilation algorithm, constantly adjusts the model trajectory automatically by relying on observation, obtains higher-precision and more consistent analysis results, and improves the prediction accuracy and predictability of the model.

The application discloses a microseismic rock breaking signal simulation device, which comprises a microseismic signal simulation system and a microseismic monitoring system which are coupled, the microseismic signal simulation system is used to repeatedly generate the same knocking signal, the microseismic signal simulation system comprises PC control software, a knocking circuit control board and a sensor knocking frame, the PC control software is connected with the knocking circuit control board, realizes the issuing of a working instruction, the knocking circuit control board transmits an instruction to the sensor knocking frame, and controls the knocking strength and the knocking frequency of the sensor knocking frame, and the microseismic monitoring system receives the knocking signal generated by the sensor knocking frame and visually displays the same; the application can repeatedly generate the same knocking signal, and can also sequentially generate the signal to simulate the rock breaking signal in an indoor environment for the research and development and maintenance of the microseismic monitoring system.

The invention relates to the technical field of shale gas geology, in particular to a method for depicting a breaking joint body in a breaking joint body development area, and the method comprises the steps: firstly, generating an initial breaking joint body probability body based on interpretable machine learning fusion seismic attributes, and building a three-dimensional space distribution model containing large and medium faults after manual interactive interpretation and well seismic calibration; on the basis, large and medium-sized faults serve as a deterministic skeleton, a fracture development rule is predicted in combination with paleotectonic stress field simulation and a rock fracture criterion, a three-dimensional discrete fracture network model constrained by geomechanics is constructed and then coupled with a matrix model, and a model set is generated by defining an uncertainty parameter space. And screening out an equivalent model group through historical matching, performing prediction verification and iterative optimization by using recent production data, and finally obtaining a three-dimensional space distribution model of the high-precision breaking joint body. According to the method, closed loop of static identification and dynamic verification is realized, and the depicting precision and the geological reliability are remarkably improved.

This invention discloses a double-layer chain coordinated coal conveying control system and method for scraper conveyors, belonging to the technical field of fully mechanized mining face conveyors. The system includes a head chain control system, a tail chain control system, a coal conveying section, and a centralized control system. The coal conveying section includes a primary chain drive system and a secondary chain drive system arranged in parallel. Motors for driving the chain drive systems are installed in the head and tail chain control systems. The control method employs a three-layer deep reinforcement learning strategy. The first layer independently controls the motor speed synchronization and tension; the second layer coordinates the motor speed and tension, and incorporates a fault-clearing function for large coal and rock breakage; the third layer achieves global coordinated control under normal and fault conditions. This invention significantly improves the load capacity, operational reliability, and fault self-healing capability of scraper conveyors.

The invention provides a rock sample hydrofracture thermal-mechanical coupling loading experiment device and method, and belongs to the technical field of rock mechanics, the rock sample hydrofracture thermal-mechanical coupling loading experiment device comprises a frame, an upper base, an upper pressing plate, a lower base, a lower support, a fixing support, a rock sample, a loading system and a hydraulic control system; limitation of a traditional triaxial experiment is effectively overcome, true triaxial non-uniform stress and thermal coupling loading of a cylindrical rock sample is realized, an underground complex ground stress and temperature field can be simulated through 12 groups of confining pressure units and 8 partition heating systems, a positioning structure and a limiting system enhance the overall rigidity of a loading cylinder, and the loading cylinder can be used for loading a rock sample. Uniform stress transmission and stable measurement basis are ensured, the signal-to-noise ratio and precision of strain data are improved, the heat conduction frame and the sealing air bag ring are combined with multi-stage sealing and pressure relief design, reliability and safety under high temperature and high pressure are fundamentally ensured, and technical support is provided for deep research of a rock fracture mechanism and optimization of a fracturing process.

This invention provides an experimental apparatus and method for hydraulic fracturing and thermo-coupling loading of rock samples, belonging to the field of rock mechanics technology. The invention includes: a frame, an upper base, an upper pressure plate, a lower base, a lower support, a fixed bracket, a rock sample, a loading system, and a hydraulic control system. This invention effectively overcomes the limitations of traditional triaxial experiments, achieving true triaxial non-uniform stress and thermo-coupling loading of cylindrical rock samples. Through 12 confining pressure units and an 8-zone heating system, it can simulate complex underground stress and temperature fields. The positioning structure and limiting system enhance the overall rigidity of the loading cylinder, ensuring uniform stress transmission and stable measurement benchmarks, and improving the signal-to-noise ratio and accuracy of strain data. The heat-conducting frame and sealing airbag ring, combined with multi-stage sealing and pressure relief design, fundamentally guarantee reliability and safety under high temperature and high pressure, providing technical support for in-depth research on rock fracture mechanisms and optimization of fracturing processes.

The invention belongs to the technical field of oil exploration, and discloses a crack propagation path quantitative prediction method based on a double extreme value principle. The method comprises the following steps: obtaining a stress-strain curve and related mechanical parameters through a rock mechanics experiment; constructing a rock fracture criterion based on a double extreme value principle; establishing a quantitative prediction model of the crack propagation angle and length; combining with three-dimensional tectonic stress field simulation to realize spatial prediction of a crack propagation path; and the reliability of the prediction result is verified through measured data. The method disclosed by the invention reveals a crack propagation mechanism from the perspective of energy evolution, has the advantages of solid physical foundation and adaptability to complex geological conditions, remarkably improves the precision of crack length and direction prediction, and provides reliable technical support for evaluation and development optimization of an unconventional reservoir crack system.

The application provides a method for quickly obtaining the creep characteristics of rock samples with different rupture degrees, and comprises the following steps: S1, sample installation, initial setting and loading of a testing machine; S2, real-time calculation of a rock rupture degree index RFD during the loading process; S3, creep test at different stress levels; S4, cyclic loading and unloading, and repeated step S3 for the creep test; S5, peak strength test; S6, multi-stage creep test at the peak strength; S7, multi-stage creep test at the post-peak deformation stage; and S8, cyclic test until the final rupture degree. The creep test at different rupture degrees and different stress levels is completed on the same sample, so that the time and sample quantity required by the test are greatly reduced, and the test efficiency is improved; the RFD calculation formula is used to monitor the rupture degree of the sample in real time, so that the rupture degree of the sample can be accurately controlled, and the accuracy of the test data is ensured; and the test cost is reduced by reducing the preparation and consumption of the sample.

The invention provides an experimental device and method capable of realizing reverse pressure driving fluid-solid coupling seepage simulation, and the experimental device is characterized in that a rock core is arranged in a triaxial rock core holder, an injection port is formed in the triaxial rock core holder, the injection port is communicated with a forward pressure driving injection system, a ground stress loading system is connected with a pressurization cylinder arranged on the triaxial rock core holder in a matched manner, and the forward pressure driving injection system is communicated with a forward pressure driving injection system; the forward pressure driving injection system is matched with a liquid outlet formed in the triaxial rock core holder, and the pressure acquisition system is correspondingly connected with the forward pressure driving injection system and the reverse pressure driving energy storage system. The device has the beneficial effects that loading of a non-uniform stress field can be achieved through the ground stress loading system, boundary stress interference is effectively eliminated in cooperation with the specially-made rock core edge reduction structure and the elastic rubber wrapping frame, crack expansion is closer to the real underground situation, and the crack expansion efficiency is improved. A reliable ground stress environment is provided for researching a rock fracture mechanism and a seepage rule under the fluid-solid coupling effect, and more reliable experimental data and theoretical support are provided for optimizing a mining scheme.

The invention discloses an earthquake vulnerability analysis method based on a rock fracture degree, and the method comprises the following steps: building a finite difference numerical calculation model of a deep underground structure, and selecting a series of seismic oscillation records as the input vibration of the finite difference numerical calculation model, based on the finite difference numerical calculation model and input vibration, determining a seismic oscillation intensity factor and a damage performance index suitable for the deep underground structure, dividing the deep underground structure seismic damage level, and based on the seismic oscillation intensity factor and the structure loss performance index, adopting an incremental dynamic analysis method to analyze the deep underground structure seismic damage level. And acquiring an earthquake vulnerability calculation sample set of the deep underground structure, and based on the earthquake vulnerability calculation sample set, analyzing the earthquake vulnerability of the deep underground structure by establishing an earthquake vulnerability function. The deep underground structure seismic vulnerability analysis precision and applicability are high under the complex seismic geological conditions.

The application provides a rock sample disturbance characteristic test method for controlling the degree of rupture, comprising the following steps: S1: sample preparation; S2: true triaxial compression test loading; S3: disturbance test; S4: lower test; S5: data analysis and result analysis. The application realizes accurate simulation and test of the disturbance characteristics of the rock under different degrees of rupture by calculating the rock rupture degree index (RFD) in real time during the true triaxial compression test and accurately controlling the rupture degree of the research object. The application can complete the disturbance test of samples with different degrees of rupture on one sample, can save the cost and time of indoor test, and can reduce the influence of sample discreteness. The method can more accurately study the mechanical behavior and failure mode of the rock under different degrees of rupture, and can provide theoretical guidance for engineering practice.

The application is based on the supporting method and system of microseismic signal stability classification, the method comprises the following steps: obtaining the total number of rock breaking signals, the highest magnitude of rock breaking signals, the number of secondary to tertiary magnitude signals, and the number of tertiary and above magnitude signals in each mining area in a preset time period; obtaining the first weight value of the total number of rock breaking signals, the second weight value of the highest magnitude of rock breaking signals, the third weight value of the number of secondary to tertiary magnitude signals, and the fourth weight value of the number of tertiary and above magnitude signals by the analytic hierarchy process; determining the daily average score of stability in the mining area; and determining the type of supporting method according to the daily average score of stability. The application can determine the actual stability of each mining area in the underground mine according to the number and magnitude of microseismic breaking signals, and improve the accuracy of the selection of the supporting method of each mining area in the underground mine.

This invention discloses a method for extracting physical constraint features from microseismic data. First, abnormal samples are removed from the microseismic data, and a correspondence between energy thresholds and rockburst hazard levels is established. Second, differentiated stratigraphic weights are assigned based on the vertical distance between microseismic events and the roof interface, highlighting the importance of near-field events on the roof. Then, an adaptive weighted improved DBSCAN spatial clustering algorithm is constructed to quantitatively characterize fracture development and energy accumulation. Next, a Gaussian mixture model is used to probabilistically model the microseismic event sequence and extract surrounding rock stability features. Finally, a multi-source physical feature vector containing temporal statistical features, spatial structural features, and probabilistic state features is constructed to form a precursor feature sequence with clear physical meaning. This method can extract multi-source features from microseismic data that integrate prior geological knowledge and rock fracture physics mechanisms, providing reliable input data for subsequent intelligent rockburst early warning models and effectively improving the accuracy of rockburst determination.

The invention relates to the technical field of rock fracture, and discloses a liquid air energy storage fracture method capable of accurately delaying, which comprises the following steps: mounting a special detonator in a drill hole and connecting the special detonator to a ground controller; the in-situ thermal conductivity coefficient of the drilling environment is detected through the special detonator, and the storage pressure and temperature of to-be-filled liquid air are obtained; operating the feed-forward calibration model, taking the detection parameters as cooperative input, and calculating and generating an operation parameter set containing calibrated delay time and a heating curve; the operation parameter set is issued to a special detonator, and liquid air filling and drilling hole sealing are completed; after an external detonation instruction is received, the special detonator autonomously and cooperatively executes preprocessing and delayed timing according to the parameter set, and detonation is triggered after timing is finished. Through active detection of working conditions, multi-dimensional cooperative calibration and autonomous execution are carried out, the difference between the geological environment and the initial state of a medium is effectively compensated, and it is ensured that liquid air reaches the optimal state at the triggering moment.

The invention discloses a rock fracture classification method based on a time-frequency double-branch fusion convolutional neural network model, and belongs to the field of rock mechanics and geotechnical engineering. The method comprises the following steps: firstly, collecting an acoustic emission signal in a rock damage process, synchronously generating a time domain oscillogram and a frequency domain spectrogram for the same acoustic emission event, and constructing bimodal input data; secondly, constructing a double-branch convolutional neural network architecture, and respectively inputting the time domain graph and the spectrogram into two independent convolutional neural network branches to extract features; and then, splicing and fusing the feature vectors output by the two branches to form a composite feature with time-frequency domain information. And finally, sending the fusion features into a classifier to realize the discrimination of the type of the rock tension and shear fracture. According to the method, the time-frequency complementarity of the acoustic emission signals is fully utilized, high-precision and high-robustness fracture classification can be realized only through single-sensor data, and an effective intelligent tool is provided for accurate analysis of a rock fracture mechanism and engineering safety early warning.

This application discloses a method and system for predicting fold-related fractures based on the principle of stress superposition, belonging to the field of geological analysis technology. The method includes: acquiring past 3D seismic data and past regional stress tensors of a region, and constructing a high-precision structural grid cell on the top surface of the target reservoir; based on the high-precision structural grid cell, determining the fracture type and fracture orientation according to the sliding window-least squares surface fitting joint method, the principle of stress superposition, and rock fracture criteria, thus obtaining a fracture prediction model; acquiring the current 3D seismic data and current regional stress tensor of the target region, and inputting them into the fracture prediction model to obtain the current fracture type and current fracture orientation. This application achieves accurate prediction of the type and orientation of fold-related fractures.

The invention relates to the technical field of oil and gas field development, in particular to a low-permeability reservoir multi-cycle hydraulic fracture expansion method and device and a storage medium. The low-permeability reservoir multi-cycle hydraulic fracture expansion method comprises the steps that the minimum horizontal principal stress and the rock fracture pressure of rock of a target interval are solved; the bottom hole pressure of the target well is obtained; enabling the reservoir to form a shear fracture expansion area; enabling the reservoir to form a tensional fracture expansion area; establishing a high flow guide channel; closing the well, measuring the pressure drop of the well mouth, and waiting for closing of the tensional crack; and the operation from the third step to the sixth step is repeated, multi-cycle liquid injection is conducted, the seam length is increased, and the expansion area of the seam network is expanded. According to the method, a displacement pressure control method is adopted, the reservoir generates shear fractures and tensile fracture zones, the tensile fractures are supported, high flow guide channels are established, the reservoir transformation volume is further increased, the recovery efficiency is improved, the effective period of measures is prolonged by two times compared with conventional fracturing, the construction cost is reduced by 10%, the oil increase of a single well is improved by 15% or above, and low-permeability reservoir benefit development can be achieved.

The invention relates to the field of image processing, and provides an infrared image feature enhancement method and system for a rock fracture precursor, and electronic equipment, and the method comprises the steps: obtaining an original infrared image of a rock fracture process; obtaining a saliency map of the rock fracture area based on the original infrared image; segmenting the saliency map to obtain a foreground region and a background mask region; enhancing the foreground region to obtain a foreground enhanced image, and enhancing the background mask region to obtain a background enhanced image; and fusing the foreground enhanced image and the background enhanced image to obtain an enhanced infrared image of the rock fracture process. The method is used for overcoming the defects that in the cracking process of a rock plate, the signal-to-noise ratio of an infrared image is low, and micro-thermal anomaly recognition is difficult, and accurate separation of a damaged area and a background is achieved based on a foreground and background segmentation module of improved significance detection; and a histogram equalization algorithm based on local variance weighting is adopted, so that an effective technical means is provided for rock burst precursor early warning.