137 results about "Gravity anomaly" patented technology

The invention discloses a submarine topography super-resolution reconstruction method based on window displacement multi-source fusion, and aims to solve the problem of precision attenuation caused by absence of multi-beam truth value evaluation and resolution improvement of an existing neural network submarine topography reconstruction method. The method comprises the following steps of: obtaining gravity anomaly, gravity vertical gradient, vertical line deviation component, submarine topography background and ship survey water depth multi-source data of a target sea area; constructing a residual U-Net attention neural network model, and performing training by taking multi-source data extracted by a 11 * 11 window and position codes as input; moving the trained model sampling window in a staggered manner according to a target resolution step length; extracting data points in the window during movement and injecting position codes; and outputting a high-resolution water depth predicted value based on the position code and the window data. The reconstruction precision is improved by fusing physical quantities, the multi-resolution robustness is guaranteed by a window displacement mechanism, and the medium-frequency feature reconstruction capability is enhanced by a residual U-Net attention model.

The invention discloses a multi-metal mineral exploration method and system, and relates to the field of multi-metal mineral exploration, and the system comprises a data acquisition module, a structure analysis module, a geophysical exploration module and a mineral evaluation module. Comprising the following steps: collecting wrinkle information, fault information and geophysical prospecting information, carrying out wrinkle state and fault state analysis on the wrinkle information and the fault information to obtain a structural shape prospecting value of each region, comparing the structural shape prospecting value of each region with a set comparison threshold to obtain a judgment signal of each region, receiving a geophysical prospecting signal, and carrying out geophysical prospecting. And performing gravity anomaly, magnetic anomaly and electrical difference analysis on the high-possibility mineral product existence area to obtain a physical exploration shape value of each geophysical exploration area, and performing comparative analysis on the physical exploration shape value and a set reference standard interval to obtain a set of mineral product areas of different grades corresponding to different geophysical exploration areas, so that the multi-metal mineral product areas can be graded according to mineral product reserves. And a basis is provided for making multi-metal mineral exploration and mine development design.

The invention relates to the technical field of geophysical exploration, in particular to a multi-scale three-dimensional gravitational-seismic joint frequency domain inversion method based on hybrid constraints. The method comprises the following steps: determining observation gravity anomaly on the ground by adopting discrete Fourier transform, and discretizing the observation gravity anomaly by adopting a method of weighted average of values at a plurality of Gaussian points; calculating spherical harmonics and spherical harmonic coefficients of two-dimensional density distribution of each layer in the inversion range, and calculating gravity anomalies on the observation surface based on the spherical harmonics and the spherical harmonic coefficients; converting the inversion range data into a three-dimensional gravitational field forward kernel matrix; constructing a three-dimensional gravitational field hybrid constraint inversion objective function; inputting pre-collected earthquake three-dimensional velocity model data, and converting the earthquake three-dimensional velocity model data into a reference density model; and calculating a gradient operator in the inversion objective function, simplifying the inversion objective function based on the gradient operator obtained through calculation, and then solving the simplified inversion objective function by using an alternating direction multiplier method.

The invention relates to the technical field of earthquake monitoring, and discloses a mining area micro-earthquake monitoring method and system based on multi-parameter fusion, and the method comprises the steps: collecting time-space synchronization data of a mining area through employing a preset sensor array, and the time-space synchronization data comprise gravity data and seismic wave data; performing mixed noise reduction on the gravity data to obtain noise reduction data of the gravity data; extracting a gravity anomaly index of the mining area based on the noise reduction data; extracting a seismic wave energy ratio of the seismic wave data; based on the gravity anomaly index and the seismic wave energy ratio, establishing a joint criterion model of the mining area; and performing micro-seismic early warning on the mining area based on the combined criterion value of the combined criterion model and a preset early warning threshold value. The micro-seismic monitoring efficiency of the mining area can be improved.

The invention discloses a submarine sea mountain terrain inversion method based on a removal and recovery method, and the method comprises the steps: removing the influence of a sea mountain on a boundary based on a water depth forward modeling formula through the removal and recovery method by employing water depth forward modeling gravity abnormality and a vertical gravity gradient, and obtaining a high-precision sea mountain boundary terrain; and high-precision inversion is carried out on the sea and mountain main body by combining a GGM method. According to the method, the influence of sea and mountain topographic relief on boundary topography inversion in the linear relation is removed, the nonlinear relation in the linear relation is captured through deep learning, meanwhile, the water depth of a sea and mountain body is obtained through inversion of high-precision ship survey water depth points in combination with a GGM, and finally the high-precision submarine topography of the complete sea and mountain is obtained.

The invention relates to the field of inversion, in particular to a three-dimensional inversion method for gravity multi-scale data, which comprises the following steps of: thinning gravity abnormal data in different scales to obtain multi-scale gravity data; and judging whether the scale of the gravity anomaly is appropriate or not, setting a subdivision unit for the gravity anomaly of the appropriate scale, and accumulating all the previous structure information in each Gramer gradient inversion as a constraint condition for current scale inversion. Applying the inversion result of the current scale to the initial model of the next scale to obtain a target function; and carrying out inversion calculation on the target function by adopting a Grubm gradient method and combining with the adaptive depth weight to obtain a three-dimensional high-resolution density result. In practical application, on the premise that original data do not need to be reconstructed, the deep geologic body inversion resolution is improved by conducting multi-scale collaborative inversion on the gravity data. In practical application, higher inversion resolution and field source depicting capability can be obtained by processing gravity abnormal data.

The invention provides an underwater gravity measurement method, device, equipment and medium based on position observation, the method is realized by gravity measurement based on Hampel and RTS smoothing filtering, and the method comprises the following steps: cleaning and identifying horizontal position data provided by a USBL by using Hampel filtering, and replacing outliers in the horizontal position data to obtain more reliable horizontal position data; the SINS system performs a moving base alignment process by means of the cleaned high-precision horizontal position data; the SINS system performs pure inertial navigation calculation, continuously provides navigation parameters, and suppresses accumulative errors of the inertial navigation system through RTS smooth filtering processing; and an original gravity anomaly result is calculated, and precision evaluation is carried out after filtering processing of an FIR low-pass filter. According to the method, the gravity data is efficiently and accurately processed under the condition that USBL data output is unstable, and the reliability of a gravity data processing result is improved while a high-precision gravity measurement result is obtained.

The invention relates to the technical field of earthquake monitoring, and discloses a non-constructional gravity effect correction system applied to flowing gravity observation, which comprises the following steps of: calculating a diffusion-non-diffusion deviation ratio representing dynamic properties by inverting a global optimal diffusivity adaptive to a current field; the diffusion non-diffusion deviation ratio quantifies the proportion of non-diffusion components which cannot be explained by the diffusion model in the gravity field change, so that whether the dominant mechanism of gravity anomaly is hydrological noise residue or real construction activity is quantitatively judged. According to the invention, self-inspection of the credibility of the correction result is realized, false signals are effectively eliminated, and the reliability of earthquake precursor monitoring is improved.

The invention relates to the technical field of underground medium density inversion, in particular to an underground medium density inversion method and system based on high-precision microgravity, and the method comprises the steps: obtaining the gravity data of each observation point in an underground medium density inversion ground surface measurement region; calculating a superposition abnormal value of each gravity subsequence of each observation point, extracting a superposition characteristic value of each modal component, obtaining the superposition interference confidence of each gravity subsequence of each observation point, obtaining the superposition influence persistence of each observation point, adjusting the wavelet threshold of the wavelet transform of the gravity data on each observation point, and calculating the superposition abnormal value of each gravity subsequence of each observation point. And correcting the gravity data of each observation point after denoising processing to extract Bouguer gravity anomaly of each observation point, and obtaining an inversion result of the underground medium density through a Parker-Oldenburg density interface inversion algorithm. According to the method, the underground medium density can be effectively and accurately inverted through the high-precision microgravity data.

The invention discloses an elevation datum plane construction method and system based on a low-order cosine correction Stokes kernel function, a medium and a product, and relates to the technical field of physical geodetic survey. The method comprises the following steps: calculating by utilizing an earth gravitational field model, topographic data and a high-frequency topographic influence combined algorithm to obtain model data, direct influence of topographic compression on ground gravity anomaly and indirect influence of topographic compression on an elevation datum plane; determining an empirical value and a test value of a correction order of the low-order cosine correction Stokes kernel function based on the accumulative error of the model gravity anomaly and the test frequency bandwidth; calculating an empirical elevation datum plane and a test elevation datum plane based on the empirical value and the test value of the correction order by adopting a low-order cosine correction Stokes kernel function; and determining a final elevation datum based on the empirical elevation datum and the test elevation datum. The construction precision of the elevation datum plane can be improved.

The invention relates to the technical field of geophysical exploration, in particular to an along-curved-surface gravitational field inversion method and device based on a target layer, and the method comprises the steps: taking a target layer curved surface of a target region as a constraint, peeling off a shallow-layer residual gravity anomaly field in a Bouguer gravity anomaly field of the target region layer by layer, and subtracting a region gravity anomaly field below the target layer to obtain a gravity anomaly field; obtaining a residual gravity anomaly field of the target layer curved surface; and in combination with the fluctuation degree of the curved surface of the target layer, performing inversion on the residual gravity anomaly field of the curved surface of the target layer by using deconvolution to obtain a density superposition field of the curved surface of the target layer. According to the method, a new along-curved-surface gravity field inversion method is established, depth parameters of a target layer curved surface are considered during inversion calculation, interference signal influences are eliminated, a density field signal along the curved surface is obtained, a density superposition field of the target layer curved surface is obtained, and an oil-gas-water enrichment area is depicted for follow-up density change interface prediction and oil-gas-water enrichment area depicting. And a basis is provided for providing reference suggestions for well position deployment and production regulation and control.

The invention discloses a geologic body boundary extraction method based on gravity total horizontal derivative anomaly, and belongs to the technical field of geophysical data processing and interpretation. Calculating gravity total horizontal derivative anomaly based on actually measured gravity anomaly data; in the sliding window, detecting whether the gravity total horizontal derivative abnormity meets a preset extreme value structure condition in multiple directions, and screening out boundary points based on an amplitude threshold value and a slope threshold value; according to the invention, a geologic body boundary extraction method based on gravity total horizontal derivative anomaly is established by using directional extremum features of gravity total horizontal derivative anomaly; compared with a traditional boundary recognition method, the method does not depend on prior information, is high in anti-noise performance, can quickly and accurately recognize the boundary position of the geologic body under a complex background, and has higher boundary resolution.

The invention discloses a gravity-magnetic joint inversion method, a gravity-magnetic joint inversion device and electronic equipment. The method comprises the following steps: for at least one exploration measuring point in a target exploration area, obtaining gravity abnormal data, magnetic force abnormal data and measuring point position information of each exploration measuring point; determining a gravity-magnetic joint inversion target function corresponding to the target exploration area according to the block position information of at least one block of the preset layer section of the target exploration area in the first direction, and the gravity anomaly data, the magnetic anomaly data and the measurement point position information of each exploration measurement point in the target exploration area; solving and processing the gravity-magnetic joint inversion objective function based on a conjugate gradient algorithm, and determining an inversion result; the inversion result includes magnetic distribution information and density distribution information of at least one block associated with the exploration point. According to the method, the gravity anomaly data and the magnetic anomaly data are subjected to joint inversion processing, so that the accuracy of a joint inversion result is improved, and a reliable basis is provided for subsequent geological interpretation of a target exploration area.

The invention belongs to the technical field of geophysical inversion, and relates to a gravity anomaly three-dimensional inversion method based on multi-scale feature fusion, which comprises the following steps: randomly generating density anomaly bodies with different numbers, densities, sizes and shapes to obtain an underground medium three-dimensional density model; carrying out forward modeling on the three-dimensional density model of the underground medium to obtain two-dimensional gravity abnormal data of the earth surface; a multi-scale feature fusion model is trained with the underground medium three-dimensional density model as output and the two-dimensional gravity anomaly data as input, and the multi-scale feature fusion model comprises a two-dimensional encoder, a three-dimensional decoder, a dimension converter and a multi-scale feature fusion device, wherein the dimension converter and the multi-scale feature fusion device are located between the two-dimensional encoder and the three-dimensional decoder; and inputting actually measured two-dimensional gravity anomaly data into the trained multi-scale feature fusion model, and performing inversion to obtain a three-dimensional density body constrained by a physical range. According to the method, the expression capability of the multi-scale features of the underground structure is enhanced, and the multi-solution problem and the deep resolution reduction problem of inversion can be relieved.

The invention discloses a fracture activity prediction method and system based on numerical simulation, and relates to the technical field of fracture activity prediction. The method comprises the following steps: firstly, acquiring geological data, seismic wave velocity, gravity anomaly, magnetic anomaly and image data and preprocessing the data, secondly, predicting the probability of fracture activity by using an optimized Bayesian network model, visualizing a prediction result, and finally, performing uncertainty analysis according to the prediction result. According to the method, multiple data sources are integrated, complex preprocessing and analysis are carried out, advanced numerical simulation and optimization technologies are combined, an accurate prediction model is established, the prediction capability of the model is further improved through an innovative Bayesian network optimization and integration method, meanwhile, real-time monitoring data are dynamically fused, and the prediction efficiency is improved. And continuously iterating and updating to reflect the latest condition, and finally providing a detailed prediction result and uncertainty analysis thereof, thereby providing efficient and accurate decision support for monitoring and prevention of fracture activity.

The invention relates to a gravity background field construction method based on iterative optimization Kriging. The method comprises the following steps: S1, obtaining in-situ gravity measurement data as a known point set; s2, based on the known point set, performing preliminary interpolation on grid points of the gridding background image by adopting a Kriging method to obtain a Kriging estimated value of each grid point; s3, by introducing a local gravity anomaly covariance and a Kriging variation function, evaluating the random uncertainty of a Kriging estimated value in an interpolation process, and dividing each grid point into a reference point and a point to be corrected based on the random uncertainty; and S4, combining the reference point and the known point set to construct a continuous distribution constraint curved surface, carrying out local continuity correction on the continuous distribution constraint curved surface based on the obtained reference point, and carrying out iterative expansion on the basis of the corrected local constraint curved surface until the continuous correction of the whole continuous distribution constraint curved surface is completed. And the construction of the gravity background field is realized.

The present application discloses a method for reducing the abnormal difference of elevation measurement in a mining area, comprising the following steps: Step S1: removing the model gravity anomaly Δg from the observed gravity anomaly Δg GM and topographic gravity effect δN T Obtain the residual gravity anomaly, substitute the residual gravity anomaly into the Stokes formula, and calculate the residual geoid δN as follows r :Step S2: In the absence of gravity data, the geoid height N is decomposed according to the spectral structure characteristics of the elevation anomaly; Step S3: At the unknown point, the model elevation anomaly of the unknown point is calculated by the EGM2008 earth gravity field model, and the residual elevation anomaly ξ of the unknown point is added to the result C , get the final elevation anomaly value of the unknown point, and find the normal height of the unknown point. Through practice, the multifaceted function fitting method based on the "remove-restore" method has a good fitting effect in the Dahongshan copper mine area, and the normal height accuracy after fitting can reach the requirement of ±2cm.

The invention discloses a gravity anomaly upward continuation calculation method based on a central grid data block separation method, belongs to the technical field of geophysical exploration data processing, and solves the problems that when an existing method is used for processing an ultra-low altitude upward continuation problem, singularity occurs when an integral kernel function coincides with a calculation point and a data point; the method comprises the following steps: stripping a central data grid where a calculation point is located from an integral domain based on a block separation method, and carrying out practical modification processing on a global integral model based on the block separation method to obtain a modified model without integral singularity; according to the method, a practical modification scheme for converting a gravity anomaly upward continuation global integral model into a local numerical integral model is provided, numerical calculation verification is carried out on a kernel function singularity solution and the practical modification scheme of a calculation model by utilizing an ultrahigh-order bit model EGM2008, and model internal coincidence precision superior to 1mGal can be obtained; therefore, the high-precision earth external gravitational field assignment requirement is met.

The invention belongs to the field of gravity exploration, and particularly relates to a method for acquiring gravity anomaly blank area data based on potential field characteristics, which comprises the following steps: acquiring gravity and topographic data of an exploration area and a neighborhood, and generating standard grid data and identifying a blank area through preprocessing and gridding; multiple interpolation algorithms are combined for parallel calculation, cross validation quantitative evaluation is carried out, and an optimal model is selected to obtain a reliable Bouguer gravity abnormal value of the blank area; mathematical analysis and filtering smoothing processing are carried out on the interpolation result, noise is eliminated, and a Bouguer gravity abnormal value conforming to the physical continuity and smoothness of the gravity field is obtained; and superposing the processed Bouguer gravity anomaly with a terrain gravity effect to obtain a complete space gravity anomaly field. Through systematic processing of existing Bouguer gravity anomaly and topographic data, filling and balancing of gravity anomaly values in areas with complex terrains and sparse data are successfully realized by using technical means of interpolation, analysis, smoothing, reduction and the like.

A method for 3D inversion of Full Tensor Gradiometry (FTG) data comprising receiving observed FTG data, performing a kernel matrix calculation on a subset of the observed FTG data and the gravity anomaly data, performing one-time forward modeling in a wavenumber domain to produce predicted FTG data and predicted gravity anomaly data for the reference density model, performing a residual between the observed data and predicted data, performing a depth-weighting function, a model covariance matrix, and data error covariance matrix on the observed FTG data and observed gravity anomaly data, obtaining a model update based on the depth-weighting function, kernel matrix, the model covariance matrix and the data error covariance matrix, and the residual between the observed FTG data and the predicted FTG data in the wavenumber domain, and performing inversion by directly obtaining an inverted model based on the model update and reference model.

The present invention relates to the field of marine surveying and mapping technology, and more specifically, to an underwater navigation adaptability improvement method based on curvature direction feature adaptation area aggregation, which is beneficial for eliminating isolated adaptation areas and disconnected adaptation blocks and filling internal voids of adaptation blocks, thereby improving directional adaptability and regional connectivity. The method comprises the following steps: obtaining a gravity anomaly reference map: gridding gravity anomaly data and dividing it using a sliding window method to obtain a gravity anomaly reference map; designing curvature direction features: combining the directional characteristics of maximum and minimum curvatures and the characteristics of Gaussian curvature for evaluating regional gravity anomaly changes to construct curvature direction features; and pre-calibrating adaptation area clustering and implementing an adaptation area reclosing mechanism to obtain a final calibrated adaptation area. Compared with the prior art, the selected area not only has stronger connectivity but also has good directional adaptability, thereby ensuring the positioning accuracy of an underwater vehicle in multiple headings.

This invention discloses a high-precision density reversal method and system for gravity anomalies based on regular, stable, and high-speed solution. [Solution] Based on the above-mentioned field source regularization solution, we propose using data with false anomalies at the field source imaging depth as boundary value conditions. Again, by solving the upper space of the first class boundary value problem of Laplace's equation, we calculate gravity anomalies on the ground and perform least-squares optimization iterative solution with the actual ground anomalies to obtain high-precision anomaly imaging data at the field source depth that does not contain false anomalies due to the Gibbs effect. This depth is used as the top interface of the field source, and the top interface is divided into grid prisms to construct the field source morphology. Density inversion is performed on each prism top surface in the frequency domain to obtain the density distribution of the field source morphology. Since this algorithm is implemented in the frequency domain and the inversion is performed at a known field source depth, the present invention is a gravity density inversion method with high speed, high precision, and high resolution characteristics, and provides a new concept for realizing the solution of gravity field source density parameters.

The invention provides an island small landslide early warning method based on gravity sensing and a related device. The method comprises the following steps: respectively collecting gravity data and environment interference data of a target island in real time by using a gravity sensing sensor array and an environment sensing sensor; performing interference correction on the gravity data based on the environment interference data to obtain corrected gravity data; mapping the corrected gravity data into a three-dimensional coordinate system of the target island, and generating a gravity field space distribution matrix; based on the gravitational field spatial distribution matrix, marking an area with gravity anomaly in the target island as a potential anomaly area; and performing prediction based on gravity data corresponding to the potential abnormal area in the corrected gravity data by using the trained landslide early warning model, and performing small landslide early warning on the target island when determining that the predicted landslide occurrence probability is greater than a preset early warning threshold. According to the invention, high-sensitivity and extreme-weather-resistant real-time monitoring and accurate early warning of small landslides of islands and reefs can be realized.

The present invention relates to a method for directly obtaining the deep fine structure of underground space by using gravity, comprising: S1, obtaining Bouguer gravity anomaly data; S2, obtaining the regularization downward continuation stability coefficient by using the sliding window numerical deviation statistical accumulation estimation method; S3, obtaining the Fourier cosine series of the Bouguer gravity anomaly; S4, obtaining the downward continuation section by using the adaptive stable regularization downward continuation algorithm; S5, obtaining the high-order vertical differential difference according to the downward continuation section; S6, obtaining the low-frequency difference map by combining low-pass filtering; S7, performing depth correction on the low-frequency difference map to obtain the deep fine structure of underground space. The method for directly obtaining the deep fine structure of underground space provided by the present invention solves the stability problem of the downward continuation technology at any depth and the problem of separating the fine structure of underground space including layered structure, deep structure, and small structures, and realizes the direct acquisition of the fine structure and tectonic information of underground space based on gravity.

This invention discloses a method, apparatus, and equipment for determining formation thickness based on combined gravity and seismic data. The method includes: extracting the vertical derivative of the Bouguer gravity anomaly in the target basin; regularizing the vertical derivative of the Bouguer gravity anomaly to obtain a regularized value; determining the formation thickness at several well points and in three-dimensional regions within the target basin based on seismic and well data; and establishing a formation thickness prediction function for the target basin based on the regularized value of the vertical derivative of the Bouguer gravity anomaly and the formation thicknesses at several well points and in three-dimensional regions, thereby determining the formation thickness of the entire target basin based on the formation thickness prediction function. This method not only reduces the uncertainty of difference caused by data sparsity when using only seismic data but also solves the drawback of existing gravity interface inversion techniques lacking seismic constraints.

The invention provides a microgravity identification method and system for an underground space. The method belongs to the technical field of gravity recognition, and comprises the following steps: carrying out forward modeling calculation on each group of geometric parameter combination by utilizing a gravity anomaly analysis formula, and generating a synthetic sample data set formed by a gravity anomaly sequence and corresponding geometric parameters; carrying out tidal correction and null drift correction on the actually measured microgravity original data to obtain a basic gravity abnormal value, carrying out terrain correction, height correction and interlayer correction on the basic gravity abnormal value, and calculating Bouguer gravity anomaly after correction; after determining the influence range of the superficial interference, stripping the superficial interference field to obtain target gravity abnormal data for inversion; training a deep learning inversion model by using the synthetic sample data set; and inputting target gravity anomaly data used for inversion into the trained deep learning inversion model, and outputting a prediction result of the geometric parameters and the spatial position of the underground target body. The microgravity recognition precision can be improved in the urban shallow complex environment.

The application belongs to the field of gravity anomaly detection, and in particular to a gravity anomaly target body boundary estimation method and system. Based on the comparison and calculation of boundary functions and forward data sets, the characteristic line segment length vector is obtained from the extreme points of the boundary functions, a reference model is set in the observation range, the characteristic line segment length of each reference model is calculated, the boundary length and the characteristic line segment vector forward data set are established, the target to be measured is matched and compared with the data set, and the boundary estimation of the target body to be measured in the medium field gravity environment is realized. The problems of data attenuation, divergence and low resolution in gravity detection in the medium field environment are solved.

The invention discloses a gravitational field adaptation degree calculation method based on course optimization. The gravitational field adaptation degree calculation method comprises the following steps: converting a gravity anomaly database into a gravity anomaly grayscale image; an improved Sobel operator template is adopted to carry out convolution on the gravity anomaly grayscale image; convolution factors in different directions in the improved Sobel operator template are determined according to the course; constructing a gray level co-occurrence matrix of each sample matching area according to a convolution result; calculating characteristic parameters according to the gray level co-occurrence matrix, and carrying out normalization processing on the characteristic parameters; and calculating the characteristic parameters of different sample matching areas through a principal component analysis method to obtain the fitness of each sample matching area. According to the method, the influence of the course is considered when the gravitational field adaptation degree is calculated, and the precision and accuracy of gravity matching navigation are improved.

This invention relates to the field of geophysical exploration, specifically disclosing a method for identifying geological body boundaries based on adaptive matching of multi-source gravity and magnetic data. The method includes: acquiring gravity and magnetic anomaly data; estimating the equivalent source depth; constructing a depth-response mismatch correction field based on the depth attenuation difference between gravity and magnetic potential fields; compensating for and registering the magnetic anomaly with remanent magnetization and demagnetization offset; constructing an adaptive coupling direction tensor based on the consistency of the local gradient structures of the two fields; performing anisotropic boundary enhancement on the two fields using the principal direction of the adaptive coupling direction tensor as a constraint and the coupling strength as a weight; and iteratively fusing the two fields through mutual verification using the adaptive coupling direction tensor as a constraint and the depth-response mismatch correction field as a weight, outputting the fine spatial location of the geological body boundary and an adaptive confidence evaluation result. This invention achieves adaptive registration and direction constraint enhancement in the depth domain of gravity and magnetic data, effectively improving the accuracy and reliability of geological body boundary identification under complex geological conditions.

The invention discloses a short critical strong earthquake occurrence time prediction method and device, a medium and equipment, and relates to the technical field of earthquake prediction. The method comprises the following steps: performing standardized preprocessing on an atmospheric tidal gravity signal in a preset time window, and after an atmospheric tidal gravity abnormal event is detected, inputting a plurality of target days into a pre-constructed prediction model respectively to obtain the probability of strong shock in each target day after the atmospheric tidal gravity abnormal event occurs; the prediction model is obtained by training according to statistical correlation characteristics between the occurrence time of the atmospheric tidal gravity abnormal event and the occurrence time of the strong earthquake; the strong earthquakes represent earthquakes of which the magnitude is greater than a preset threshold value; and determining a strong earthquake occurrence time prediction result according to the probability of occurrence of the strong earthquake in each target day after the abnormality occurs. According to the method, quantitative probability prediction of the strong earthquake occurrence time is realized, and the method has the advantages of interpretability, calibration and online updating.