29 results about "Resistivity inversion" patented technology

A 3D inversion method of DC method using seismic data constraints is disclosed, comprising processing of seismic data and inversion processing of resistivity data; by utilizing seismic wave interval velocity information to constrain the high-density electrical inversion, which can play a complementary role to a certain extent, it is beneficial to supplement the resolution of resistivity inversion with 3D seismic image information, reflect a boundary of subsurface electrical anomalous body, and further characterizes the boundary characteristics of anomalous body through comprehensive geological-geophysical analysis. Seismic data constraints are applied to 3D resistivity inversion, performing numerical simulation and inversion of electrical data under undulating terrain using the finite volume method and Gauss-Newton inversion method. Furthermore, the seismic anisotropic velocity tensor constraint is introduced for inversion to mitigate the non-uniqueness inherent in single-method inversion, yielding a more accurate 3D subsurface electrical structure and improving the resolution of longitudinal boundaries.

The application discloses a polarization anomaly information extraction method based on resistivity inversion results, and comprises the following steps: introducing a Cole-Cole model into controllable source one-dimensional forward calculation, and deriving one-dimensional frequency domain forward calculation formula containing induced polarization effect; simulating frequency domain electromagnetic field response under the condition of layered induced polarization medium, and analyzing the influence of induced polarization parameters in the Cole-Cole model on the electromagnetic field response; adopting a step-by-step processing strategy to carry out inversion processing on the electrical property parameters of the measured electromagnetic field data, so as to obtain geoelectric section resistivity data; and adopting mapping imaging and sensitive optimal layer recursive imaging to extract the geoelectric section resistivity data, so as to obtain induced polarization anomaly information contained in the electromagnetic field response. Through the above scheme, the application has the advantages of simple logic, accuracy and reliability, and has high practical value and popularization value in the field of geophysical exploration technology.

A hydrothermal type uranium mine deep structure detection method based on electromagnetic method combined inversion, comprising: based on wide area electromagnetic method and magnetotelluric method, respectively acquiring wide area electromagnetic data set and magnetotelluric data set of each measuring point on the measuring line, and synchronously collecting the resistivity of rock samples, and generating a physical parameter table according to the resistivity; the wide area electromagnetic data set and the magnetotelluric data set are subjected to one-dimensional Occam inversion, and first resistivity profile and second resistivity profile are respectively generated; according to the depth weight function, the physical parameter table, the first resistivity profile and the second resistivity profile, an initial resistivity model is generated; the inversion objective function is iteratively solved by using the combined inversion algorithm, and the two-dimensional resistivity inversion profile is output when the iteration is terminated; the two-dimensional resistivity inversion profile is interpreted according to the physical parameter table, and a three-dimensional structural framework is established by using the interpretation result; based on the three-dimensional structural framework and the two-dimensional resistivity inversion profile, the target area in the target mine field is obtained.

The invention discloses a region decomposition-based two-dimensional array resistivity inversion method, electronic equipment, a storage medium and a device. The method comprises the steps that area decomposition is conducted on a large array lateral logging response data set based on the layer interface position of a target area, a plurality of sub-areas are obtained, and every three adjacent stratums form one sub-area; the thickness and the center point position of each stratum are calculated, and then the thickness and the center point position of each sub-region are obtained; constructing a one-dimensional inversion model based on the stratum to perform one-dimensional array resistivity inversion; and constructing a two-dimensional inversion model based on the sub-regions to perform two-dimensional array resistivity inversion, and taking a one-dimensional inversion result as an initial parameter value of the two-dimensional inversion model. The method fully considers the influence of radial mud invasion and longitudinal surrounding rock layers, and strengthens the information constraint of the upper and lower well sections, thereby weakening the influence of surrounding rock, guaranteeing the extraction precision of the real resistivity of the stratum, and achieving the rapid and accurate imaging of the two-dimensional profile of the resistivity of the stratum.

The embodiment of the invention relates to the field of electric or magnetic exploration or detection, in particular to a method and system for determining the extension form of a fracture deep part of a granite type uranium mine. According to the method and the system, the relation between the electrical difference and the underground geologic structure can be quantified by determining the relation between the electrical resistivity of the fracture area and the electrical resistivity of the peripheral area of the fracture area; an underground resistivity inversion cross-section diagram is determined according to the frequency-apparent resistivity of each measuring point, and the deep extension form of the fracture can be visually judged; according to the method, the frequency-apparent resistivity at the measuring point is determined only by using the electric field signal, so that the calculation result is more accurate; and in combination with an underground resistivity inversion section diagram of a detection section, the deduction of the deep extension form of the fracture can be more accurate.

The application discloses a cement mixing pile hole forming uniformity detection method based on resistivity three-dimensional imaging, and particularly relates to the field of nondestructive testing of engineering materials, and is used for solving the problem that the general resistivity inversion method is blurred in detecting the real defect boundary due to the smoothness constraint when detecting the discrete non-uniform body in the cement mixing pile, and false abnormal transition zones are prone to be generated, thereby affecting the detection accuracy; effective data is obtained by acquiring resistivity measurement data and screening, a partition constraint inversion strategy is adopted based on the effective data to weaken the smooth constraint on the core area of the pile body and to retain the conventional smooth constraint on the surrounding medium area, so as to generate a three-dimensional resistivity distribution result, the density clustering and spectral density analysis are extracted and utilized to verify the time and space of the electrical property mutation boundary, the continuous false abnormal transition zone is removed through similarity matching to generate a purified resistivity distribution result, and the uniformity detection conclusion is output based on the result, and the accuracy of the internal non-uniform defect recognition of the cement mixing pile is improved.

A system for creating an enhanced parametric map of an earth formation. A sensor obtains parameter data from the earth formation. A processor obtains an initial parameter map along at least a portion of a borehole through an earth formation. The initial parameter map includes a distribution of values of a parameter of the earth formation. A profile of the parameter is selected from the initial parameter map. A region is selected within the selected contour, and a location of a region boundary of the selected region is identified. A location of a region boundary of an adjacent region in an adjacent contour is identified and used to replace the selected region boundary. A location of a replacement region boundary is determined using locations of region boundaries of adjacent regions in the adjacent contours. An enhanced parameter map with replacement region boundaries is displayed.

The application belongs to the technical field of geophysical signal processing and analysis, and specifically discloses an airborne transient electromagnetic data resistivity inversion method and device based on a genetic algorithm, which comprises the following steps: taking a resistivity model and a transmitting coil height as input, taking airborne transient electromagnetic observation response data as output, and training a deep learning network model to obtain a forward simulator; determining the optimal population number of the genetic algorithm according to the inflection point of the efficiency curve of the forward simulator, then generating an initial population by using a sliding smooth population sampling method, and forming a continuous resistivity model after processing by cubic spline interpolation; coupling the forward simulator to a parallel genetic algorithm parameter inversion framework to generate a target network model; and based on the inversion framework, performing resistivity inversion on the analyzed airborne transient electromagnetic data to obtain multiple groups of smooth resistivity models that meet data fitting differences. The application can significantly improve the reliability of transient electromagnetic data resistivity inversion.

The invention discloses a transient electromagnetic data driving and physical constraint combined two-dimensional resistivity inversion method and system, and relates to the technical field of geophysical electromagnetic exploration and artificial intelligence inversion, and the method comprises the steps: collecting or generating transient electromagnetic multi-time-channel observation data, carrying out the preprocessing, and constructing a pseudo-profile input employing a time channel-measurement point as a core; inputting the pseudo section into a convolutional neural network inversion model to obtain an initial two-dimensional resistivity section; and on the basis of frozen convolutional neural network parameters, introducing a physical information constraint refinement network, carrying out residual error correction on the initial two-dimensional resistivity profile, and outputting a refinement two-dimensional resistivity profile and an error evaluation result through joint optimization of data fitting constraint, diffusion / smooth physical constraint, prior constraint and boundary range constraint. According to the method, the problems of high probability of artifacts, insufficient physical consistency and poor generalization reliability of data-driven inversion are solved, and the stability and interpretability of an inversion result can be remarkably improved while the inversion efficiency is kept.

The application provides a tunnel induced polarization inversion imaging method and device, and the tunnel induced polarization inversion imaging method comprises the following steps: establishing a resistivity initial model m0; performing inversion iteration according to the resistivity initial model m0 and outputting a resistivity model m1; establishing a polarization rate initial model η0; constructing a polarization rate reference model η based on the resistivity model m1 r2 ; performing inversion iteration according to the polarization rate reference model η r2 , and outputting a polarization rate inversion result η1. The tunnel induced polarization inversion imaging method is based on the idea of sequential inversion, a polarization rate inversion reference model is constructed under the premise of obtaining a resistivity inversion result, a polarization rate inversion reference model η r2 is constructed and a polarization rate inversion reference model constraint inversion equation is derived, the tunnel induced polarization inversion imaging method ensures that inversion converges in the correct direction, and solves the problem that traditional polarization rate inversion is prone to local optimization and difficult to converge.

The application discloses a time-frequency electromagnetic resistivity inversion method based on resistivity and layer thickness threshold model constraints, comprising the following steps: determining an inversion depth, collecting geological information of a target area, constructing a geological model, and obtaining a two-dimensional geological model information graph of an inversion profile; determining inversion stratum information according to physical properties, and determining the electrical property layer thickness and resistivity value of the target area to constitute a solution space of the geological model; performing forward modeling on a group of random models in the solution space of the geological model to obtain a forward modeling response function; constructing a target function by using the forward modeling response function and the geological model; determining a fitting difference function of the target function and a preset iteration number, and obtaining a constraint term of the geological model; obtaining a correction amount of the geological model according to the constraint term, and combining the fitting difference to perform correction or performing correction according to the preset iteration number. In conclusion, the application has the advantages of simple logic, strong correlation, reliable inversion and the like.

The invention discloses a resistivity inversion method and device based on well seismic information constraint, electronic equipment and a medium. The method comprises the following steps: fitting longitudinal wave impedance and resistivity in logging data to obtain a fitting empirical formula; performing inversion to obtain longitudinal wave impedance, and calculating first resistivity through the longitudinal wave impedance obtained through inversion and a fitting empirical formula; a stratum framework is constructed, and a second resistivity model is obtained by adopting a Crisgin interpolation method in combination with the resistivity logging data; fusing the first resistivity and the second resistivity by using attribute fusion based on LLE to obtain a well seismic constraint resistivity model; and based on a well-seismic constrained resistivity model, inverting resistivity data by using the acquired time-domain electromagnetic data and adopting a finite memory quasi-Newton method-based global electromagnetic inversion technology. According to the invention, logging and horizon information and wave impedance information of an earthquake are fused to constrain resistivity inversion, and resistivity inversion based on well-earthquake information constraint is realized.

The invention discloses a cement mixing pile pore-forming uniformity detection method based on resistivity three-dimensional imaging, and particularly relates to the technical field of engineering material nondestructive testing. The method is used for solving the problem that a real defect boundary is fuzzy due to smoothness constraint when a general resistivity inversion method is used for detecting a discrete non-uniform body in a cement mixing pile, and meanwhile, a false abnormal transition region is easily generated, so that the detection accuracy is influenced. Effective data are obtained by acquiring resistivity measurement data and screening, smooth constraint of a pile body core area is weakened by adopting a partition constraint inversion strategy based on the effective data, and conventional smooth constraint of a peripheral medium area is reserved to generate a three-dimensional resistivity distribution result. According to the method, the electrical abrupt change boundary is extracted and subjected to space-time verification by utilizing density clustering and spectral density analysis, then a continuous false abnormal transition region is eliminated through similarity matching to generate a purified resistivity distribution result, and a uniformity detection conclusion is output based on the result, so that the accuracy of identifying the non-uniform defect in the cement mixing pile is improved.

The invention discloses a combined advanced detection method based on borehole transient electromagnetism and direct-current resistivity, and the method comprises the steps: laying an advanced borehole in a tunnel face in a tunneling direction, carrying out the collection of borehole transient electromagnetic data, and carrying out the inversion, and obtaining a borehole transient electromagnetic inversion result; according to an inversion result and a corresponding estimation method, calculating to obtain Gaussian variation models in three main axis directions, and expanding the Gaussian variation models to any direction; then, the Gaussian variation model in any direction is substituted into a covariance calculation formula, a covariance value between any two grid units in the area needing to be detected is obtained through calculation, and a covariance constraint matrix is assembled; and finally, introducing the matrix as a regularization item into an inversion objective function of direct-current resistivity advanced detection to realize covariance constrained direct-current resistivity inversion, so that the inversion stability and the inversion imaging precision of the direct-current resistivity advanced detection are remarkably improved, and the method is suitable for scenes such as tunnel face or coal mine underground tunneling advanced detection and the like.

The invention discloses a resistivity three-dimensional inversion method based on underground water seepage parameter constraint, and relates to resistivity inversion, and the method comprises the following steps: building a three-dimensional model, and determining model parameters; inputting an initial model and observation data; performing forward numerical calculation by adopting finite difference to obtain a model electric field value, and comparing the electric field value obtained by forward modeling with observation data to obtain a data error; calculating a cross gradient term of the model resistance and the hydrological parameters in a physical property space; establishing an objective function, calculating the gradient of the objective function, taking a nonlinear conjugate gradient method as an inversion method, and obtaining a search step length and a search direction through a quasi-forward modeling mode; judging whether the linear search convergence condition converges or not, if yes, entering the next step, otherwise, updating the model, and returning to forward calculation; and calculating a data root mean square error, if convergence occurs, ending iteration, otherwise, updating the step length and the search direction, calculating a model update amount, and returning to forward calculation.

The invention relates to a system for surface and underground feature integrated visualization based on multi-software cooperation, and the system comprises a data collection module which is used for obtaining underground feature data and surface feature data; the data processing module is used for performing enhancement processing on the underground feature data and the earth surface feature data and respectively creating a resistivity inversion curved surface model and an earth surface feature line frame model; and the modeling and visualization module is used for carrying out spatial synchronous fusion on the enhanced data and the earth surface feature line frame model of the earth surface features, and carrying out visual display through an environment visualization system. According to the method, the data transmission process is optimized, and the problem of multi-software compatibility is solved, so that comprehensive, accurate, visual and integrated display of building or construction site information is ensured, and efficient and visual support can be provided for analysis and decision-making of complex scenes.

The present application relates to the technical field of geophysical exploration, in particular to a method, medium and device for electromagnetic method and microseismic monitoring joint observation inversion constraint, the method comprising the following steps: constructing an underground resistivity model and a velocity model; constructing an inversion objective function based on the microseismic first arrival wave travel time difference according to the corrected travel time difference, obtaining the velocity model parameters through the first arrival wave travel time difference tomography by the adjoint state method; using a regularization method to construct the magnetotelluric inversion objective function, adding the velocity lateral gradient of the discrete grid of the velocity model to the smoothing constraint term of the resistivity model, and using global optimization inversion to solve the magnetotelluric inversion objective function to obtain the inverted resistivity model. In the present application, the velocity model obtained by the travel time inversion of the microseismic monitoring has the characteristics of high lateral resolution, and the use of the natural exponential function weighting can help to reduce the lateral smoothing of the resistivity model and improve the lateral resolution of the resistivity inversion.

The invention provides a direct-current resistivity inversion method, device, equipment and medium, and relates to the technical field of geophysical exploration, and the method comprises the steps: obtaining the observation apparent resistivity data of a target region; based on the observation apparent resistivity data, determining a resistivity preliminary structure corresponding to the observation apparent resistivity data; constructing a training sample data set of the target area based on the resistivity preliminary structure; based on the training sample data set and the weighted objective function, optimizing the width learning network to obtain a model for inversion; and based on the observed apparent resistivity data, the inversion model is adopted to invert the real resistivity data of the target area, so that the precision of the resistivity inversion result is improved, and the high-precision inversion of the underground resistivity structure is realized.

The invention discloses a method for accurately monitoring saturation distribution of hydrates in sediments, and the method comprises the steps: building a resistivity and sound wave collection device which comprises a hydrate sample preparation module, a pressure test module, a temperature test module, a resistivity parameter test module and an acoustic parameter test module; carrying out a simulation experiment to obtain temperature, pressure, sound wave and resistance data; converting the measured resistance data into two-dimensional resistivity data by using a resistivity tomography technology; utilizing the optimized acoustic rock physical model to inversely calculate the hydrate saturation; optimizing the resistivity inversion hydrate saturation based on the calculated hydrate saturation and the obtained two-dimensional resistivity data to obtain two-dimensional saturation data; and based on the two-dimensional saturation data, establishing a three-dimensional image of the hydrate saturation by adopting a sequential Gaussian simulation method. According to the method, the calculation precision of the hydrate saturation is improved, the distribution of the hydrate saturation is accurately imaged, and data support is provided for hydrate reservoir evaluation.

The application discloses a method for DC data inversion constrained by multi-point geostatistics structure, and belongs to the field of geophysical exploration, which comprises the following steps: based on geological drilling data, a model containing geological structure information is established by using multi-point geostatistics algorithm, and an underground stratum structure operator is constructed by using the model; the structure operator is added to a regularization term, a data residual term is calculated by giving an initial resistivity model, and an inversion objective function with structure constraint is formed; in the inversion process, a limited memory quasi-Newton optimization algorithm is used to iteratively optimize the objective function until the difference between the forward simulation data and the measured data reaches a set threshold, that is, the constrained inversion is completed; and finally, the resistivity inversion model is output. The application reduces the problems of stratum boundary blurring and resolution decline caused by the regularization smoothing constraint in the traditional method, is suitable for underground stratum structure detection and fine imaging under complex geological environment, and has wide application value.

The invention discloses a multi-layer metal layering thickness measuring method, which comprises the following steps of: firstly, carrying out a multi-electrode electrical measurement method experiment on the surface of a multi-layer metal material to obtain apparent resistivity of measuring points under different electrode distances; then calculating the relation between the measurement depth of the accurate measurement point and the electrode spacing in the multi-electrode electrical measurement method, and further obtaining the measurement depth of the measurement point under different electrode spacing in the experiment; the method comprises the following steps: constructing a one-dimensional convolutional neural network model for inversion of the thickness and resistivity of a multi-layer metal material, creating a training sample to train the model, and finally inputting the obtained apparent resistivity and measurement depth data of measurement points under different electrode distances into the trained model. And carrying out inversion to obtain layering thickness information and resistivity information of the multi-layer metal material. Pre-calibration is not needed before the method is used, the thickness of each layer of the multi-layer metal can be obtained through the method, and the type of the material can be roughly judged through the resistivity obtained through inversion on the premise that the type of the material is unknown.

The application discloses a kind of layered metal layered thickness measurement method, this method first carries out multi-electrode electrical measurement method experiment on the surface of layered metal material, obtains the apparent resistivity of measuring point under different electrode spacing;Then the relationship between the measurement depth of accurate measuring point in multi-electrode electrical measurement method and electrode spacing is calculated, further obtain the measurement depth of measuring point under different electrode spacing in experiment;A one-dimensional convolutional neural network model for layered metal material thickness and resistivity inversion is constructed, training samples are created to train the model, and finally the apparent resistivity of measuring point under different electrode spacing and the measurement depth data obtained are input into the model after training, and the layered thickness information and resistivity information of layered metal material are obtained by inversion.The application does not need to be pre-calibrated before use, and the thickness of each layer of layered metal can be obtained using the method, and the material type can be roughly judged by the resistivity obtained by inversion under the premise of unknown material type.

The invention relates to the technical field of engineering geophysical prospecting, and discloses a high-density electrical method inversion method based on multi-detection mode fusion, which comprises the following steps: S1, acquiring multi-source detection data, and acquiring apparent resistivity observation data of a temperature sensor device and a dipole device; s2, carrying out spatial registration on the collected multi-source detection data, wherein the spatial registration comprises registration in the horizontal direction and registration in the vertical direction; s3, performing differential preprocessing on the registered multi-source data respectively; s4, constructing a weighted joint inversion model, calculating a basic weight based on a measurement error, introducing a depth factor to modulate the basic weight, balancing the total weight of the two types of devices through a scaling factor, and constructing a diagonal weight matrix W for joint inversion of a target function; and S5, performing inversion iterative optimization, and adopting a Gauss-Newton method to minimize the objective function so as to realize the iterative updating of the model. On the premise of not changing the arrangement of the detection electrodes, the inversion precision is improved and the detection blind area is reduced through the complementation of the detection advantages of the temperature nano device (alpha) and the dipole device (beta).

The invention relates to the technical field of electrical prospecting, and particularly discloses a thin-layer resistivity inversion method and device based on pseudo seismic wave impedance, and the method comprises the steps: carrying out the preprocessing of original seismic data, and obtaining wide-area electromagnetic data; establishing simulated seismic curve data based on the wide-area electromagnetic data; improving the resolution of the simulated seismic curve data; carrying out wave impedance inversion on the simulated seismic curve data after the resolution is improved to obtain an inversion result; and performing resistivity inversion by taking the inversion result as an initial model to obtain a resistivity distribution result of the stratum. On the basis of a resolution improving technology in seismic exploration, a set of equivalence resistivity inversion technology for improving thin layer precision is developed by establishing a wave impedance inversion result of simulated seismic data, the data potential of an existing wide-area electromagnetic method can be fully excavated, and then the resolution and precision of electrical exploration are improved.

The present application relates to the technical field of geophysical electromagnetic prospecting, and particularly relates to a multi-source coverage electromagnetic method observation data inversion method, medium and equipment, the multi-source coverage electromagnetic method observation data inversion method comprising: arranging electromagnetic measuring points and signal transmitting sources in a target detection area, and collecting measured electromagnetic field data; calculating theoretical primary electromagnetic fields of each electromagnetic measuring point in the detection area under the condition of all signal transmitting sources, and fitting the measured electromagnetic field data of all electromagnetic measuring points by using a dichotomy method to obtain a background resistivity; constructing an initial inversion resistivity model based on the background resistivity; constructing a resistivity inversion objective function of the target detection area according to a model constraint term and a data fitting term; and performing iteration until RMS < G or q >Q times of output resistivity models. The present application removes the field source effect caused by resistivity abnormal bodies outside the target detection area by subtracting the data between electromagnetic measuring points during inversion, so as to further improve the resistivity structure precision.

This application discloses a method, apparatus, device, and storage medium for resistivity and surface wave inversion probability fusion for shallow geological exploration, comprising: acquiring resistivity data and surface wave data of a target area; iteratively inverting and updating multiple model samples based on the resistivity data and surface wave data to determine the corresponding resistivity inversion model set information and velocity inversion model set information; evaluating the corresponding probability distribution and uncertainty voxels based on the resistivity inversion model set information and velocity inversion model set information to determine resistivity evaluation information and velocity evaluation information; determining the resistivity information entropy information and velocity information entropy information of uncertainty voxels at the corresponding normalized scale based on the resistivity information entropy information and velocity information entropy information; and fusing the resistivity evaluation information and velocity evaluation information based on the voxel weights corresponding to the resistivity information entropy information and velocity information entropy information to determine the fused probabilistic geological result.

The application discloses a method for resistivity inversion assisted by a geological map space database, and comprises the following steps: S1, selecting a geological map of a specified scale and constructing a geological map database, and extracting specified parameters of resistivity inversion; S2, constructing a gridded geological surface body, and obtaining the lithology distribution and physical property parameters in each grid unit; S3, constructing an underground physical property distribution model by using the obtained parameter combination; S4, introducing geological constraints and obtaining regional regularization parameters of spatial variation according to the underground physical property distribution model based on a preset inversion optimization algorithm, and the obtained regional regularization parameters are used for performing resistivity inversion calculation; S5, performing information data superposition and comparison in GIS software based on the resistivity obtained by the inversion calculation; and S6, defining a consistency scoring function, and quantifying the matching degree of the inversion result and the geological boundary and the structural belt. The application can improve the accuracy and efficiency of inversion modeling and enhance the geological consistency of the inversion result by using existing geological information.

The present application relates to a kind of stratum water resistivity inversion interpretation methods based on conventional well logging curve, constructs a rock conductive response model and natural potential electrochemical response model;With stratum conductivity measured value and natural potential deviation measured value as constraint, in the stratum water conductivity range of the region where target well section is located, rock conductive response model and natural potential electrochemical response model are jointly constrained inversion solution, obtain an optimal stratum water conductivity so that the predicted value of rock conductive response model and natural potential electrochemical response model simultaneously approaches corresponding measured value;Further, according to the optimal stratum water conductivity, the predicted stratum water resistivity is obtained.The present application utilizes dual physical field constraint to improve the uniqueness and reliability of inversion result, solves the correction problem of shale additional conductivity, and still maintains high precision in complex lithology reservoir;Only need conventional logging data, without special logging or formation test, can realize point-by-point calculation of whole well section, has very strong popularization value.

This invention provides a method and system for monitoring the stability of soil and rock masses based on high-density electrical resistivity methods (EDS), comprising: acquiring apparent resistivity data of the target soil and rock mass monitoring area based on a high-density electrode array; using a parallelized three-dimensional resistivity inversion algorithm to invert the apparent resistivity data into a true three-dimensional resistivity model of the soil and rock mass, and storing the inversion results in time sequence to construct a four-dimensional resistivity database; spatiotemporally aligning and fusing the four-dimensional resistivity database with other monitoring data of the target soil and rock mass monitoring area to obtain an analysis dataset; wherein, the other monitoring data include rainfall, groundwater level, and surface displacement; training a neural network model based on the analysis dataset to construct a soil and rock mass stability monitoring model; and performing real-time monitoring of the soil and rock mass to be monitored based on the soil and rock mass stability monitoring model to obtain monitoring results. This invention elevates the traditional decentralized, delayed, and superficial monitoring mode into an integrated, real-time, and in-depth intelligent early warning system.