689 results about "Geophysical prospecting" patented technology

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

The invention provides a BIM (Building Information Modeling)-based rail transit construction geological exploration profile generation method, which belongs to the technical field of exploration measurement and comprises the step of comprehensively improving the accuracy of rail transit construction geological exploration through an advanced data acquisition and intelligent analysis method. In a construction site, multi-dimensional data of geological drilling, geological radar, geophysical prospecting testing and the like are acquired through various precise instruments, and a three-dimensional coordinate system is firstly established; and deep feature extraction is performed on complex data by using a deep learning algorithm, and key information such as geological stratification, rock and soil parameters and underground water level is accurately obtained. Intelligent fusion of multi-source data is realized by constructing a geological stratification model, a rock and soil parameter model and an underground water level model, and a comprehensive geological information model is generated. And importing the extracted geological profile data into a BIM platform, and carrying out strict precision verification and optimization by adopting a professional geological information collaborative equation set to finally form a highly accurate and reliable rail transit construction geological exploration profile.

The invention belongs to the technical field of geophysical exploration. The invention provides an inversion method and system based on transient electromagnetic and ground penetrating radar data collaborative correction, and the method comprises the steps: converting the preprocessed ground penetrating radar data into a format of transient electromagnetic detection data, or converting the preprocessed transient electromagnetic detection data into the format of the ground penetrating radar data; performing weighted summation on the ground penetrating radar data and the transient electromagnetic detection data after format conversion to obtain fusion data; performing three-dimensional joint inversion according to the fused data to obtain a final three-dimensional joint inversion result; according to the method, collaborative detection of different depths of the detection area is realized, a brand new underground structure detection interpretation scheme is provided through intelligent data preprocessing, intelligent correction and three-dimensional joint inversion technologies, and comprehensive, efficient and high-precision interpretation of the underground structure is realized.

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

The invention discloses an earth geology physical three-dimensional modeling method based on multi-data fusion, which comprises the following steps: A, data acquisition: acquiring geological data through geological exploration and measurement technologies, comprising geological profile, underground water level, lithology, structure, surface digital elevation model (DEM) data, remote sensing image data, surface geographic information data, drilling data, geological plane data, profile data, stratum isoline data, fault data, geophysical prospecting data, dynamic data and related document data. According to the invention, data of geological profile, underground water level, lithology, structure, earth surface digital elevation model (DEM) data, remote sensing image data, earth surface geographic information data, drilling data, geological plane data, profile data, stratum isoline data, fault data, geophysical prospecting data, dynamic data and related document data are collected. And the data can be effectively integrated.

The invention discloses a geological mineral exploration data extraction method and system, and relates to the technical field of geological mineral exploration data extraction, and the method comprises the steps: carrying out the data collection of a target region through a multi-source data collection method, obtaining satellite remote sensing data, unmanned aerial vehicle aerial survey data and ground geophysical prospecting data, and obtaining an original data set; preprocessing the collected data by adopting a preliminary data processing method, removing noise and correcting errors to obtain a high-quality data set; integrating data from different sources in the high-quality data set by adopting a weighted fusion algorithm to generate a comprehensive database and obtain a comprehensive data set; performing high-resolution geophysical exploration on the fused comprehensive data set by adopting a geophysical exploration technology to obtain underground structure information; analyzing the exploration data by adopting a geophysical inversion technology, and identifying the position of a potential ore body to obtain an ore body distribution map; the method is based on the comprehensive data set, underground structure information and the ore body distribution diagram.

The invention belongs to the field of geotechnical engineering and engineering geological information modeling, and relates to a stratum-parameter coupling randomness three-dimensional random field modeling and shield construction ground surface settlement rapid prediction method and device based on multi-source data fusion. According to the method, a three-dimensional joint random field acting on stratum types and rock-soil key physical property parameters at the same time can be constructed under the joint constraint of multi-source data such as drilling, geophysical prospecting, geotechnical tests and terrains, and a calibrated, explainable and updatable geological section automatic generation and uncertainty quantification channel is formed; on the premise that geological rationality is guaranteed, section geometry and parameter distribution under the conditions of complex structures and lateral phase change are restored robustly, the accuracy, consistency and interpretability of the three-dimensional geological section are remarkably improved, and a combined uncertainty result which can be directly used for rapid prediction and risk assessment of shield construction settlement is output. The technical problems that a geological section generated by an existing method is not accurate enough, uncertainty is difficult to quantify, and the extrapolation capacity of a complex scene is weak are solved.

The invention relates to the technical field of geophysical exploration, in particular to a multichannel deep learning magnetotelluric inversion method based on physical information constraint. The method comprises the following steps: generating a synthetic data set containing a geoelectric model and forward modeling response thereof, and adding a noise simulation actual observation condition; constructing a hybrid network architecture combining Transform and U-Net, taking apparent resistivity and impedance phase as dual-channel input, extracting global features by using an encoder, gradually recovering spatial resolution through a decoder, and outputting an underground resistivity model; network training adopts a composite loss function fusing model loss and data loss, and an inversion process is constrained by introducing a magnetotelluric forward modeling physical rule, so that a result is ensured to fit observation data and conform to a physical mechanism; after training is completed, preprocessed actual measurement data are input into the model, and a resistivity image can be directly obtained. The method is used for geological structure identification and reservoir interpretation, and the inversion precision and reliability are effectively improved.

The invention relates to the technical field of geophysical exploration, and particularly provides a three-dimensional finite element transient electromagnetic forward modeling calculation method based on an iterative solution method.The method comprises the steps that tetrahedron space discretization is carried out based on a vector finite element method, and an electric field is given to six edges of a space tetrahedron; constructing a back-pushing Euler finite element equation set, and assembling a linear system formed by a large sparse matrix based on the equation set; performing iterative solution on the linear system based on an FGMRES algorithm to obtain an electric field value corresponding to a spatial tetrahedron unit edge; optimizing a spatial tetrahedral mesh based on a quadratic nesting method, and optimizing a time step length based on a third-order backward Euler difference format; a grid pre-encryption method is adopted, the calculation error of iterative solution is reduced, a region decomposition method is used for achieving parallel calculation, and the calculation efficiency is greatly improved. According to the method, the requirements of high precision and high efficiency in three-dimensional transient electromagnetic forward modeling calculation can be met, and an advanced calculation tool is provided for resource exploration in a complex geological environment.

The invention provides a multi-source geophysical prospecting data fused Zenzenite rock mass contact zone anomaly method and system, and relates to the technical field of geophysical prospecting, the method comprises the following steps: executing joint denoising processing and time-frequency feature enhancement processing on a TFEM data set in a three-dimensional fused data volume, and outputting the optimized three-dimensional fused data volume; and based on the optimized three-dimensional fusion data body, by establishing a mapping relationship between magnetic, electric and polarization anomalies and a geologic body, quantifying the correlation between a multi-parameter combination and a mineralization index and screening an up-to-standard abnormal region, and finally delineating a magnetic anomaly gradient zone, a low-resistance region and a high-polarization anomaly co-occurrence ore prospecting target region three-dimensional distribution diagram. Through multi-source geophysical prospecting method collaboration, data deep fusion, quality optimization and accurate mapping, full-chain technology upgrading from data acquisition to target area delineation is realized, and the high efficiency of mineral exploration is improved.

The invention relates to the field of mine geophysical exploration, and discloses a fully mechanized coal mining face geological abnormal area prediction method based on multi-source data, and the method comprises the steps: carrying out the detection of a fully mechanized coal mining face through a radio pit penetrating device and a slot wave seismograph, and obtaining a working face CT image and a slot wave energy attenuation coefficient image; analyzing a distribution rule of a plurality of abnormal prompt areas in the working face CT image, and delimiting a plurality of candidate abnormal areas to obtain an average abnormal amplitude value of each candidate abnormal area; analyzing a plurality of slot wave attenuation high value abnormal regions in the slot wave energy attenuation coefficient imaging, and carrying out overlapping region calculation on the plurality of candidate abnormal regions to obtain a plurality of overlapping regions; carrying out drilling point arrangement and drilling according to the plurality of overlapped areas, and measuring a plurality of drilling trajectories and drilling data corresponding to each drilling point through a trajectory instrument; and according to the plurality of drilling trajectories and the drilling data corresponding to each drilling point, abnormal region prediction data is generated, so that accurate prediction of the abnormal region is realized.

The invention discloses an intelligent grouting pressure adjusting method and system based on deep learning, and relates to the technical field of grouting pressure adjustment. Geological and geophysical prospecting data of a to-be-grouted area before grouting construction are obtained; all parameters of the surrounding environment influence, the active regulation and control pressure pulse and the pressure pulse of the grouting equipment serve as the state S for describing grouting diffusion, all the parameters in the state S are input into a pre-trained grouting pressure influence prediction model, and the corresponding grouting effect is obtained; according to geological and geophysical prospecting data, the needed grouting diffusion threshold value state is calculated, all parameters in the state S, the corresponding grouting effect and the grouting diffusion threshold value state are input into a pre-trained grouting pressure regulation and control model, and the model takes the grouting diffusion threshold value state as the target of the grouting effect and outputs grouting pressure regulation operation; and according to the actual grouting condition and the real-time feedback of the actual grouting parameters, the grouting pressure regulation and control model is updated, so that the grouting pressure is regulated, and the grouting pressure is automatically and accurately regulated.

The invention belongs to the technical field of geophysical exploration in an extremely complex tunnel environment, and provides an air-ground and hole-tunnel multi-angle combined tunnel unfavorable geology advanced detection system and method.A first main control unit is used for establishing a unified time reference and controlling an air-ground capacitive induced polarization detection unit to collect air-ground electric field data under the unified time reference; the second main control unit is used for controlling the hole-tunnel induced electric field and natural electric field combined detection unit to collect underground induced polarization response signals and continuous natural electric field signals and controlling the tunnel seismic electric field detection unit to collect seismic electric field signals and seismic wave signals; and the second main control unit is used for receiving the air-ground electric field data sent by the first main control unit, uniformly integrating the air-ground electric field data with an underground induced polarization response signal, a continuous natural electric field signal, a seismic electric field signal and a seismic wave signal which are acquired by the second main control unit to obtain a multi-field data set, and performing interpretation and inversion to obtain a potential unfavorable geologic body identification result. And the disaster source detection precision and efficiency in the extremely complex tunnel environment are obviously improved.

The invention discloses an underground target imaging method and imaging system based on variable scale deep learning, and belongs to the technical field of geophysical exploration, and the method comprises the following steps: S1, building a multi-scale magnetic survey data set; s2, constructing a UNet + +-based variable-scale deep learning network model, and performing feature fusion on pooled information and information subjected to split convolution by a dynamic information fusion layer so as to adapt to input data of any size and make up for information loss caused by pooling; s3, designing a multi-constraint loss function formed by mean square error and loss weighting; s4, migration learning is adopted, model parameters trained in a fixed size serve as initial weights, progressive training of multi-size data is achieved by freezing and fine tuning of decoder parameters, and finally the effectiveness of the whole network model is verified according to a test set prediction effect, so that the universality and flexibility of the network are improved when data of different sizes are processed, and the network performance is improved. And large-size data features in a specific area can be quickly adapted.

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 a geological forecasting technology, discloses a tunnel advanced geological forecasting method based on multi-geophysical prospecting joint inversion and multi-source data fusion, and solves the problems of poor efficiency and reliability caused by lack of effective constraints of an initial inversion model during joint detection of existing multiple geophysical prospecting methods. And the judgment accuracy is influenced by the failure of deep fusion of multi-source geological data. The method comprises the following steps of: detecting geological conditions in front of a tunnel face by adopting advanced horizontal drilling and advanced geophysical prospecting to obtain an advanced horizontal drilling detection result and original data of each geophysical prospecting method; the method comprises the following steps of: establishing an initial model by taking a prior mean constraint and a structure constraint as means and utilizing an advanced horizontal drilling detection result, and carrying out echelon joint inversion of a multi-geophysical prospecting method by taking high-precision information as a prior condition of low-precision information and taking structural plane information as a prior condition of resistivity information inversion; carrying out dimension reduction fusion and cross correction on the inversion result of each parameter; and finally, identifying geological information in front of the tunnel face by explaining the meaning of the parameter data and imaging.

The invention provides a sandstone type uranium ore prospecting method based on a tectonic unit boundary, and the method comprises the steps: obtaining the geological data of a sedimentary basin, determining the spatial distribution and the tectonic and stratum characteristics of tectonic units in the sedimentary basin, and determining the types of beneficial metallogenic tectonic units according to the spatial distribution and the tectonic and stratum characteristics of the tectonic units; and determining a first-level exploration target region of the sandstone type uranium mine by combining the gravity data and / or seismic data and / or oil and gas bearing conditions of the favorable metallogenic structure units for different types of favorable metallogenic structure units. According to the method, on the basis of deep analysis of uranium-controlled metallogenic characteristics of the tectonic unit boundary, the upheaval and fracture of the tectonic unit boundary are taken as important marks for prospecting, and geological and geophysical prospecting methods are combined, so that a novel efficient and low-cost prospecting method is formed, an optimal target of a sandstone type uranium ore prospecting area can be accurately locked, and the prospecting efficiency of the sandstone type uranium ore prospecting area is improved. The blindness in the prospecting process can be obviously reduced, and the exploration efficiency is improved.

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 belongs to the technical field of tunnel engineering geophysical prospecting, and particularly relates to a full-wave-field tunnel advanced prospecting method based on rock physical constraint, which comprises the following steps of: constructing an initial geologic model, sampling on an upper interface of a layer section where a tunnel is located and carrying out longitudinal and transverse wave velocity measurement to obtain a longitudinal wave velocity Vp and a transverse wave velocity Vs; combining all sampled longitudinal wave velocities Vp and transverse wave velocities Vs, calculating longitudinal wave velocities and transverse wave velocities of a target layer section, obtaining elastic parameters of the target layer section, importing the obtained elastic parameters into an initial geologic model, obtaining a parameter inversion initial model, constructing a forward wave field and a simulated seismic record, and making a difference between an actual observation record and a simulation record, so as to obtain an initial geologic model; and conjugate gradient inversion is carried out. According to the method, all wave field information excited by the shield tunneling machine is fully utilized, and high-precision parameter inversion is carried out under rock physical constraints, so that more accurate tunnel front geological prediction can be provided, and a scientific basis is provided for safe and efficient construction of the shield tunneling machine.

The invention provides a denoising method for non-stationary nonlinear magnetotelluric sounding signals, and relates to the technical field of geophysical exploration, and the method comprises the steps: obtaining magnetotelluric sounding signals from a magnetotelluric depth finder, selecting one from the obtained magnetotelluric sounding signals, carrying out the denoising of the selected magnetotelluric sounding signals, repeating the above operation, and carrying out the denoising of the selected magnetotelluric sounding signals. And carrying out de-noising processing on the other acquired magnetotelluric sounding signals. VMD (variational mode decomposition) and ICA (independent component analysis) are combined, denoising of the magnetotelluric sounding signals is realized from multiple angles of time-frequency domain and statistical property, and when effective signals are interfered by long-time high-energy non-stationary noise, the method can ensure high quality of reconstructed signals, effectively reduce the influence of manual parameter selection, and improve the denoising performance of the magnetotelluric sounding signals. Compared with the prior art, the method has the advantages that the method is high in robustness to noise, clear physical interpretation is provided, limitation of a traditional denoising method is overcome, and a more reliable and accurate data processing means is provided for the field of geophysical exploration.

The invention discloses a gravity-magnetoelectricity three-dimensional joint inversion method based on reweighting, and belongs to the technical field of geophysics. According to the method, the resolution and physical property difference characteristics of data of geophysical gravity, a magnetic method and an electromagnetic method are fully utilized, and a more reliable underground structure model is obtained in a joint inversion mode; according to the method, gravity, magnetic and electric multi-field data are processed at the same time, and the method is suitable for mineral resource exploration, oil and gas reservoir exploration, deep structure research and other scenes under complex geological conditions, and especially has remarkable advantages in hidden ore body boundary recognition, lithologic contact zone positioning and the like; by integrating reweighting, cross gradient and efficient iteration technologies, the manual intervention and parameter debugging cost is greatly reduced, the automatic inversion process from data input to model output is realized, and the engineering application efficiency of geophysical exploration is improved.

The invention relates to the technical field of geophysical exploration data processing, and discloses a multi-element prospecting data cleaning and feature extraction system based on machine learning, and the system comprises a structure field generation unit which is used for constructing a multi-scale structure tensor field according to three-dimensional seismic data and extracting a structure vector representing a geological structure; the self-adaptive cleaning unit is used for carrying out abnormal value judgment and interpolation on non-seismic data by using the structural vector as prior guide information; the coupling feature generation unit is used for generating single-scale and cross-scale coupling features capable of deeply quantizing the relationship between the attribute change and the structure by calculating the projection of the non-seismic data gradient on different-scale structure vectors; and the feature output unit is used for combining the cleaned data, coupling the features and the original seismic attributes and constructing a high-dimensional final feature vector. According to the method, input with more geological significance is provided for machine learning, so that the precision and reliability of prospecting prediction are remarkably improved.

The invention discloses a semi-aviation transient electromagnetic signal adaptive gain method and system, and relates to the technical field of geophysical exploration, and the method comprises the steps: obtaining a differential signal of a receiving coil, and carrying out the chopping self-stabilization zero amplification processing of the differential signal; the method comprises the following steps: dividing a total time window of a differential signal into a plurality of time channels under a set time reference, adjusting the length of each time channel according to a signal attenuation characteristic, calculating the time length and data point number of each time channel according to a sampling rate and the total time window, and calculating the time length and data point number of each time channel; the data points are distributed to an early time channel, a middle time channel and a late time channel, so that different gain multiples are switched, and adaptive gain amplification is carried out; and the differential signal subjected to adaptive gain amplification is transmitted to a receiver after being collected by an ADC (Analog to Digital Converter). By dynamically adjusting the gain coefficient in different time channels, the technical problems of large dynamic range of transient electromagnetic signals and low signal-to-noise ratio of weak signals are solved, and high-fidelity acquisition of full-time-domain signals is realized.

The invention provides a method for reconstructing a grouting, water-retaining and water-resisting layer in a mining area and related equipment. Geophysical prospecting is carried out in a coal mining treatment area of a mining area from a water-bearing layer to a goaf, first apparent resistivity of all positions in a space is obtained, and the positions with the first apparent resistivity smaller than or equal to first preset resistivity in the space are selected to form a first dominant water guiding channel area; performing water flow direction testing on at least two monitoring wells in the coal mining treatment area to obtain a first flow direction fitting function of each monitoring well, and selecting two first flow direction fitting functions to calculate a first flow direction intersection point of the two corresponding monitoring wells; and when the first flow direction intersection point is located in the first dominant water guide channel area, grouting operation is conducted on the first dominant water guide channel area. The mining area grouting water-retaining and water-resisting layer reconstruction method and the related equipment provided by the invention are simple and convenient, grouting water retention can be quickly and accurately realized, the cost is low, and the loss of superficial water resources is effectively reduced.

The invention discloses an unmanned aerial vehicle airborne geophysical prospecting method and system based on big data, and the method comprises the steps: obtaining the positioning data of a global navigation satellite system and the measurement data of an inertial measurement unit, carrying out the correction and compensation through the combination of a differential positioning technology and a terrain height model, and obtaining an accurate three-dimensional coordinate data set; acquiring a magnetic field signal and a spectral signal according to the three-dimensional coordinate data set, and performing de-noising processing on the magnetic field signal and the spectral signal by adopting an adaptive filtering algorithm to obtain preprocessed signal data; judging whether the signal data volume of the preprocessed signal data exceeds a preset threshold value or not, if the signal data volume exceeds the preset threshold value, performing fragmentation processing on the preprocessed signal data through a distributed computing framework, extracting feature vectors in each piece of fragmented data by adopting a convolutional neural network, and generating a feature vector set; according to the invention, full-link optimization from data acquisition to ore body prediction is realized, and the precision and efficiency of geological exploration are improved.

The invention mainly relates to the technical field of geological prediction. In order to improve the accuracy and stability of a tunnel face geological prediction result, the invention provides a method for performing tunnel face geological prediction based on geophysical prospecting parameters and geological characteristic parameters, and the core idea of the method is as follows: extracting key geophysical prospecting parameters for performing geological prediction on a tunnel face from geophysical prospecting parameters of an excavated tunnel face; geologic characteristic parameters of the excavated tunnel face are collected according to the formulated geologic characteristic parameter description standard, and key geologic characteristic parameters for conducting geologic prediction on the tunnel face are obtained; a tunnel face geological prediction model is established, and the tunnel face geological prediction model comprehensively considers the characteristics of a geologic body from the two aspects of physical properties reflected by the key geophysical prospecting parameters and the geological background reflected by the key geologic characteristic parameters based on the key geophysical prospecting parameters and the key geologic characteristic parameters; and rock grade categories and geological disasters under complex geological conditions can be predicted more accurately.

The invention relates to the technical field of oil and gas geophysical exploration, and particularly discloses a tight sandstone gas reservoir fluid mobility gradient attribute prediction method and system.The method comprises the steps that a reflection coefficient expression containing a fluid mobility item is constructed, and a formula for calculating fluid mobility through frequency dispersion attributes is deduced; constructing a fluid mobility gradient attribute related to the frequency and the incident angle of the seismic wave; the method comprises the following steps: establishing a double-pore rock physical model, generating a synthetic seismic record, applying frequency variation AVO inversion to the synthetic seismic record, and extracting a bulk modulus dispersion attribute and a shear modulus dispersion attribute; and calculating the fluid fluidity changing along with the frequency and the incident angle, and calculating the gradient attribute of the fluid fluidity based on a gradient attribute calculation formula and the fluid fluidity. According to the method, seismic wave frequency dispersion and attenuation response caused by permeability and gas saturation are fully utilized, the seismic gradient attribute of the fluid fluidity and the calculation method are constructed, and high-precision prediction of the fluid fluidity by applying seismic signal elasticity and frequency dispersion rock physical information is realized.

The invention relates to the technical field of geophysical exploration, in particular to an optimal selection method for an oil-gas structure favorable area of a low-exploration-degree area of a mountain-front thrust zone. The method comprises the following steps: selecting an oil and gas prospective area, carrying out surface geological survey based on a regional geological map, compiling a surface fracture structure outline map and determining a main structure trend; performing wavelet decomposition on the gravity data to determine a substrate fracture adaptation result; deploying a magnetotelluric sounding profile in a direction perpendicular to the structure to obtain an electrical model, and compiling a substrate fracture diagram; deploying a sounding profile and a wide-line two-dimensional seismic profile fixed low-resistance strip in a parallel structure trend; a base depth map is calibrated, and a hidden strike-slip fracture layout is tracked; performing mesh generation to calculate indexes, performing standardized assignment, and performing mean value gridding; and preferably selecting an oil-gas structure favorable area by combining a drilling gas content fixed boundary. By adopting the ground measurement and multi-geophysical technology, the method is low in cost, simple to operate, high in efficiency and adaptive to a low exploration area, the optimization accuracy is improved, and powerful technical support is provided for optimization of an oil-gas exploration target area.

The invention discloses a loess collapsibility evaluation method and system based on a geophysical prospecting test technology, and relates to the field of land exploration, and the method comprises the steps: laying regular detection grids in a to-be-evaluated loess site, and constructing a site geographic coordinate system; collecting Rayleigh wave signals in real time, inverting a transverse wave velocity profile, and collecting apparent resistivity data; a shallow soil sample is drilled, soil property parameters are measured, and a model is constructed according to the mapping relation between the field geophysical prospecting parameters and the soil property parameters; inputting the acquired data into the wave velocity-water content correlation model and the resistivity-dry density correlation model to generate a water content distribution field and a dry density distribution field; and calculating the collapsibility of loess in each detection grid based on a geophysical prospecting response equation of the collapsibility coefficient, outputting a collapsibility coefficient contour cloud picture, and judging the collapsibility grade of each grid and the distribution range of collapsed loess. The method has the advantages that the collapsibility distribution field and the contour cloud picture are generated through accurate non-intrusive data acquisition and model analysis, and a scientific basis is provided for engineering construction.

The invention relates to the technical field of geophysical exploration, in particular to a pure-data-driven Marchenko multiple suppression method based on SVT nuclear norm constraint, and the method comprises the steps: collecting seismic data, and carrying out the preprocessing of the seismic data, and enabling the seismic data to serve as an actual medium; introducing a reference medium and setting a focus point; inputting the actual medium, the reference medium and the focus point into an MME (Mobility Management Entity) algorithm to start iteration until a preset number of iterations is reached, and obtaining an iteration result; wherein the iteration is divided into an odd number of iterations and an even number of iterations, and the odd number of iterations and the even number of iterations are respectively used for updating the downlink focusing function and the uplink focusing function by introducing an SVT nuclear norm constraint operator; and extracting primary wave data at the focus point at each sampling moment based on the iteration result by using an uplink Green function, traversing all sampling moments, constructing a primary wave data set, and completing suppression. According to the invention, the precision and reliability of seismic data processing can be improved.