344 results about "Geomechanics" patented technology

The invention relates to the technical field of oil and gas field development, and discloses an ultra-large type true triaxial hydraulic fracturing fracture evolution path prediction method and system.The prediction method comprises the steps that a coupling geomechanical model integrating microscopic, macroscopic and wellbore flow scales is constructed; initializing the model and performing crack initial expansion simulation; collecting construction data in real time, and dynamically optimizing model parameters through a data assimilation algorithm; performing fracture evolution advanced prediction by using the updated model; and generating an optimization decision based on the prediction result and feeding back to the construction site. According to the method, fusion of a multi-scale physical mechanism and real-time dynamic prediction is realized, and accurate prediction and active control can be performed on crack expansion under the ultra-large true triaxial condition.

The invention discloses a rock multi-field coupling test system and a damage evaluation and prediction method thereof, belongs to the technical field of geotechnical engineering and geomechanics experiments, and solves the problem that the rock state under the multi-field coupling condition cannot be monitored in real time in the prior art. The system comprises a multi-physics field coupling loading system, a multi-field data monitoring system and a multi-field data acquisition system. The system can simulate and apply axial pressure, confining pressure, pore pressure and temperature of an in-situ environment to a rock sample, integrates an acoustic monitoring system, a deformation monitoring system and a CT scanning system to realize multi-dimensional real-time monitoring of rock sample damage, overcomes the limitation of a single monitoring method, realizes multi-system electrical connection by taking an upper computer as a data acquisition center, and realizes multi-dimensional monitoring of rock sample damage. And a multi-parameter model is constructed by fusing sound waves, deformation and CT data, so that the whole-process quantitative evaluation from microcrack initiation to macroscopic fracture is realized, and the damage evaluation is comprehensively performed.

The invention relates to the technical field of mine safety monitoring, and discloses a roadway surrounding rock stability evaluation method, which comprises the following steps: step 1, collecting roadway surrounding rock geological data, step 2, constructing a three-dimensional geomechanical model, step 3, inverting mechanical parameters, step 4, calculating a stability coefficient, and step 5, outputting an evaluation result. According to the method, rock mass types, structural plane occurrence, crustal stress vectors and permeability parameters are integrally collected through geological radar scanning, drilling coring and crustal stress measuring devices, the problem of model distortion caused by single data in a traditional method is solved, deformation of a stress concentration area is accurately captured by adopting a non-uniform grid division strategy, inversion mechanical parameters are combined, and the method is suitable for large-scale popularization and application. The network is trained by using in-situ direct shear and triaxial test data, the inversion efficiency is improved compared with manual trial and error, the whole surrounding rock fracture process is simulated based on a finite element-discrete element coupling algorithm, plastic zone distribution and a comprehensive index S are output, and automatic judgment of the stability level is realized.

The invention discloses a slope settlement data processing method under an infiltration surface effect based on a water-soil coupling model, and relates to the technical field of civil engineering geomechanical analysis. And establishing a water-soil coupling numerical model containing a mutual coupling relationship between water flow permeation and soil deformation. According to the method, the multi-source monitoring data and the sudden change recognition algorithm are fused, so that the recognition precision and real-time performance of the sudden change point of the slope infiltration surface are improved. And a parameter adaptive correction mechanism is introduced, so that the model can dynamically adjust key parameters, and the adaptability to a complex geological environment and the prediction stability are enhanced. Meanwhile, a dynamic processing flow integrating data driving, model calculation and risk identification is constructed, intelligent linkage early warning of the side slope settlement risk is achieved, the landslide accident risk is effectively reduced, and the scientificity and safety of geological disaster monitoring are improved.

The invention relates to the technical field of computer simulation, and discloses a computer simulation-based overlying strata multilevel grouting design optimization method, which comprises the following steps of: constructing a three-dimensional geomechanical model of a goaf according to geological exploration data; calculating development characteristics of each layer in the overlying strata of the goaf, and constructing a grouting bearing layer position of the goaf according to the development characteristics; fracture development characteristics and horizon stress distribution are analyzed; according to fracture development characteristics and horizon stress distribution, analyzing grouting simulation parameters of the horizon of the grouting bearing layer; generating a multi-level layered grouting simulation scheme of the position of the grouting bearing layer; generating a digital track of the position of a grouting bearing layer according to the multi-level layered grouting simulation scheme, and generating a grouting control simulation instruction according to the digital track; and according to the grouting control simulation instruction, multi-level grouting simulation operation is carried out on the position of the grouting bearing layer, and a multi-level grouting simulation result is output. According to the method, the accuracy of the grouting level of overlying strata multi-level design optimization can be improved.

The invention provides a method and system for predicting the uplift bearing capacity of a mud mixed pile. According to the method, modeling is carried out by integrating geomechanics and monitoring data. The method comprises the following steps: firstly, acquiring geometric parameters of a multi-layer heterogeneous soil layer interface, constructing a database through a mechanical test, and improving the reliability by combining gradient recognition and cooperative verification of pile deformation and load data; dividing longitudinal segmentation units, adjusting anti-slip parameters to generate a space mapping table, establishing a debonding dynamic model containing an interlayer retardation effect, simulating a debonding expansion process, and outputting load evolution data. And judging the maximum load of the critical state based on data convergence analysis, and taking the maximum load as a predicted value of the uplift bearing capacity. According to the technical scheme, through dynamic parameter mapping and debonding process simulation, accurate prediction of the uplift bearing capacity of the pile foundation in a complex soil layer is achieved, and the defect that a traditional model is insufficient in characterization of interlayer heterogeneity and dynamic debonding behaviors is overcome.

A geological disasters monitoring method, device, medium and product are provided, which relates to the technical field of geological monitoring. The method includes determining microscopic deformation parameters of an area to be monitored according to remote sensing observation data corresponding to a slope body of the area to be monitored, determining macroscopic deformation parameters of the area to be monitored according to optical remote sensing data and terrain data of the area to be monitored, and determining the landslide remote sensing geomechanical deformation type in the area to be monitored according to material composition, movement mode, slope structure, the microscopic deformation parameters and the macroscopic deformation parameters of the area to be monitored. The present disclosure improves the accuracy of monitoring geological disasters.

The invention relates to the technical field of geotechnical engineering safety monitoring, in particular to a river valley area bedding slope stability monitoring method and related products, and the method comprises the steps: building a three-dimensional geology-mechanics numerical model of a slope; acquiring monitoring data of the slope state in real time; dynamically correcting mechanical parameters in the three-dimensional geology-mechanical numerical model through inversion calculation; evaluating the stability of the slope and outputting early warning information; according to the method, multi-source monitoring data are fused into the numerical model in real time, dynamic inversion and tracking of internal mechanical parameters of the slope are achieved, comprehensive indexes such as the real-time safety coefficient, the main sliding direction deviation angle and the damage evolution rate are calculated, graded early warning is triggered according to the indexes, and the perspectiveness and reliability of early warning are improved.

The invention provides a multi-physics field cooperative regulation and control method in coal mine rock burst prevention and control, and relates to the technical field of coal mine rock burst prevention and control, and the method comprises the steps: synchronously collecting stress field, fracture field and vibration wave field data in real time through a distributed optical fiber sensor network and a micro-seismic monitoring system, and constructing a dynamically updated three-dimensional geomechanical model; based on an adaptive Kalman filtering algorithm, noise reduction multi-source data are fused, a dynamic stress concentration factor and an energy accumulation critical index are extracted, and a rock burst risk probability model is established; a multi-objective optimization algorithm is adopted to generate graded regulation and control instructions of grouting reinforcement, mining speed adjustment and pressure relief drilling, and the graded regulation and control instructions are executed in real time; and iteratively optimizing the model weight by using a transfer learning algorithm in combination with a historical case library to form a closed-loop feedback adaptive prevention and control system. According to the method, the analysis precision of rock mass fracture evolution under complex geological conditions is improved through multi-physics field collaborative perception and dynamic modeling, and risk quantification and real-time regulation and control are realized through multi-algorithm coupling analysis.

The invention discloses a tunnel-landslide mass stability evaluation method based on space-time multi-scale coupling, and belongs to the field of tunnel-landslide masses, and the method comprises the following steps: S1, extracting a feature parameter set and an abnormal event mark set; s2, constructing a three-dimensional geological-mechanical model; s3, space-time multi-scale modeling of multi-physics field coupling is carried out; s4, outputting a stability prediction level by using the constructed ISSA-LSTM-GARCH combined prediction model; s5, generating an early warning in combination with an association rule engine; and S6, knowledge updating and systematic evolution of closed-loop optimization are carried out. According to the tunnel-landslide mass stability evaluation method based on space-time multi-scale coupling, multi-source monitoring data and a multi-physical field coupling model are fused, landslide mass stability under the influence of tunnel engineering is accurately and comprehensively analyzed through high-precision positioning and parameter inversion optimization, and powerful support is provided for engineering decision making.

The invention discloses a non-coal mine safety risk dynamic monitoring and early warning system based on a point-surface fusion technology, and relates to the technical field of mine safety monitoring. The system uses four-dimensional space-time coordinate data of ground surface monitoring points to construct a dynamic ground surface model; dynamically inverting a probabilistic three-dimensional underground geomechanical model from the earth surface by adopting a deep learning large model (DSIM), and quantifying uncertainty; online self-adaptive evolution of the DSIM model is carried out by comparing the difference between prediction and actual observation; integrating a causal inference engine and deeply tracing risk driving factors; according to the method, underground state perspective, risk cause traceability and model self-evolution are realized, and the precision, reliability and intelligent decision support level of monitoring and early warning are remarkably improved.

The invention provides a coal mine high-precision three-dimensional geological modeling method and system based on multi-source heterogeneous data fusion, and relates to the technical field of coal mine geological modeling. The method comprises the following steps: establishing a unified semantic reference system and a time-space coordinate reference, and generating an alignment anchor point set; mapping the multi-source observation data to form an alignment feature set and calculating a source weight; according to a multi-evidence consistency rule and geomechanical prior inversion, a discontinuous geological structure is obtained; constructing an implicit stratigraphic function and applying a boundary jump condition to solve a stratigraphic boundary set; and taking the stratum boundary as a framework, and executing anisotropic joint estimation to obtain a property distribution model and an uncertainty result. According to the method, integrated modeling of the geological structure and the property of the complex structure area is achieved, and the precision, the stability and the credibility of the three-dimensional geological model are remarkably improved.

The invention belongs to the technical field of shale oil and gas development, and particularly discloses a multi-source information fused horizontal well casing deformation risk section prediction method, which comprises the following steps: representing shaft crack zone information; establishing a work area construction model and an attribute model; with shaft crack zone information as a constraint, disturbance is performed on crack information predicted based on seismic data, and a three-dimensional crack network model is established; a work area geomechanical model is established, and crustal stress distribution characteristics in the shaft direction of the horizontal well are obtained; a work area casing deformation comprehensive database is established by combining casing mechanical attribute data and work area fracturing construction parameters, and fault zone activity factors are obtained based on the Mohr-Coulomb criterion; and establishing a stratum-fracture-wellbore model, obtaining a mathematical model of fracture zone activity factors and casing deformation degrees, and dividing casing deformation risk grades. According to the method, accurate recognition of the well periphery crack network and advanced pre-judgment of the well periphery crack activation risk and the wellbore casing deformation can be achieved, and guidance is provided for formulating targeted casing deformation prevention and control measures.

The invention discloses an InSAR (Interferometric Synthetic Aperture Radar) deformation monitoring system for landslide and a method thereof, and relates to the field of geological disaster monitoring. The method has a high-precision deformation monitoring effect, through multi-source SAR data fusion, interference pair screening optimization and multi-source error correction (such as troposphere and ionosphere delay correction), the fidelity of a deformation phase sequence is remarkably improved, and the precision limitation under a complex terrain is overcome; the method has an intelligent geological constraint inversion capability, introduces geological prior knowledge (such as fault and fracture characteristics), enables a deformation field to better conform to the actual geomechanical law through deep learning semantic segmentation and a Bayesian inversion model, and reduces misinformation and missing report. The method has self-adaptive landslide recognition, adopts deformation gradient field calculation and a dynamic threshold segmentation algorithm, automatically recognizes a potential sliding zone boundary, improves the landslide partitioning efficiency, and is suitable for large-range monitoring.

The invention relates to the technical field of geomechanical simulation of tunnel engineering, in particular to a tunnel surrounding rock water immersion weakening fluid-solid coupling simulation method and system.The method comprises the steps that mechanical parameters and seepage parameters of typical tunnel surrounding rock materials are obtained, and then an evolution equation of water immersion equivalent strain along with time is constructed; constructing a water immersion equivalent strain-seepage parameter dynamic correlation model based on the evolution equation and the seepage parameters; a seepage-stress coupling elastic-plastic damage constitutive model is constructed on the basis of a water immersion equivalent strain dynamic evolution model, and coupling circulation of a seepage-stress-damage field under the influence of water immersion degradation is represented on the basis of the seepage-stress coupling elastic-plastic damage constitutive model. The technical blank that bidirectional strong coupling of a seepage field and a mechanical field under water immersion response cannot be realized in the prior art is filled, and a high-precision simulation technical scheme is provided for stability analysis of tunnel surrounding rock in a water-rich environment.

The invention discloses an intelligent analysis method for geomechanical conditions of coal seam surrounding rocks, and belongs to the field of intelligent analysis of the geomechanical conditions of the coal seam surrounding rocks. The intelligent analysis method comprises the following steps: performing time sequence matching processing on historical geological data and real-time monitoring information by adopting a dynamic data integration technology according to a preliminary integration result of multi-source data; determining a unified feature set after multi-source data fusion; acquiring geomechanical condition related data of the unmined area according to the initial prediction model parameters, and performing simulation analysis on the surrounding rock stability to obtain stability prediction distribution of the unmined area; according to the stability prediction distribution of the unmined area, combining a dynamic data integration result, carrying out local correction on the prediction distribution, and determining a final stability prediction result; and for a final stability prediction result, generating a geomechanical condition risk distribution diagram of the unmined area through an intelligent prediction technology, obtaining distribution characteristics of a potential risk area, and completing output of a prediction model.

The invention provides a petroleum drilling geomechanical characteristic estimation method based on deep learning, and aims to solve the problems of high measurement cost and poor real-time performance of shear wave velocity Vs in traditional geomechanical analysis by fusing logging while drilling LWD data and real-time drilling engineering parameters. According to the method, a Transformer model is adopted to carry out depth correction on logging-while-drilling data, depth offset of a drill bit and a logging sensor is eliminated, and real-time drilling parameters such as torque T, bit pressure WOB and drilling speed ROP are combined and input into a multi-layer perceptron MLP network to predict the shear wave speed Vs. And further calculating key geomechanical parameters based on the predicted shear wave velocity Vs. In practical application, the method improves the shear wave velocity prediction accuracy to 97.2%, the mean absolute error MAE of the shear modulus is reduced from 0.186 to 0.059, and the bulk modulus is reduced from 0.189 to 0.040. The method can be used for outputting stratum elastic parameters, optimizing bit pressure, pre-warning well wall instability and adjusting a well track, well drilling safety and efficiency are improved, and meanwhile dependence on an expensive well logging technology is reduced.

The invention provides an intelligent support scheme recommendation method based on an artificial intelligence algorithm, which comprises the following steps: acquiring multi-source heterogeneous geological environment parameters of a target engineering site and real-time dynamic monitoring data flow in a construction process, and constructing a dynamically updated three-dimensional geomechanical model through a geology-construction coupling modeling engine. And performing construction process dynamic risk deduction by using the geological risk assessment artificial intelligence model to generate a risk assessment result. Based on the result, intelligent evolution search is executed in a supporting structure parameter space through a multi-objective optimization artificial intelligence model, a plurality of candidate schemes are generated, screening is carried out in combination with engineering constraint conditions, and a feasible candidate scheme set is formed. And performing multi-dimensional utility evaluation and sorting on the candidate schemes by using the support scheme intelligent sorting artificial intelligence model, generating an optimal support scheme recommendation sequence, and realizing online adaptive optimization through a digital twin feedback loop. According to the method, scientificity, safety and economical efficiency of support design can be improved.

The invention belongs to the technical field of geothermal energy development and geological engineering, and discloses a geothermal reservoir fracture network dynamic modeling method based on geomechanical constraints. The method comprises the following steps: firstly, acquiring multi-source monitoring data of the geothermal reservoir, wherein the multi-source monitoring data comprises rock mass surface deformation data, microscopic damage space-time distribution data and acoustic emission fracture signal data; constructing a microscopic-macroscopic correlation model based on a bonded particle model and a moment tensor theory, and obtaining a characteristic value of rock mass damage evolution; performing three-dimensional fracture source positioning on the acoustic emission fracture signal; constructing a cubic cluster model based on a positioning result, and generating an initial topological structure of the fracture network; dynamically adjusting the geometrical morphology and connectivity of the fracture network through a random walk algorithm and a fracture intersection correction mechanism according to the evolution characteristic value in combination with a geomechanical constraint condition; and finally predicting fracture expansion trends and damage evolution laws under different geomechanical conditions. According to the method, the accuracy and reliability of fracture network evolution prediction are remarkably improved.

The invention provides a hydraulic fracturing crack propagation simulation method and device and electronic equipment, and the method comprises the steps: obtaining the ground stress field distribution of each fracturing section through a geomechanical model according to the geological parameters, logging interpretation and rock mechanics experiment data of a target area fracturing section; utilizing an induced stress field model to simulate induced stress distribution of each fracturing section; obtaining comprehensive crustal stress field distribution according to the crustal stress field distribution and the induced stress distribution; the theoretical crack initiation pressure of each perforation cluster of each fracturing section is calculated according to the comprehensive crustal stress field distribution by means of a perforation cluster crack pressure model, perforation cluster crack initiation data of each fracturing section are determined according to the theoretical crack initiation pressure and the actual crack pressure, and the perforation cluster crack initiation data comprise the perforation cluster crack initiation state and the perforation cluster crack initiation number; and utilizing the multi-cluster crack propagation model to obtain a crack propagation trajectory simulation result according to perforation cluster crack initiation data and an actual pump injection program. According to the method and the device, hydraulic fracture expansion of segmented multi-cluster fracturing can be accurately simulated.

The invention provides a stratified reservoir lamination fracture high-crossing evaluation method and device, and relates to the technical field of oil-gas exploration, and the method comprises the steps: carrying out the combined analysis of a geomechanical model based on a target position of a research area, a first fracture propagation analysis result and a second fracture propagation analysis result, and obtaining a first fracture propagation analysis result and a second fracture propagation analysis result; determining conditions of crack induced bedding opening and crossing expansion under different reservoir and interlayer stress differences and interlayer thicknesses, and drawing a crack height crossing evaluation chart corresponding to the target position by taking the reservoir and interlayer stress differences and the interlayer thicknesses as two-dimensional coordinate axes; and performing layer crossing evaluation before fracturing construction of the to-be-built production block by using the seam height layer crossing evaluation chart. According to the method, the fracture height crossing evaluation chart is determined by combining the formation mechanical characterization, the fracture propagation physical simulation experiment and the multi-cluster fracturing fracture propagation numerical simulation experiment in the horizontal well, then the crossing evaluation of the to-be-built production block is carried out, and the post-fracturing production capacity, the overall production effect of the reservoir and the overall development benefit of the stratified reservoir are improved.

The invention relates to the technical field of geological disaster monitoring and early warning, and discloses a geological disaster early warning system based on multi-source data fusion. The system comprises a data acquisition and preprocessing module, a dynamic coupling modeling module, a space mapping and feature recognition module and a risk analysis and early warning generation module. Firstly, transient disturbance and long-term steady-state components in monitoring data are separated; a dynamic coupling model containing bidirectional geomechanical feedback is constructed, the component fusion proportion is automatically adjusted according to the feedback intensity, and physically consistent fusion data is generated; spatial mapping is carried out by using an adaptive grid, and an effective abnormal feature cluster is identified through parallel scanning and prior geological knowledge constraint; and constructing a causal graph based on the abnormal clusters to carry out risk assessment and early warning. According to the system, physical driving of data fusion and knowledge guidance of anomaly recognition are realized, and the accuracy and reliability of early warning are improved.

The invention relates to the technical field of geological engineering safety risk evaluation, in particular to a regional tectonic stress risk quantitative analysis method for tunnel engineering. The method comprises the following steps: collecting multi-source geomechanical parameters, simulating and inverting a tectonic stress field, and verifying the tectonic stress field; constructing a multi-scale geomechanical model, coupling simulation tectonic stress and gravity stress, and generating a stress space basic layer; utilizing Kriging interpolation and inversion decomposition to obtain a stress value and a directional diagram layer; calculating an included angle between the maximum principal stress direction and the tunnel axis, and performing vector decomposition to obtain a vertical stress component; and carrying out standardized normalization on the factors, determining a weight calculation risk value, and finally generating a tectonic stress risk quantitative grading graph and carrying out GIS visual rendering. The tunnel engineering-oriented risk quantitative analysis mechanism is constructed by retaining the directivity and spatial heterogeneity characteristics of the tectonic stress tensor, and the authenticity, resolution and engineering applicability of tectonic stress identification are remarkably improved.

The invention relates to the technical field of geological information, and discloses a precise positioning method and system based on geological mineral product three-dimensional modeling, and the method comprises the steps: deploying a laser ranging array, a micro-seismic array and a fiber grating sensing array, and synchronously collecting multi-source deformation and stress data; after space-time alignment and filtering, an improved ICP algorithm is adopted to reconstruct a millimeter-level precision three-dimensional point cloud model; a safety coefficient cloud picture is calculated by combining a geomechanical constitutive equation, and a risk area is automatically delineated according to a three-level threshold value; and closed-loop control instructions such as voice alarm, thermodynamic diagram pushing, grouting coordinates and avoiding paths are generated. The system is composed of a sensing deployment unit, a data preprocessing unit, a point cloud reconstruction unit, a mechanical analysis unit, a risk delineation unit and an instruction distribution and execution unit. Millimeter-level positioning, sub-hour-level early warning and full-automatic intervention of goaf deformation are achieved, the early warning accuracy rate exceeds 95%, the emergency response is shortened to the minute level, and mine safety and mining efficiency are improved.

The invention provides a method for determining advanced controllable roof cutting parameters of a thick and hard roof of a coal mine stope face, which comprises the steps of engineering general situation field investigation and survey, in-situ geomechanical test, goaf roof thickness / thin plate theoretical analysis, coal pillar or filling body vertical load theoretical analysis, numerical simulation calculation and engineering test verification. Analyzing the mechanical behavior of the working face roof based on a plate theory, verifying the correctness of a theoretical model through measured data, and changing boundary conditions to predict the mechanical behavior of the roof after roof cutting; the method comprises the following steps: analyzing the vertical load of a coal pillar or a roadside support body after roof cutting and the influence rule of roof cutting height and angle on the roadside support body through a mechanical model, and preliminarily obtaining better roof cutting parameters; by establishing a numerical model of different topping parameter combinations, different performance parameters are used for comparing and evaluating different topping parameters, so that the optimal topping parameter is determined; according to the method, advanced controllable roof cutting of the hard roof of the coal seam is achieved, and the mine pressure treatment effect in mining is predicted.

The invention provides a method for predicting ground subsidence caused by ground stress change in geothermal exploitation, which comprises the following steps: collecting geological survey data of a target geothermal exploitation area, and constructing a three-dimensional geomechanical model; based on the constructed three-dimensional geomechanical model, simulating crustal stress evolution processes in different mining stages by adopting a numerical simulation method to obtain crustal stress tensor time sequence change data; inputting the crustal stress tensor time sequence change data into a three-dimensional geomechanical model as a boundary condition, and calculating the deformation of each rock stratum in the vertical direction to obtain a ground surface settlement estimated value; constructing a crustal stress-settlement prediction model based on the nonlinear mapping relationship between the crustal stress tensor time sequence change data and the settlement estimated value, and training; and inputting subsequent terrestrial heat exploitation scheme parameters, and predicting a future ground surface settlement trend by using the trained ground stress-settlement prediction model. The method is wide in application range and can be suitable for ground subsidence prediction of the geothermal exploitation area under different geological conditions.

The invention discloses an intelligent well completion optimization design method and device based on multi-objective optimization, and the method comprises the steps: carrying out the clustering of a first data set according to a weighted clustering model, carrying out the evaluation of the geological sweet spots of all clusters after clustering, and obtaining the evaluation result of the geological sweet spots, the first data set comprises physical property parameters of each reservoir along the depth of the horizontal well, and the weighted clustering model is constructed according to the weight of the physical property parameters of each reservoir; according to an engineering dessert evaluation result and a preset segment length constraint, a fracturing segment is divided, and the engineering dessert evaluation result is determined according to geomechanical parameters; and in the divided fracturing sections, solving a multi-objective function constructed according to the geological dessert evaluation result, the engineering dessert evaluation result and the preset cluster spacing constraint, and performing well completion optimization design according to the objective solving result of the multi-objective function. According to the method, well completion optimization design can be efficiently, finely and intelligently carried out.

The invention relates to the technical field of geological disaster early warning, and discloses a geological deformation early warning method and system based on AI vision, and the method comprises the steps: obtaining surface micro-deformation features through an AI vision system, and constructing a geological map structure network; fusing a nonlinear geomechanical equation in a graph neural network to realize physical constraint driven feature extraction; creating a multi-dimensional graph structure model representing different depth layers, and realizing cross-layer information transmission through a physical information guide type graph attention mechanism; deploying a graph neural network of a Bayesian probability framework to carry out geological stress field distribution modeling, and quantizing prediction uncertainty; and finally, generating intelligent early warning decision information with risk grade division. According to the method, the AI vision and the physical constraint graph neural network are combined, accurate inference of the underground stress field is realized, the uncertainty can be quantitatively predicted, and the reliability and timeliness of geological disaster early warning are improved.

A method for evaluating shale compressibility logging based on game theory, comprising: step 1 of preparing rock core data, conducting experiments, and obtaining rock mechanical parameters and experimental rock physical parameters; step 2 of establishing a relationship between the rock mechanical parameters and the experimental rock physical parameters; step 3 of establishing a relationship between the rock mechanical parameters and the experimental rock physical parameters to predict the formation pore pressure based on the well logging rock physical parameters; step 4 of establishing a relationship between the laboratory and field logging rock physical parameters; step 5 of constructing a geostress calculation model for the research block formation and further obtaining related parameters; step 6 of obtaining the main controlling factors of shale compressibility geomechanics by normalizing the oil recovery intensity; step 7 of obtaining the main expression parameters and ranking of the relatively independent shale compressibility; and step 8 of determining the shale compressibility index. [Effects] A method for evaluating shale compressibility has been established with high accuracy.

The invention discloses a fracture prediction method based on well-to-seismic joint inversion and heterogeneous mechanical modeling, and the method comprises the following steps: collecting and preprocessing basic geological data of a target block; building a high-resolution reservoir rock physical model; establishing a three-dimensional geologic model of the heterogeneous mechanical body; carrying out fracture sensitivity prediction and spatial distribution modeling; and crack network three-dimensional visualization and development decision support. According to the method, well-to-seismic joint inversion, heterogeneous geomechanical modeling and artificial intelligence prediction technologies are deeply fused, and a systematic, intelligent and refined crack prediction solution is formed. Compared with a traditional method, the method has remarkable advantages in the aspects of crack space identification precision, multi-field coupling analysis capability and intelligent level, and provides scientific basis and technical support for efficient development of oil and gas reservoirs.