10847 results about "Geophysics" patented technology

The invention provides a slope deformation monitoring method and device based on multi-source data fusion, and relates to the technical field of dam slope safety monitoring. The method comprises the steps that a multi-source monitoring system composed of a global satellite signal receiver, a measuring robot and an interference synthetic aperture radar is arranged in a dam slope area; according to the collected slope deformation disturbance parameters, performing monitoring area selection division on a dam slope area; determining a data fusion weight corresponding to each data fusion observation area; collecting multi-source monitoring data in each data fusion observation area; and based on the determined data fusion weight, performing weighted fusion processing on the multi-source monitoring data in the selected area to generate a slope deformation monitoring result. According to the technical scheme, fusion of multi-source monitoring data is realized through region division, the reliability, comprehensiveness and environment adaptability of slope deformation monitoring data are improved, and the stability, accuracy and precision of a slope deformation monitoring result are improved.

The invention discloses a loess tunnel surrounding rock deformation monitoring method, and relates to the technical field of civil engineering and geological engineering, and the method comprises the steps: integrating a spiral winding type optical fiber sensor, a double-cavity humidity compensation vibrating wire sensor and a microseismic array, and capturing surrounding rock strain, vibration and geological activities; the vibrating wire sensor suppresses humidity interference through a silicone oil damping medium and self-adaptive excitation frequency, and the optical fiber sensor is fixed through a pre-embedded silica gel sleeve to adapt to surrounding rock deformation; edge computing nodes are deployed on the inner wall of the tunnel, an FPGA chip and a lightweight GRU model are integrated, optical fiber strain, a micro-seismic energy spectrum and laser point cloud displacement field data are fused in real time, the strain gradient is analyzed, and a crack propagation probability cloud picture is generated; redundant optical fiber link switching is combined with a six-degree-of-freedom mechanical arm to realize breakpoint self-repairing, and a self-cleaning air curtain is integrated to inhibit dust adhesion; and constructing a geological parameter library based on a BIM-GIS fusion platform, driving a finite element-discrete element coupling model to dynamically update boundary conditions, and predicting surrounding rock deformation and collapse risks.

The invention provides an underground cavern surrounding rock parameter collaborative sensing method and system based on multi-source data fusion, and the method comprises the steps: firstly deploying a sensor group comprising an optical fiber strain sensor, a micro-seismic monitoring array, a three-dimensional laser scanner and an acoustic emission sensor, the optical fiber strain sensor is arranged along the axis of a cavern, the micro-seismic monitoring array is deployed according to a triangular network, and the three-dimensional laser scanner is arranged along the axis of the cavern; performing time synchronization on the sensor group through a synchronization pulse signal, establishing a local coordinate system at a central point of a cavern entrance, uniformly collecting data, generating a time-aligned data stream and a space-unified data set, and triggering associated sensors to enter a hierarchical response collection mode according to a strain rate and a vibration signal; and generating a multi-modal monitoring data set, finally carrying out dynamic weight distribution and conflict resolution processing on the multi-modal monitoring data set, extracting surrounding rock deformation characteristics and fracture event density, and outputting a surrounding rock stability evaluation result, thereby realizing underground cavern surrounding rock parameter collaborative perception and stability evaluation.

The invention discloses a landslide hidden danger point displacement monitoring system applying multi-source data fusion, and the system comprises a multi-source sensing unit which comprises a spaceborne radar sensing module which is used for obtaining large-range ground surface deformation data through a synthetic aperture radar; the earth surface deformation sensing module is used for monitoring earth surface displacement in real time through a double-frequency GNSS receiver and an optical fiber grating sensor; the underground stress sensing module is used for acquiring the stress change of an underground rock-soil body through a micro-seismic monitoring array and a distributed optical fiber sensor; and the edge calculation unit comprises a dynamic weight fusion module which is used for dynamically distributing the weight of the multi-source sensor according to the geological state and generating high-precision fusion displacement field data. According to the invention, through multi-source data fusion, model parameter real-time updating and a closed-loop optimization mechanism, bottlenecks of a traditional monitoring system in aspects of data quality, model precision and response efficiency are broken through, and data support is provided for accurate early warning and intelligent emergency of landslide disasters.

The invention discloses a seabed karst stratum tunnel shield data monitoring and analyzing method and system. The method comprises the steps that shield construction mechanical parameters, karst stratum acoustic emission signals and seawater osmotic pressure data are synchronously collected; shield construction mechanical parameters, karst stratum acoustic emission signals and seawater osmotic pressure data are subjected to seepage-stress coupling constraint, a hydraulic connectivity strength index is generated through fracture network seepage tensor inversion, and the filler migration risk level is judged based on pore water pressure dynamic mutation characteristics. And fusing the cutterhead torque frequency spectrum characteristic and the propulsive force fluctuation characteristic to generate a shield disturbance entropy value. According to the method, the hydraulic connectivity index is generated through seepage stress coupling inversion, the grouting path and the rheological parameters are dynamically optimized based on the fracture probability field, shield tunneling, seepage sudden change and grouting prevention and control cooperation is achieved, and the problem of prevention and control disjunction is radically solved.

The invention relates to the technical field of geological disaster prevention and control, in particular to a rock engineering slope stability classification method. According to the technical scheme, the method comprises the following steps: obtaining spatial distribution characteristics of a slope structural plane through combined detection of three-dimensional laser scanning and a geological radar, and establishing a quantitative index system containing occurrence, density and connectivity of the structural plane; the method comprises the following steps: acquiring a fracture signal in a slope in real time by adopting a micro-seismic monitoring system, and extracting a micro-seismic event energy release rate, a dominant frequency offset and a seismic source mechanism parameter through time-frequency analysis; and constructing a geologic structure evolution inversion model, reconstructing a geologic structure evolution process based on the regional geologic database and the field drilling data, and calculating the distribution characteristics of the residual stress field of the structure. According to the method, comprehensive, accurate and real-time monitoring and classified evaluation of the rock engineering slope stability are realized, potential risks can be effectively predicted, a scientific and accurate decision basis is provided for slope support and treatment, and the safety and stability of the rock engineering slope are greatly guaranteed.

The invention relates to the technical field of geophysical exploration, and particularly discloses a tunnel surrounding rock stability automatic monitoring and early warning method and system. The method comprises the steps that surrounding rock microseismic signals, convergence displacement and osmotic pressure data are collected through a space-time synchronization array to generate a multi-source fusion data set; based on a dynamic constitutive model separation frequency dispersion effect, extracting correlation characteristics of a microseismic event rate and a displacement rate; generating an instability energy density index; dynamically switching impact or creep damage criteria according to the deformation behavior of the surrounding rock; inputting the indexes into corresponding criteria to generate a damage state result; and if the result exceeds the threshold value, verifying the spatial focusing property of the micro-seismic event cluster, and outputting an early warning instruction when the focusing degree exceeds the critical value. Through multi-source fusion and a dynamic criterion mechanism, the accuracy of tunnel surrounding rock instability early warning is remarkably improved.

A stability assessment method of roadway surrounding rock includes: obtaining actual stratum rock parameters; establishing a two-dimensional geological model through numerical simulation based on a drill core columnar diagram and the actual stratum rock parameters; changing influencing factors, and recording amounts and acceleration values of deformation of roadway sidewalls, and whether failure occurs to obtain dynamic response characteristics of roadway surrounding rock, combining the changed influencing factors and the dynamic response characteristics as labels to obtain a dataset, and obtaining multiple datasets including the dataset; dividing the multiple datasets into a training set and a validation set, inputting the training set into a PSO-BP neural network and a GA-SVM deep learning model to obtain a preliminary stability assessment model, and adjusting and validating the preliminary stability assessment model by the validation set to obtain an optimized stability assessment model; and using the optimized stability assessment model to assess roadway stability.

The invention provides a road slope data monitoring method under a complex geological condition, and relates to the technical field of road slope monitoring, and the method comprises the steps: carrying out the temperature compensation of a change rate, analyzing the thermal expansion characteristic of a material, calculating the deformation caused by the temperature change, correcting the monitored side length, and generating a temperature compensation side length; according to the temperature compensation side length and the surrounding rock rheological equation, correcting the two adjacent side lengths through the strain difference of the adjacent sides so as to obtain the final side length; combining the final side length with the reference interior angle to generate a topological structure; based on the topological structure, constructing a three-dimensional deformation index matrix containing a diagonal displacement difference, an adjacent side curvature ratio and an interior angle variation coefficient; and inputting the index matrix, the support structure strain space-time matrix and the rock mass fragmentation tensor into a space-time attention graph neural network together, and outputting a deformation evolution trend including a diagonal displacement difference, an adjacent side curvature ratio and an interior angle variation coefficient. According to the invention, high-precision real-time monitoring can be realized.

The invention discloses a geothermal field parameter inversion calculation method, device and system, and a storage medium. The method comprises the following steps: establishing a geophysical stratified model; through Monte Carlo sampling of preset parameter spaces of the crustal heat generation rate and the heat conductivity, a temperature value is calculated in combination with a heat conduction equation, and a Gaussian likelihood function evaluation model is constructed to predict the matching degree of the temperature and the actually measured temperature; obtaining the optimal estimation of the thermal parameters, a confidence interval and a correlation matrix among the parameters based on the posterior probability distribution; and according to the correlation matrix, taking a high-confidence result generated by Monte Carlo inversion as priori knowledge of a physical guidance neural network PINNs, and finally outputting a thermal parameter spatial distribution prediction result of the target area through parameter initialization constraint, output layer range limitation and a physical regularization loss item. By adopting the technical scheme of the invention, the defects that the existing actually measured geothermal field parameters are rare and the regional characteristics cannot be described and the geophysical joint inversion of the geothermal field parameters cannot be realized in the prior art are overcome.

The invention belongs to the technical field of rock freeze-thaw damage prediction, and relates to a deep learning rock freeze-thaw damage prediction method based on physical constraints, which is used for improving the physical consistency and prediction precision of a rock freeze-thaw damage prediction model. According to the method, a physical constraint formula is introduced into a data-driven deep learning model, and organic unification of data fitting and physical rationality is realized by using an adaptive weight strategy. The prediction method comprises the steps of data acquisition, data set generation, network construction, physical constraint mechanism formula design, rock freezing and thawing experiment observation or theoretical formula derivation, design of a formula reflecting evolution of various physical properties, model training and prediction output. The deep learning rock freeze-thaw damage prediction method based on the physical constraint has the advantages that generalization ability is remarkably improved, physical continuity and consistency are higher, multi-parameter and multi-source data are comprehensively applied, a staged self-adaptive training strategy is adopted, cost and resources are saved, operation is easy and convenient, and application and popularization are convenient.

The invention discloses a coal and rock mass fracture instability multivariate signal fusion analysis method, and belongs to coal and rock mass analysis. The method comprises the following steps: carrying out time-frequency domain processing on an acoustic emission signal to obtain an accumulated ringing characteristic value # imgabs0 # and an accumulated b characteristic value # imgabs1 #; a main control frequency characteristic value # imgabs2 # and an amplitude characteristic value # imgabs3 # are accumulated; a spatial characteristic value # imgabs4 # of acoustic emission; fitting a fitting function # imgabs7 # from the characteristic value # imgabs5 # to the characteristic value # imgabs6 # respectively; according to the fitting function # imgabs8 #, calculating a correlation coefficient matrix R between the characteristic values # imgabs9 # to # imgabs10 #; according to the matrix R, determining a weight coefficient # imgabs11 # of each characteristic value; a first-order derivative function # imgabs13 # and a second-order derivative function # imgabs14 # of the fitting function # imgabs12 # are obtained, and according to the first-order derivative function # imgabs15 # and the second-order derivative function # imgabs16 #, a demarcation time point # imgabs17 # in the coal and rock mass damage process is determined; and the boundary time point # imgabs19 # is corrected by using the weight coefficient # imgabs18 #, and a corrected boundary time point # imgabs20 # is obtained. In order to solve the problems that an existing coal and rock mass fracture instability judgment index is single, and coal and rock mass fracture instability early warning is low in single index precision, the early warning precision is improved through multi-element signal fusion.

The invention relates to the technical field of oceanographic engineering surveying and mapping, and provides an oceanographic engineering surveying and mapping deep sea terrain reconstruction method, which comprises the steps of multi-modal data synchronous acquisition, frequency domain feature cross enhancement, dynamic convolution feature fusion, inverse projection terrain reconstruction and terrain credibility verification. According to the invention, an acousto-optic multi-mode fusion technology is adopted, and the advantages of acoustic penetrability and optical high resolution are combined, so that the complex terrain detail capturing capability is improved; the dynamic convolution network adaptively adjusts convolution kernel parameters through frequency domain energy, the multi-scale feature fusion effect is enhanced, and the accuracy of terrain texture expression is improved; according to the motion distortion compensation method, carrier attitude drift is corrected in real time through inertial navigation data, and the geometric fidelity of a reconstruction model is guaranteed. The method is suitable for a deep sea complex environment, and provides high-precision terrain reconstruction method support for ocean engineering surveying and mapping and ocean resource exploration.

The invention relates to the technical field of coast engineering, in particular to a beach change evolution inversion method combining numerical simulation and actually measured data, which comprises the following steps: S1, acquiring an actually measured shoreline data set of a current period; s2, establishing a wave-tidal current-sediment coupling numerical model; s3, outputting a simulated shoreline data set; s4, performing spatial matching on the actually measured shoreline data set and the simulated shoreline data set to generate a spatial discrete residual field; s5, taking the spatial discrete residual field as a constraint condition, and reversely solving an optimal hydrodynamic parameter combination; and S6, inputting the optimal hydrodynamic parameter combination into the wave-tide-sediment coupling numerical model, and outputting the beach evolution form in the future period. According to the method, dynamic coupling of the hydrodynamic parameters and the beach evolution process is realized by constructing an inversion optimization mechanism based on actual measurement data driving, and the accuracy of shoreline change simulation and the reliability of prediction are greatly improved.

A heat source inversion-based tunnel high-temperature heat hazard advanced geological detection method and system. The method comprises: by means of multi-view joint observation of "rock wall and drilling", extracting two kinds of collected temperature data to form a new sequence, carrying out inversion interpretation on the sequence, constructing a least square-based three-dimensional heat source inversion objective function and an inversion equation, and solving for the inversion equation; and on the basis of a solution result, forming a heat source and temperature field imaging result graph of high-temperature heat hazard detection within a detection area range. The present invention achieves effective positioning and capturing of a high-temperature heat source, high-temperature heat hazard level division and heat hazard risk evaluation, and provides a reference basis for determining a tunnel design and construction scheme.

The present invention relates to the technical field of mine rock slope analysis, and in particular to a freeze-thaw damage analysis method and system for mine rock slopes. The method comprises the following steps: selecting mine rock slope samples, performing freeze-thaw cycle tests on the mine rock slope samples, and obtaining rock freeze-thaw test information; on the basis of the rock freeze-thaw test information, setting displacement analysis indices, and on the basis of the displacement analysis indices, obtaining displacement variations of rock slopes under freeze-thaw cycles; on the basis of the rock freeze-thaw test information, analyzing plastic damage conditions and mine safety coefficients of the rock slopes under the freeze-thaw cycles; on the basis of the rock freeze-thaw test information, establishing a stress analysis model, and by means of the stress analysis model, obtaining stress distribution conditions of the rock slopes under the freeze-thaw cycles; and by combining the displacement variations, the plastic damage conditions, the mine safety coefficients and the stress distribution conditions, analyzing damage results of the mine rock slopes. In the present invention, multi-objective analysis of freeze-thaw damage conditions of mine rock slopes is performed, thereby ensuring the stability of the rock slopes.

The invention provides a while-drilling formation pressure early warning method and device based on model prediction, equipment and a medium, and relates to the technical field of low-carbon mining, and the method comprises the steps: in a pre-drilling stage, based on seismic data, adjacent well historical data and design data, analyzing and generating prediction risk data of a target monitoring well; in the drilling process, actual formation pressure data are calculated in real time by using drilling data collected for a target monitoring well in real time, and the actual formation pressure data are compared with the predicted risk data; in the drilling stage, a pressure safety window is depicted based on the predicted risk data, the cycle equivalent density of the target monitoring well calculated in real time is compared with the safety window, and the drilling safety risk is recognized and analyzed; and after drilling is finished, summarizing the predicted risk data, the actual formation pressure data and the drilling safety risk, and updating and iterating the model algorithm through the summarized data. The method has the effect of improving the accuracy of formation pressure early warning while drilling in the petroleum drilling process.

The invention provides a tunnel disaster source multi-attribute joint inversion method and system based on physical property constraint, and relates to the technical field of tunnel engineering and joint inversion, and the method comprises the steps: constructing a tunnel face three-dimensional geologic model, applying controlled disturbance to surrounding rock physical property parameters, analyzing the change characteristics of earthquake and electromagnetic observation response, and obtaining a tunnel face three-dimensional geologic model; establishing a quantitative mapping relation between the surrounding rock physical property parameter disturbance quantity and the multi-field response signal variable quantity; constructing a multi-dimensional sensitivity evaluation index, and generating a joint sensitivity result; the surrounding rock units are identified and divided, differentiated partition rock physical relationship constraints are constructed, and a physical multi-attribute inversion target of joint inversion is determined based on the partition rock physical relationship constraints; and on the basis of a physical multi-attribute inversion target, a multi-source joint inversion target function is constructed in combination with the joint sensitivity result, joint solving and iterative updating are carried out, and a tunnel face advanced inversion result is output. According to the invention, calamity source fine identification and risk quantitative evaluation in front of the tunnel face during the tunnel construction period are realized.

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 provides an ocean near-surface sub-mesoscale process flow field inversion method and device. The method provided by the invention comprises the following steps: screening an ocean near-surface sub-mesoscale representative sea area; obtaining the structure image information of the frontal surface and the filament of the phytoplankton in the marine sub-mesoscale process; acquiring displacement velocity field information at the same position; the structure image information and the displacement velocity field information are matched, and a first training sample set is constructed; correcting the first training sample set based on the second data set and the third data set to obtain a second training sample set; training the initial model by using the second training sample set to obtain a flow field inversion model; obtaining a plurality of sub-mesoscale sea surface water color images of the sea area to be detected; and processing the sub-mesoscale sea surface water color image by using the flow field inversion model to obtain a displacement velocity field. The invention provides an ocean near-surface sub-mesoscale process flow field inversion method and device. The method and device are used for solving the problem that a current ocean flow field inversion algorithm is not high in sub-mesoscale process inversion precision.

The invention relates to the technical field of geothermal drilling monitoring management, in particular to a construction monitoring system and method for geothermal drilling. The method comprises the following steps: constructing a state variable set, quantifying structural disturbance intensity by adopting a disturbance derivative method, normalizing the structural disturbance intensity, and defining a state transition tensor mapping behavior influence coefficient; in combination with the high-order derivative of the disturbance trend function and the behavior collaborative change matrix, an offset risk factor is generated through fusion for early warning; dividing a well drilling area into three-dimensional grids, calculating local stress potential energy, adjusting weight through a dynamic sensitive belt, and generating a risk distribution diagram through smooth filtering; performing closed-loop dynamic regulation and control by using risk potential energy centroid coordinates and gradient field inversion intervention vectors for medium and high risk areas; and through multi-period risk potential energy tensor analysis, calculating the matching degree of a self-healing index and a stable cone region, evaluating the self-healing capability of the system and feeding back a regulation and control strategy. According to the invention, a closed-loop monitoring and active control system for nonlinear risks of geothermal drilling is formed.

The invention discloses an intelligent reconstruction and prediction method and system for an ocean three-dimensional flow field, and relates to the technical field of data processing, and the method comprises the steps: obtaining the multi-source observation data of an ocean through a large language model and an edge monitoring device; preprocessing and fusing the multi-source observation data to obtain fused observation data; taking the target observation parameters in the fused observation data as nodes, and taking the space-time correlation and physical quantity coupling relationship among the target observation parameters as edges to construct a space-time correlation map; reconstructing and determining reconstruction data corresponding to the multi-source observation data according to the space-time correlation atlas; the three-dimensional flow field of the ocean is obtained through prediction according to the reconstruction data, and a visual three-dimensional flow field is output. According to the method, the multi-source observation data are fused and reconstructed, and the accuracy of predicting the ocean three-dimensional flow field can be improved.

The invention provides a deep geologic body occurrence characteristic quantitative representation modeling method and system, and the model focuses on the multi-physics field occurrence environment of rock mass material composition, structural characteristics, stress distribution and the like under the continuous mining condition of a deep underground metal mine. An information expression framework capable of crossing a'microcosmic-experimental-engineering 'multi-level spatial scale is constructed, microcosmic rock core mineral components and crack information, laboratory mechanical response parameters and structural surface shear characteristics and macroscopic fault system and stress disturbance data reflected by microseismic events are introduced, a heterogeneous data fusion method is comprehensively applied, and a microcosmic-experimental-engineering multi-level spatial scale is constructed. A three-dimensional tensor model with dynamic evolution capability and physical interpretation capability is established, high-precision, dynamic and multi-scale comprehensive modeling of a complex deep geologic body occurrence environment is realized, and the model has the characteristics of clear information hierarchy, high fusion precision, strong physical interpretability and the like. And dynamic perception and scientific research and judgment of geologic mass mechanics and structure states can be realized in a complex deep environment.

The invention relates to the technical field of hydraulic fracturing, in particular to a method for evaluating effectiveness of fracture parameters of artificial fracturing of a horizontal well. The method comprises the following steps that information collection based on ground process parameters and underground dynamic parameters is conducted on the horizontal well artificial fracturing construction process, and fracturing working condition data are obtained; according to the fracturing working condition data, the fracture expansion of the horizontal well is monitored in real time, digital conversion processing is conducted, and real-time fracture monitoring data is generated; performing micro-seismic signal analysis on the real-time crack monitoring data, and performing crack network space distribution calculation to generate crack network distribution data; performing reservoir stress field dynamic evolution analysis according to the fracture network distribution data to generate stress field distribution data; and carrying out propping agent migration trajectory tracking according to the stress field distribution data to generate propping agent distribution data. According to the method, the reservoir stress field dynamic evolution analysis and the proppant migration mechanical model are combined, and the effectiveness of the fracture parameters can be evaluated more accurately.

The invention relates to the technical field of layered surrounding rock inversion analysis, and discloses a layered surrounding rock three-dimensional crustal stress field inversion intelligent analysis system and method, and the system comprises a dimensional geological value module, an intelligent inversion analysis module and an inversion result verification module. The method comprises the steps of collecting geological data in target layered surrounding rock; carrying out normalization processing on the geological data, and carrying out sensitivity analysis; constructing a three-dimensional geologic model, and performing numerical simulation; a crustal stress field inversion intelligent analysis model is generated based on the three-dimensional geologic model; training the crustal stress field inversion intelligent analysis model by using the training sample; inputting the real-time geological data into the crustal stress field inversion intelligent analysis model to obtain a crustal stress inversion analysis result; carrying out visual output on the ground stress analysis result; and adjusting the crustal stress field inversion intelligent analysis model according to the actually measured data. Scientific ground stress field analysis basis can be provided for complex projects such as tunnel engineering, underground engineering and hydropower stations.

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.

A method of constructing an injection well for a geothermal energy system comprising determining a fracture area of an injection well with a curved wellbore by inputting the curved wellbore path, a set of formation properties, and a fracturing operation, into a fracturing model. The curved wellbore path can promote fracture interference between fracture stresses extending from the injection wellbore. A production model can determine an economic value of the production fluids produced from at least one production well by determining a contact time for the injection fluids to traverse the formation. A design process can iterate the curved wellbore path of the injection well to produce a production fluid with an economic value above a threshold value.

The invention discloses an earthquake prediction method and system based on multi-physics coupling and quantum optimization, and relates to the technical field of earthquake prediction, and the method comprises the following steps: obtaining earth surface deformation observation data, geomagnetic observation data, gravity gradient data, and infrasonic wave monitoring data, and carrying out the preprocessing; performing multi-physics field coupling calculation on the preprocessed earth surface deformation observation data, geomagnetic observation data, gravity gradient data and infrasonic wave monitoring data; optimizing the fault network by adopting a D-Wave quantum annealing technology to find a lowest energy state to obtain a quantum optimization result; and generating an earthquake probability distribution diagram, an earthquake magnitude-time window table and a fault stress field three-dimensional model, thereby greatly expanding the breadth and depth of data, and remarkably improving the comprehensiveness of earthquake prediction.

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 provides a shield adaptability adjusting method based on a stratum structure, which comprises the following steps: acquiring geological parameters of a construction area of a shield tunneling machine through drilling and geophysical prospecting, and arranging sensors at key positions of the shield tunneling machine to acquire construction parameters of the shield tunneling machine in real time; a convolutional neural network CNN is adopted to analyze the geological parameters to identify stratum features, and a geological model is constructed based on the identified stratum features; constructing a disaster risk index system, and predicting a disaster risk based on the geological model and the construction parameters by adopting Logistic regression and a random forest algorithm; according to the predicted disaster risk, the cutterhead configuration of the shield tunneling machine is dynamically adjusted, and tunneling parameters are optimized or a muck improvement scheme is adopted; by monitoring geological parameters, construction parameters and environmental changes in real time, a multistage early warning mechanism is adopted to trigger emergency response measures, and construction safety is guaranteed. According to the method, the safety and efficiency of shield construction can be improved, the geological disaster risk is reduced, and reliable technical guarantee is provided for underground space development.