60 results about "Gravity anomaly" patented technology

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 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 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 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 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.

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.

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.

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.

The application belongs to the technical field of geophysical inversion, and relates to a gravity anomaly three-dimensional inversion method based on multi-scale feature fusion, comprising the following steps: randomly generating density anomaly bodies with different number, density, size and shape to obtain a three-dimensional density model of underground medium; forward modeling the three-dimensional density model of underground medium to obtain two-dimensional gravity anomaly data of the ground surface; training a multi-scale feature fusion model with the three-dimensional density model of underground medium as output and the two-dimensional gravity anomaly data as input, wherein the multi-scale feature fusion model comprises a two-dimensional encoder and a three-dimensional decoder, and a dimension converter and a multi-scale feature fusion device located between the two-dimensional encoder and the three-dimensional decoder; inputting the measured two-dimensional gravity anomaly data into the trained multi-scale feature fusion model to obtain a three-dimensional density body constrained by a physical range through inversion. The application enhances the expression capability of multi-scale features of underground structures, and can relieve the multi-solution problem of inversion and the problem of resolution decline in deep parts.

The invention discloses an edge detection filter based on a TANH function and an arcsine function, and the filter determines Bouguer gravity anomaly data through obtaining free air gravity anomaly data, terrain correction values and Bouguer correction values of a plurality of gravity points of a research region. Calculating Gaussian envelope gradient data based on the gravity gradient tensor component data and Gaussian envelope, and obtaining an edge detection filtering result according to the Gaussian envelope gradient data and TANH function filtering; noise interference can be effectively suppressed by adopting a double-constraint mechanism, a generated boundary result is clear and continuous, and the problems of boundary divergence, positioning fuzziness, form distortion and the like existing in a traditional method are effectively solved; anomalous bodies with different depths are synchronously and accurately identified, stable detection performance can be maintained under complex geological conditions, and generation of false boundaries under the condition of coexistence of positive and negative anomalies is reduced; the reliable boundary recognition capability can be kept under the strong noise background, manual intervention in the preprocessing link is reduced, and the practical application convenience and the result reliability are improved.

The invention relates to the technical field of data processing, in particular to a mining area geological information comprehensive analysis method and system based on data integration, and the method comprises the steps: obtaining and preprocessing multi-source geological data, carrying out the feature correlation analysis and normalization, and obtaining a standardized data set; classifying the magnetic anomaly and gravity anomaly data through a support vector machine to generate a fluid dynamic classification result; performing interpolation processing on the classification result to generate continuous fluid dynamic data, and analyzing the speed and direction change of the fluid to generate a permeability distribution diagram; extracting an abnormal region according to the dynamic change trend, matching the abnormal region with historical data, marking geological abnormal points and generating an abnormal distribution diagram; according to the geological flow monitoring report, the underground water body type or the change of the oil-gas mixing proportion is judged, a pressure fluctuation mode is recognized, and a refined geological abnormal point distribution diagram is generated. According to the invention, mining area resource management and potential risk early warning can be effectively supported.

The invention discloses a method for multi-source data joint identification and inversion of a middle and lower earth crust high conductor, and relates to the technical field of geophysical exploration. The method for multi-source data joint identification and inversion of the middle and lower earth crust high conductor mainly comprises the following steps: carrying out potential field separation on Bouguer gravity anomaly data to obtain residual gravity anomaly, regional gravity anomaly and field source depth, and further determining earth crust residual gravity anomaly and middle and lower earth crust density disturbance characteristics; and calculating residual gravity low anomalies reflecting the middle and lower earth crust high conductors in the research area, delineating plane distribution of the middle and lower earth crust high conductors, and performing random sub-domain three-dimensional automatic inversion for the residual gravity low anomalies to obtain a three-dimensional space distribution form of the middle and lower earth crust high conductors. By implementing the multi-source data combined identification and inversion method for the mid-lower earth crust high conductor provided by the invention, the mid-lower earth crust high conductor can be rapidly and effectively identified and inverted, and the three-dimensional space distribution of the mid-lower earth crust high conductor can be obtained.

The application discloses a kind of estimation method and system based on high frequency information gravity-magnetic anomaly lateral resolution, comprising the following steps: obtaining gravity-magnetic anomaly data, griding gravity-magnetic anomaly data, obtaining griding gravity-magnetic anomaly data;Low-pass filtering is carried out to the griding gravity-magnetic anomaly data, and regional gravity-magnetic anomaly data are obtained;Based on the griding gravity-magnetic anomaly data and regional gravity-magnetic anomaly data, subtract to obtain residual gravity-magnetic anomaly data;Change geometric scale factor, obtain residual gravity-magnetic anomaly data of different scales;The residual gravity-magnetic anomaly data of different scales are compared and analyzed, and the preset scale that presents residual gravity-magnetic anomaly distribution characteristics is obtained, and the estimation of gravity-magnetic anomaly lateral resolution is realized.The lateral resolution of gravity anomaly or magnetic anomaly estimated by the method can evaluate the related geological problems that can be solved by existing gravity-magnetic data, and can improve the efficiency of gravity-magnetic data processing and interpretation.

The present disclosure provides a gravity anomaly extraction method, device, equipment and storage medium, and belongs to the technical field of gravity exploration. The method comprises: performing terrain correction and curving processing on the Bouguer gravity anomaly of a target region to obtain a first gravity anomaly; performing constant-density gravity stripping processing on the first gravity anomaly to obtain a second gravity anomaly; performing variable-density gravity stripping processing on the second gravity anomaly to obtain a third gravity anomaly, wherein the density of the multiple layers of strata between the stratum where the target geological body is located and the surface is variable in the along-layer lateral direction; determining a first gravity regional field of the target region; and extracting the gravity anomaly of the target geological body according to the third gravity anomaly and the first gravity regional field. The variable-density gravity stripping processing on the second gravity anomaly can eliminate the influence of the variable density of the strata in the along-layer lateral direction on the gravity anomaly of the target geological body, thereby improving the accuracy of the extracted target gravity anomaly.

The present invention discloses a method and system for high-precision density inversion of gravity anomalies based on regular stable fast solution. [Solution] Based on the above source regularization solution, we propose using data containing spurious anomalies at the source imaging depth as boundary value conditions. Then, through the upper half-space solution of the first-class boundary value problem of Laplace's equation, we calculate the gravity anomaly on the ground, and perform a least-squares optimization iteration with the actual ground anomaly to obtain high-precision anomaly imaging data at the source depth without spurious anomalies caused by the Gibbs effect. This depth is used as the top interface of the source, and the top interface is divided into grid prisms to construct a source configuration. Density inversion is performed on each prism top surface in the frequency domain to obtain the density distribution of the source configuration. Because this algorithm is implemented in the frequency domain and the inversion is performed at a known source depth, the present invention provides a gravity density inversion method with high speed, high precision, and high resolution, and provides a new concept for solving gravity source density parameters.

The application discloses a method, device and equipment for determining crust shortening amount and a storage medium, and belongs to the technical field of geophysical exploration. The method comprises the following steps: acquiring gravity data and geological data of a detection area comprising a compression structure area and a gravity background area; determining a first gravity anomaly integral amount of the detection area based on the gravity data of the detection area; determining a gravity contrast model corresponding to a specified area based on the geological data of the detection area, and further calculating a second gravity anomaly integral amount of the detection area; and calculating the crust shortening amount of the detection area based on the first gravity anomaly integral amount and the second gravity anomaly integral amount. According to the method, the gravity data is combined with the deformation of the compression structure based on the gravity anomaly of the crust compression structure, so that the crust shortening amount can be obtained simply, quickly, accurately and reliably, and reliable prior information can be provided for compression structure research and geophysical structure modeling.

The application discloses a gravity data downward continuation method based on a discrete model of a reverse band-limit Poisson integral, equipment, a medium and a product, relates to the technical field of gravity data processing, and performs gridization on discrete gravity point data, determines a grid limit frequency, a truncation order of grid gravity anomaly data and a type of a discrete model of a reverse band-limit Poisson integral, and when a direct discrete model in a removal recovery mode is removed, determines a coefficient matrix, a parameter vector and a constant vector based on the grid gravity anomaly data, a continuation height and an earth gravity field model; determines a target calculation formula based on the coefficient matrix, the parameter vector and the constant vector; when an indirect discrete model in a near-zone integral mode is removed, determines a target calculation formula of the discrete model based on the grid gravity anomaly data and the continuation height; and obtains a downward continuation result based on the target calculation formula of the discrete model. The application can stably and highly accurately perform downward continuation on gravity data.

The invention relates to an underwater navigation adaptation area connectivity improving method based on correction domain boundary screening, which comprises the following steps: constructing a gravity anomaly feature and adaptation area correlation model EBMAS, and completing underwater navigation adaptation area calibration by using an EBMAS model, firstly, making up an evaluation blank of a navigation reserved boundary of a TERCOM algorithm by using a correction square domain migration mechanism and an out-of-domain sequence reduction mechanism; an adaptation area is calibrated; secondly, obtaining a training data set in combination with adaptive region class labels and gravity anomaly features; then, a range control synthetic minority class oversampling technology RCSMOTE is combined to control the position of a newly synthesized adaptive region sample in a data space so as to identify a potential adaptive region sample and enhance the classification identification performance of the calibration model; afterwards, a key gravity anomaly feature set with comprehensive information representation is screened in combination with a maximum correlation minimum redundancy algorithm mRMR, and compared with the prior art, the comprehensiveness and accuracy of calibration of the adaptation area can be effectively improved, and high applicability is still shown when the model is migrated to a new area.

The invention discloses a strong earthquake prediction method and device based on earthquake precursor information, a medium and equipment, and relates to the technical field of earthquake prediction. When it is determined that the atmospheric tidal gravity signal is an atmospheric tidal gravity abnormal signal, inputting the atmospheric tidal gravity abnormal signal into a pre-constructed gradient elevator model, and performing spatial partition simulation on the research area to obtain a simulated magnitude of each partition; compensating the energy loss of the signal in the complex medium propagation by using an attenuation function to obtain the actual magnitude of each partition; further determining the distribution condition of a seismic source risk area in combination with regional seismic spatial distribution characteristics, and outputting a strong seismic prediction result of the research area according to the distribution condition; on the basis, a characteristic contribution degree analysis method is introduced, physical interpretability test is carried out on model output, and an influence mechanism of key characteristics of abnormal signals on a prediction result is clarified. According to the method, the accuracy of strong earthquake quantitative prediction is improved.

This invention relates to the field of deep learning technology and discloses a real-time regional gravity field modeling method and system based on deep neural networks. The method includes the following steps: acquiring ground gravity measurement data and calculating the original ground gravity anomaly at discrete ground points; introducing a global gravity field model to obtain the long-wave gravity anomaly component of the discrete ground points in real time; introducing a deep fully connected neural network (FC-DNN); calculating the short-wave gravity anomaly component of the discrete ground points in real time; introducing a convolutional neural network (CNN); predicting the residual gravity anomaly component of the discrete ground points in real time; and fusing the residual gravity anomaly component, short-wave gravity anomaly component, and long-wave gravity anomaly component of the discrete ground points to complete the modeling of the regional ground gravity field. This invention features high training efficiency and fast inference speed, solving the problem of insufficient computational efficiency in existing gravity field modeling methods.

The application 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, which comprises the following steps: obtaining gravity data of each observation point in an underground medium density inversion surface measurement area; calculating the stacking anomaly value of each gravity subsequence of each observation point, extracting the stacking characteristic value of each mode component, obtaining the stacking interference confidence degree of each gravity subsequence of each observation point, obtaining the stacking influence duration of each observation point, adjusting the wavelet threshold of wavelet transformation of gravity data on each observation point, correcting the gravity data of each observation point after denoising to extract the Bouguer gravity anomaly of each observation point, and obtaining the inversion result of the underground medium density through a Parker-Oldenburg density interface inversion algorithm. The application can effectively and accurately invert the underground medium density through high-precision microgravity data.

The application discloses a sea depth prediction method and system based on a variational filtering method and a baseband removal method, and a storage medium, relates to the technical field of geographic information data processing, and comprises the following steps: obtaining a gravity anomaly residual frequency domain signal and a ship-surveyed sea depth residual frequency domain signal; performing filter design to obtain a sea depth filter and a gravity anomaly filter; performing filtering to obtain a ship-surveyed sea depth mid-wave frequency domain signal and a gravity anomaly mid-wave frequency domain signal; obtaining a target area mid-wave predicted sea depth, a target area long-wave predicted sea depth and a target area short-wave predicted sea depth; and obtaining a target area predicted sea depth. In the scheme, the existing discrete data is used to obtain the target area predicted sea depth from the signal decomposition angle based on the semi-physical set and the semi-data fusion driving mode, the existing data is constrained in a fuzzy and wide range, the application range is widened, the experience interference is reduced, the time consumption is reduced while the result convergence is ensured, and the sea depth prediction effect is good.

The invention belongs to the field of gravity anomaly detection, and particularly relates to a gravity anomaly target boundary estimation method and system.The method comprises the steps that on the basis of comparative calculation of a boundary function and a forward modeling data set, feature line segment length vectors are obtained through boundary function extreme points, reference models are set in an observation range, and the feature line segment length of each reference model is calculated; and establishing a boundary length and feature line segment vector forward modeling data set, and carrying out matching and comparison calculation on the to-be-measured target and the data set to realize boundary estimation of the to-be-measured target body in the midfield gravity environment. The problems of gravity detection in a midfield environment, data attenuation, divergence and low resolution are solved.

The application discloses a short-term strong earthquake occurrence time prediction method and device, medium and equipment, and relates to the technical field of earthquake prediction. The method performs standardization preprocessing on atmospheric tide gravity signals in a preset time window, inputs a plurality of target days into a prediction model constructed in advance after detecting an atmospheric tide gravity anomaly event, and obtains the probability of strong earthquakes occurring in each target day after the atmospheric tide gravity anomaly event. The prediction model is trained according to the statistical correlation characteristics between the atmospheric tide gravity anomaly event occurrence time and the strong earthquake occurrence time. The strong earthquake refers to an earthquake with a magnitude greater than a preset threshold. According to the probability of strong earthquakes occurring in each target day after the anomaly, the strong earthquake occurrence time prediction result is determined. The method realizes quantitative probability prediction of the strong earthquake occurrence time, and has the advantages of being interpretable, calibratable and online updatable.

The invention relates to the technical field of remote sensing image processing, in particular to a satellite image RPC parameter elevation optimization method fused with a gravity field model. Comprising the following steps: S1, aerial triangulation encryption and key point acquisition; s2, coordinate transformation; s3, primarily calculating geodetic coordinates by the model; s4, carrying out elevation conversion on the EGM2008 model; s5, constructing a block adjustment model considering the gravity field; s6, iterative solution and output are carried out; according to the method, the earth height (H) directly output by the RPC model is accurately converted into the normal height (h) by introducing the EGM2008 earth gravitational field model, so that the elevation system error caused by the fluctuation of the geoid in a complex region with abnormal and remarkable gravity is effectively eliminated. The normal height is used as a hard constraint to be fused into block adjustment, and the RPC parameters are optimized in a targeted manner, so that the final elevation positioning precision is improved by more than 30% compared with that of a traditional method, and the elevation precision requirement of topographic map surveying and mapping with the measuring scale of 1: 10000 and even 1: 2000 can be met.

The application provides a geophysical gravity anomaly source model construction and fast forward and inverse method, and relates to the technical field of intelligent three-dimensional geological modeling and simulation. According to the geological information of a research area, the method sets the source body modeling parameters of the gravity anomaly field of the research area, obtains a three-dimensional model matrix M capable of describing multiple abnormal bodies underground; a fast forward network is constructed, a nonlinear mapping from the three-dimensional model matrix to simulated anomaly data is established through the fast forward network, and the forward response of the three-dimensional model matrix is calculated; an inversion network based on a concurrent module CFTBlock, a joint CNN and a Transformer is constructed, and a nonlinear mapping from the gravity anomaly data to the three-dimensional model matrix is established. The method has the advantages of fast and accurate forward and high-resolution inversion, and is suitable for better interpretation of measured gravity data.