265 results about "Geological structure" patented technology

The invention relates to the technical field of geological disaster monitoring, and discloses a landslide dynamic simulation monitoring and early warning method based on multi-source sensing fusion, and the method comprises the steps: collecting multi-source data of a landslide body through a plurality of heterogeneous sensors, and enabling the multi-source data to be in space-time alignment after preprocessing; building a multi-parameter fusion model fusing a displacement field, a mechanical field and an environment field based on the preprocessed data, enabling the multi-parameter fusion model to output a deformation rate and a stability coefficient, and dynamically adjusting the weights of the displacement field, the mechanical field and the environment field according to a landslide evolution stage; predicting a future deformation trend of the landslide mass in combination with a geological structure and historical data, comparing a stability coefficient with a dynamic safety threshold to judge a risk level, and generating early warning information; and dynamically correcting a reference weight coefficient in the model based on the deviation between the monitoring data and the model output, so that the model is adaptively optimized. The problems of single monitoring dimension and static model solidification in the prior art are solved, and accurate and adaptive monitoring and early warning of the risk state of the landslide mass are realized.

The invention discloses a post-stack seismic data denoising method based on multi-dip-angle structure guided filtering, and belongs to the field of seismic data denoising, and the method comprises the following steps: carrying out the processing of input seismic data through guided filtering, and obtaining a fault likelihood attribute; dividing the seismic data into a fault region and a continuous stratum region based on fault likelihood attributes; in the fault region, performing filtering processing on the seismic data by using an edge-preserving smoothing algorithm to obtain a filtering result of the fault region; in the continuous stratum area, calculating a local inclination angle of the seismic data, and performing filtering processing on the seismic data by adopting a structure guiding filtering algorithm which performs smoothing along the direction of the local inclination angle to obtain a filtering result of the continuous stratum area; and fusing the filtering result of the fault region and the filtering result of the continuous stratum region to obtain final de-noised seismic data. According to the method, efficient noise suppression can be performed on post-stack seismic data, and meanwhile, the protection capability on a complex geological structure is 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 provides a geological disaster intelligent early warning method based on fusion of a physical information neural network and space-air-ground monitoring, and the method comprises the following steps: S10, obtaining geological structure features of different depths under the ground of a city, and recognizing the spatial distribution and thickness of an underground abnormal body; acquiring a surface deformation time sequence, crack and landform information, a three-dimensional point cloud and a continuous vibration signal of a surface-shallow stratum; s20, constructing a three-dimensional twin substrate, performing space-time alignment and resampling on multi-source heterogeneous data, mapping the data to a three-dimensional grid of a unified coordinate system, and extracting and fusing geological disaster precursor features; s30, taking the generated fusion feature field as an input training neural network model, carrying out geological disaster forward prediction and parameter inversion, and outputting future stability probability distribution, a potential slip plane and key parameter evolution; and S40, adaptively adjusting a risk threshold and an early warning rule, constructing an incremental data set, and carrying out periodic incremental training and parameter optimization on the physical information neural network in the step S30.

The invention discloses a geological modeling method for fusing remote sensing and seismic data based on a multi-mode auto-encoder, and the method comprises the steps: collecting a remote sensing image covering a target area and seismic exploration data, and converting the attribute of the seismic exploration data into a resolution consistent with the remote sensing image; respectively extracting remote sensing image features and seismic attribute features by using a parallel double-branch coding structure of a multi-mode encoder; a fusion module is arranged in the middle layer of the remote sensing image encoder and the seismic attribute encoder, fusion is carried out in the fusion module, remote sensing images and seismic data are reconstructed by using a decoder based on fusion features, and difference data between reconstructed data and the remote sensing images and the seismic data are calculated based on a combined loss function introducing regular terms. Training a multi-modal encoder by using the difference data to obtain an encoding feature and a difference heat map; and on the basis of the coding features and the difference heat map, key geological structure region identification and visual display are carried out, and key geological structures comprise faults and lithology.

The invention discloses an engineering geology grouting reinforcement device, and relates to the field of geology grouting reinforcement, the engineering geology grouting reinforcement device comprises a mounting rack, the mounting rack is fixedly connected with a first telescopic driving part, the output end of the first telescopic driving part is fixedly connected with a mounting plate, and the mounting plate is fixedly connected with a grouting pipe. The grouting pipe is used for pressurizing and grouting, so that the grout enters a reinforcing gap under the action of pressure; after filling is conducted for a period of time, the injection-compression pipe moves downwards, the sealing plate blocks the grouting opening under the action of the spring to prevent grout from flowing back, meanwhile, the injection-compression pipe moves downwards to extrude the grout, the extrusion force is further increased, and geological gaps are filled with the grout more sufficiently. Through the reciprocating operation, the geological reinforcement position can be fully grouted, the stability and strength of the geological structure are effectively enhanced, the quality and reliability of grouting reinforcement are greatly improved, and the reinforcement requirement under the complex geological condition is met.

The invention relates to the technical field of geological data analysis, discloses a bank slope deep unloading developmental zone identification and evaluation method and system based on a sliding window, and aims at solving the problems that an existing method is low in efficiency and high in subjectivity, and evaluation results are discrete and cannot be quantized. Based on set window parameters, space convolution calculation is carried out through a sliding window, and a continuous feature signal sequence is generated; segmenting the sequence by using a preset background noise threshold value, and identifying candidate sections; matching and calibrating the boundary of the candidate section and the position of a known geological structural plane, and delineating a depth-keeping unloading development zone; the comprehensive development strength index of each deep unloading development zone is calculated, and quantitative evaluation is achieved. According to the method, automatic and continuous space recognition and quantitative representation of the deep unloading development zone are achieved, efficiency and accuracy are improved, and the method is particularly suitable for safe site selection and construction of major projects.

The invention provides a geological structure intelligent detection system and method for a deep special space, and relates to the technical field of geological exploration. The geological structure intelligent detection system and method for the deep special space comprises the steps that S1, a distributed sensor network is deployed in the deep special space, and seismic wave, electromagnetic field, sound wave, temperature and strain multi-physical field original detection data are synchronously collected; constructing a noise channel model based on a quantum computing principle, and modeling the original detection data; a quantum inspired adaptive filtering algorithm is applied, and noise characteristics are estimated in real time through variational optimization. Through synchronous acquisition of a distributed multi-physics field sensor network and an adaptive filtering technology of quantum inspiration, effective enhancement of weak characteristic signals is realized in a strong noise environment, and the signal-to-noise ratio and the target geological structure identification precision are significantly improved; and a neural network inversion model is combined with physical information constraint.

The invention discloses a stratigraphic water content layering inversion method based on a shallow seismic full waveform, and relates to the technical field of geophysical exploration data processing, and the method comprises the following steps: 1, under the same survey line condition, synchronously obtaining a seismic wave full waveform, complex impedance and an induced polarization frequency spectrum; 2, constructing a layered initial model containing a layer boundary line and an in-layer water content initial value; based on the layered initial model, executing dual-domain quantile alignment interface keeping iteration until convergence, and obtaining a final layer boundary line and an in-layer water content field; the double-domain quantile alignment interface maintaining iteration comprises the following steps: updating an in-layer moisture content field and a layer boundary line according to a seismic wave full waveform; and performing total variation regularization processing on the updated in-layer water content field to maintain the transition characteristic of the layer boundary line. According to the method, an efficient and reliable solution with actual guidance value is provided for mineral resource exploration, geological structure detection, groundwater survey and engineering geology evaluation.

The invention relates to the field of environmental analysis, and provides a gas hydrate three-phase coexistence region modeling method and system. The method comprises the following steps: acquiring three-dimensional seismic data and original logging data, and preprocessing the original logging data to obtain corrected logging data; respectively performing logging interpretation and structural interpretation according to the corrected logging data and the three-dimensional seismic data to obtain interpretation results; converting a structure interpretation result in the interpretation results into a three-dimensional geological structure model, and performing grid division on the research area by adopting a corner grid system to obtain a structure grid model; and performing attribute modeling on the constructed grid model based on variation function analysis, and predicting porosity and saturation in a three-dimensional space through a Kriging interpolation algorithm to obtain a three-phase coexistence region model. According to the method, the influence of complex geological conditions on the accuracy of the model is reduced, and the precision of the three-phase coexistence region model is remarkably improved.

The invention discloses a magnetotelluric sounding measurement method for multidirectional aggregation observation, and the method comprises the steps: building a novel device layout: designing a reasonable measurement point layout scheme according to geological features and electromagnetic response distribution; processing data and establishing an unstructured grid: acquiring an electromagnetic field component, completing data acquisition, and inputting the processed electromagnetic field data into an unstructured grid model; impedance tensor calculation: on the basis of the unstructured grid, performing impedance calculation by utilizing multi-component electromagnetic field data and combining an interpolation idea, and constructing an extended impedance tensor of an electromagnetic field component to obtain an impedance value component; and three-dimensional inversion and visualization: performing three-dimensional inversion through a vector finite element method to obtain an inversion result. According to the method, richer observation data are provided for deep geologic structure inversion.

The invention relates to the field of mine disaster prediction, and discloses an AI-based mine disaster prediction and risk assessment method, which comprises the steps of deploying a multi-source sensor network which comprises a microseismic monitoring sensor, a gas concentration sensor, a stress sensor and a hydrological sensor, the data acquisition module is used for acquiring micro-seismic waveform data, gas concentration time sequence data, stress data and hydrological parameter data of a mining working face, a roadway and a geological structure area; and performing space-time alignment processing on the microseismic waveform data, the gas concentration time sequence data, the stress data and the hydrological parameter data to generate a space-time aligned heterogeneous data set, and performing encryption feature interaction with an external system through a federated learning framework. According to the method, a multi-modal deep learning model is constructed, microseismic waveforms, gas concentration time sequences and geologic structure space correlation characteristics are extracted, rock mechanics equation constraint conditions are injected in model training, and the recognition capacity of rock stratum fracture precursor signals and the disaster chain coupling process is remarkably enhanced.

The invention discloses a seismic wave velocity model inversion method based on time-space coupling deep learning, and the method achieves a time-space coupling mechanism through a Fourier neural operator framework of a wavelet transform-attention mechanism, and supports the reconstruction of a spatial two-dimensional velocity model from a time sequence track of multiple seismic sources. Firstly, the local time-frequency representation of each seismic time-domain trajectory is extracted by adopting continuous wavelet transform, and then a wavelet time-frequency spectrogram is coded through a convolution feature extractor. Then, information from multiple sources is fused at each receiver point location through a multi-head attention mechanism, enhancing correlation between multiple sources. And finally, projecting the fused features into a two-dimensional Fourier neural operator to efficiently learn space mapping and reconstruct a bottom-layer velocity model based on sound velocity. According to the method, the time sequence characteristic and the spatial distribution characteristic of the seismic channel are fully utilized, the precision and robustness of an inversion result are improved, and a more reliable speed model is provided for geological structure interpretation and acoustic imaging.

The invention discloses a coal mine tunneling roadway advanced geological exploration and ground stress inversion method, particularly relates to the technical field of seismic signal processing in geophysical exploration, and is used for solving the problems of geological exploration signal distortion and insufficient stress inversion precision caused by strong noise interference of tunneling equipment in the prior art. Rock mass vibration signals are collected through an optical fiber sensor arranged on a roadway wall, equipment noise characteristics are identified through spectral analysis, a quantitative mapping relation between working condition parameters and noise characteristics is established, a noise reference time period is determined according to the quantitative mapping relation, a spatial coherence characteristic template is constructed, high-coherence noise components are inhibited through template comparison, and the noise reference time period is determined according to the spatial coherence characteristic template. Finally, the geological structure and stress field distribution in front of the working face are inverted based on the purified seismic wave signals, a stress concentration area and a disaster risk area are identified, the signal-to-noise ratio of the seismic signals in the strong noise environment and the reliability of the geological inversion result are effectively improved, and accurate technical support is provided for safe mining of a coal mine.

The invention relates to a geological radar advanced forecasting system for TBM shield construction and a detection method, which are characterized in that a transmitting antenna and a receiving antenna are arranged in a tool bit gap of a TBM shield machine, rotation of a tool bit is not affected, measurement can be carried out when the tool bit rotates, and a three-dimensional structure section right in front of the tool bit is further acquired; a method of forming obvious reflection based on geological body physical property dielectric constant difference is adopted, the TBM shield tunneling advancing direction is detected and imaged, a geological structure image is obtained, then geological information such as faults, rich water, cavities and boulders is provided, the influence of geological difference is small, and testing is more accurate compared with a seismic wave method; the receiving antenna and the transmitting antenna are arranged in the tool bit gap of the TBM, the receiving antenna and the transmitting antenna are not affected by the blade, rotation of the tool bit is not affected, and stability and accuracy of rotation measurement of the whole set of forecasting system can be guaranteed.

The invention relates to a tunnel surrounding rock grading method and system based on multi-source data fusion, and the method comprises the following steps: obtaining image data and point cloud data of a tunnel face, carrying out the preprocessing and data enhancement, obtaining image features and point cloud features reflecting the shape, structure, texture and roughness of the tunnel face, and carrying out the classification of the image features and the point cloud features; carrying out fusion processing on the obtained features; during feature fusion, according to the joint density in the image, determining the image block granularity, and projecting the image block granularity to the image features; determining a geological weight according to geological information acquired in advance, and embedding the geological weight into the image features; fusing the surrounding rock roughness and the rock quality index in the point cloud features with the image features through a cross-modal attention mechanism to obtain fused features; and the fused features learn geological structure laws through a pre-trained main network and a pre-trained slave network to obtain a comprehensive score, and a surrounding rock grading result is determined in combination with a threshold value of a set geological parameter.

The invention belongs to the technical field of geological three-dimensional modeling, and provides a line-plane boundary constraint promotion modeling method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the modeling through employing a line-plane boundary constraint promotion model, and obtaining a three-dimensional geologic body model; the modeling method comprises the steps that a point set of a three-dimensional geologic body is obtained, optimization is conducted through a minimization energy function when radial basis function implicit modeling processing is conducted according to the point set, and a normal vector and an implicit function are obtained; the method comprises the following steps: introducing information of a planar geologic structure into an implicit modeling framework in an integral form, performing line-plane constraint on an implicit function, processing the line-plane constrained implicit function through a solution matrix to obtain an implicit function parameter, and determining a line-plane boundary constraint promotion model according to the implicit function and the implicit function parameter. The planar feature information of a geologic body can be effectively utilized, accurate constraint and continuous expression of a geological interface or a stratigraphic structure are achieved, and the spatial precision and reliability of three-dimensional geological modeling are improved.

The invention discloses a seismic-electromagnetic joint inversion method based on bidirectional cross gradient constraint. The method comprises the following steps: firstly, establishing three physical field initial models; taking a seismic grid as a main grid, and mapping respective models of a direct current method and a transient electromagnetic method to the main grid through interpolation; constructing a joint inversion objective function containing data fitting terms of the three physical fields, model constraint terms and cross gradient constraint terms between every two of the three physical fields; decomposing the joint inversion objective function into three inversion objective functions which are coupled with one another, and respectively carrying out iterative updating on the seismic velocity model, the direct current method resistivity model and the transient electromagnetic method resistivity model by adopting a collaborative alternative iteration strategy; each iteration update of any model is constrained by the cross gradient exported by the last iteration result of the other two models, so that the structural consistency between the models is forcibly realized; and after completion, outputting a geologic structure model fusing the three-field information, thereby effectively improving the detection precision and interpretation reliability of the geologic structure under the complex geological condition.

The invention discloses a sampling device for traffic geology surveying and mapping exploration, and relates to the field of geological prospecting, the sampling device comprises a U-shaped moving plate and a sampling pipe, the sampling pipe is located above a U-shaped groove of the U-shaped moving plate, a drill bit is installed at the bottom end of the sampling pipe, a sleeve is arranged in the sampling pipe, two annular blocks are fixed on the inner wall of the sleeve, a vertical rod is arranged in the sleeve, and the vertical rod is connected with the drill bit. A threaded pipe is arranged on the upper surface of the drill bit, a movable cavity is formed in the pipe wall of the threaded pipe, a movable plate is slidably installed in the movable cavity, the bottom end of the movable plate penetrates out of the movable cavity to be fixedly connected with the top end of the drill bit, internal threads are arranged on the inner wall of the bottom end of the sampling pipe, and external threads of the threaded pipe are connected with the internal threads in a meshed mode; according to the rotary drilling device, the drill bit can form continuous and stable impact crushing action, drilling resistance caused by hard rock strata and special geological structures is effectively broken through, and propelling difficulty caused by pure rotary drilling is avoided.

The invention discloses a three-dimensional geological modeling method based on sequential Gaussian simulation, and particularly relates to the technical field of geological modeling, in particular to a three-dimensional geological modeling method based on sequential Gaussian simulation. The method comprises the steps of obtaining and preprocessing geological data, constructing a three-dimensional grid model, analyzing a space structure by adopting an improved variation function integrated with anisotropic parameters, carrying out random simulation by utilizing a sequential Gaussian simulation algorithm and introducing a dynamic conditional mechanism, and meanwhile, integrating multi-source soft data as collaborative variables to apply geological constraints. And finally, post-processing and uncertainty quantification are carried out on a simulation result. According to the method, the description precision of the model on a complex geological structure, the efficiency of simulation calculation and the reliability of multi-source data collaborative application are effectively improved.

The invention discloses a coal mine geological data three-dimensional modeling and transparent working face construction method and system. The method comprises the steps that multi-source geological and production data are collected and preprocessed; constructing a refined three-dimensional geologic body model based on multipoint geostatistics and a collaborative Kriging method; fusing the roadway model through Boolean operation; dynamically constructing a working face model by using real-time mining data; when a model error exceeds a threshold value, dynamic updating based on data assimilation is triggered; and finally, realizing model integration and transparent display in a three-dimensional visualization engine. According to the method, multi-point geostatistics and collaborative Kriging interpolation are fused, multi-source data such as geological drilling and three-dimensional earthquakes are integrated, the depicting precision of complex geological structures such as faults and collapse columns is greatly improved, the geometrical shape of the constructed three-dimensional geologic body model is more vivid, rock mechanics parameters are integrated, and the method is suitable for large-scale popularization and application. The problem that an existing three-dimensional geologic model is limited in precision is solved.

The invention relates to a refined three-dimensional geological modeling method based on a geophysical prospecting three-dimensional inversion algorithm, and belongs to the field of geological exploration, and the method comprises the steps: obtaining multi-source data, constructing an initial model, and obtaining a three-dimensional physical property model through the combined constraint of the three-dimensional inversion algorithm; creating a lithology classifier, generating a three-dimensional lithology probability body according to the three-dimensional physical property model, performing geological structure boundary enhancement, and performing geological classification based on the probability body; and extracting a contour surface from the three-dimensional lithologic probability body, generating a preliminary geological interface, performing construction processing, performing attribute model coupling, and outputting a model. According to the method, the spatial continuous model is directly constructed through three-dimensional joint inversion, and interpolation errors between measuring lines are avoided; drilling data forced matching and geophysical prospecting data trend control consider both local precision and global rationality; the whole process algorithm is driven from inversion to lithology classification, and manual intervention is reduced; the method is suitable for high-precision scenes such as urban underground space, mineral exploration and geological disaster assessment.

The invention relates to the technical field of geological disaster early warning, in particular to a risk grading method for tunnel seismic wave data and geological information fusion, which comprises the following steps: S1, collecting tunnel multi-temporal seismic wave amplitude, frequency response and propagation delay information, identifying an abnormal response event, extracting a spatial propagation path of the abnormal response event in combination with a tunnel structure, generating a seismic wave evoked response event chain set; s2, geological information such as a drilling profile, a geological structure line and lithologic distribution is fused, and a structure chain type conduction diagram is output; and S3, counting the activeness, the derivation direction and the time sequence trend of the structural unit in the conduction diagram, calculating a trend activation factor, and generating a risk level map with predictability and evolution ability. According to the method, the earthquake response event chain and the structure conduction network are constructed, the multi-source geological information is fused, and the trend activation factor is introduced, so that the dynamic, accurate and predictable grading evaluation of the tunnel structure risk is realized.

The invention relates to the technical field of geological disaster monitoring, in particular to a rock collapse accumulation body debris flow tendency intelligent evaluation system and method based on multi-parameter coupling. The method comprises the following steps: acquiring geological structure data of a rock collapse accumulation body; performing potential unconsolidated formation analysis according to the geological structure data to obtain potential unconsolidated formation data; performing rainfall infiltration analysis according to the potential unconsolidated formation data to obtain infiltration rate data; determining the water content state of the accumulation body according to the infiltration rate data; performing stability analysis according to the water-containing state of the accumulation body to obtain accumulation body stability data; identifying a potential sliding section based on the accumulation body stability data; detecting flow energy according to the potential sliding section to obtain sliding power data; and performing hydrological confluence analysis according to the geological structure data to obtain hydrological confluence data. According to the method, the accuracy of identifying and evaluating the debris flow tendency of the rock collapse accumulation body is improved based on a geological disaster monitoring technology.

The invention discloses a mine geology advanced detection and real-time monitoring system based on a six-component seismograph, and relates to the technical field of coal mine underground seismic exploration. The six-component seismographs are respectively arranged on coal walls of a coal face and a driving face, synchronously collect original data at the same time, and upload the collected original data to the background server through the wireless repeater and the industrial looped network; the background server converts the original data into a geophysical inversion result; and the background server carries out real-time dynamic interpretation and artificial intelligence dynamic early warning on parameters of the stratum form, the geological structure and the rock mechanical property according to a geophysical inversion result, uploads early warning information to a control center and distributes the early warning information to personnel and mechanical equipment of a working face. Prediction and early warning of parameters such as stratum form, geologic structure and rock mechanical property are realized, and dynamic high-precision spatio-temporal information is provided for an intelligent mine transparent geologic support system.

The invention belongs to the technical field of coal bed gas detection, and discloses a coal bed exploration logging gas reservoir identification method, which comprises the steps of data acquisition, data preprocessing, gas reservoir preliminary identification, multi-dimensional cross validation, and gas content and development value evaluation. According to the coal seam exploration logging gas reservoir identification method, firstly, association of logging, a rock core and three-dimensional seismic data is established by means of well-seismic calibration on the basis of multi-source data acquisition, then a three-dimensional cross validation closed loop is formed through rock core logging point verification and well-seismic space verification, and the precision of single well local identification is guaranteed through rock core experimental data; according to the method, seismic data are used for checking the spatial suitability of a gas reservoir, a structure height part and a fracture area, the boundary of the gas reservoir is corrected in combination with wave impedance abnormal characteristics, the limitation of traditional single rock core verification is eliminated, it is ensured that the recognition result is highly consistent with a geological structure rule, and accurate parameters are obtained through fusion of rock core actual measurement and logging inversion.

The invention provides a geological exploration data visualization dynamic processing method and system, and relates to the technical field of intelligent geological exploration, and the method comprises the steps: constructing a prior three-dimensional geological structure model and a forward substitution model; constructing a multi-source joint loss function based on forward modeling output of the forward modeling substitution model and geological survey data; based on a multi-source joint loss function, performing layer-by-layer reasoning reconstruction on geological point cloud parameters in the prior three-dimensional geological structure model to obtain a dynamic three-dimensional geological parameter set; performing fusion rendering and interaction analysis on the dynamic three-dimensional geological parameter set to obtain a visualization result of a fusion geological structure and multi-field evolution information, and constructing a scene deduction component based on the dynamic three-dimensional geological parameter set and a forward substitution model; according to the geological situation sensing and deduction early warning method and device, high-precision geological situation sensing and deduction early warning can be achieved through deep fusion of the forward modeling model constrained by physical information and the layered dynamic inversion algorithm.

The application belongs to the technical field of slope displacement monitoring, and specifically discloses a kind of slope displacement monitoring method based on Beidou positioning, the method comprises: according to slope geological survey data, geological structure data and historical monitoring data, fixed monitoring point is laid out in stable area, and mobile monitoring point is dynamically initialized, the three-dimensional coordinates of each monitoring point are collected in real time, the slope displacement and settlement rate of mobile point relative to fixed point are calculated, the risk point and influence range are determined in combination with geological and historical data, the density and position of mobile monitoring point are dynamically adjusted based on risk influence range, and finally the slope displacement monitoring is carried out;The application lays out fixed monitoring point in stable monitoring area by combining slope geological survey data, geological structure data and last period monitoring data, and then avoids the coordinate distortion caused by the displacement of reference point, significantly improves the calculation accuracy of three-dimensional displacement data and the reliability of analysis result.

The invention discloses a mountain geological disaster monitoring method and system based on remote sensing data, and relates to the field of geological disaster monitoring, and the system comprises an analysis module which is used for receiving satellite and unmanned aerial vehicle remote sensing data, and carrying out the topographic correction and noise filtering of the remote sensing data based on the mountain topographic features, extracting multi-dimensional characteristic parameters of earth surface deformation, vegetation coverage and water body distribution; the coupling module is used for receiving the multi-dimensional characteristic parameters output by the analysis module, dynamically associating the multi-dimensional characteristic parameters with the geological structure and rock-soil body property data of the mountainous area, and constructing a space-time matching and coupling calculation model of the multi-source data; according to the method, remote sensing data processing is optimized based on mountain topographic features, the multi-dimensional feature extraction accuracy is improved, data relevance is enhanced through multi-source data space-time matching and coupling calculation, disaster hidden danger points are accurately recognized and positioned in combination with dynamic weight distribution, and meanwhile the disaster development rate and the influence range are scientifically deduced according to a time sequence evolution model.

The invention discloses an elastic reverse time migration imaging method based on deviatoric stress characterization, and relates to the technical field of exploration geophysics. Deviatoric stress is introduced into a conventional elastic wave equation, and a speed-deviatoric stress elastic wave equation describing stress propagation characteristics is obtained through derivation; based on Hooke's law, P wave contribution in total partial strain is removed through partial strain decomposition, decoupling of P-S wave stress components is achieved, and correctness of amplitude, phase and physical unit of a decoupling wave field is guaranteed; and then a joint imaging condition with the average stress as a seismic source wave field and the multi-stress component as a receiving wave field is constructed, PP waves are subjected to normalization superposition through the average stress and the deviatoric stress, and PS waves are subjected to shear stress imaging. According to the method, the sensitivity to heterogeneity and local stress variation of underground media can be remarkably improved, P-S wave crosstalk and imaging noise are effectively eliminated, the imaging precision and resolution of a complex geologic structure are greatly improved, and a reliable technical means is provided for high-precision seismic exploration of complex oil and gas reservoirs.