572 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 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 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 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 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 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 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 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 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.

The invention belongs to the technical field of coal mine green mining and disaster prevention and control, and particularly relates to a caving area gangue grouting and filling method for recycling underground coal mine water resources. And zero emission and efficient cyclic utilization of water resources are realized. The coal gangue is used as a main filling aggregate and is directly digested underground, so that the problems of land occupation and environmental pollution caused by ground stockpiling are avoided, and harmless and large-scale treatment of the coal gangue is realized. A water treatment system and a gangue treatment system are combined into a whole, the comprehensive operation cost of a mine in the aspects of water disaster prevention and control, gangue treatment and outsourcing of a water source is remarkably reduced through a cyclic operation mode, and the cost benefit is high. Accurate detection and effect verification of the previous and later ponding areas are carried out through a geophysical prospecting means, and measures such as directional drilling and safety monitoring are combined, so that controllability and safety of the whole operation process are ensured, and the safety and reliability are high.

The invention discloses a thermal-fluid-solid medium seismic wave simulation method, device, program and medium, and relates to the technical field of oil and gas resource geophysical exploration, and the method comprises the following steps: constructing a first-order thermal-fluid-solid coupling wave equation in an equation coupling form; constructing a coupling wave equation staggered network finite difference discrete format; analyzing numerical stability conditions; constructing a complete matching layer absorption boundary; and performing forward modeling simulation of seismic waves in the three-layer heat-fluid-solid coupling model according to the model parameters and the seismic source parameters. The method breaks through the assumption that the classical seismic wave propagation theory is completely elastic under the isothermal or adiabatic deformation condition, considers the influence of temperature change on the propagation of seismic waves in fluid and solid media, and improves the description precision of the propagation process of the seismic waves in the heat-fluid-solid media. And the capability of inverting the underground temperature field based on seismic wave data in the later period can be effectively improved.

The invention provides a comprehensive advanced geological forecasting method for an ultra-deep vertical shaft of a metal mine, and belongs to the technical field of water prevention and control in construction of the ultra-deep vertical shaft of the metal mine. The conditions that a tectonic fracture zone, a high confined aquifer and the like possibly exist in the deep stratum, have construction hidden dangers and are prone to causing water burst disasters are accurately recognized, and the advanced detection precision of the deep stratum of the shaft is improved; meanwhile, a feedback forecasting process of geological analysis-geological modeling-geophysical prospecting circle target-drilling verification is formed, a multi-level verification system is constructed, the specific geological condition of an abnormal area is clearly detected, and the advanced positioning and judgment accuracy of a geological abnormal body in a deep stratum is remarkably improved; and by integrating and fusing multi-source geological information, the geological abnormal body information is comprehensively analyzed and judged, so that the requirements of deep rock mass mechanical property analysis and water inrush disaster prevention and control are met.

The invention relates to a seabed elastic parameter inversion method, system and device under an earthquake spherical reflection wave oscillation-gradual change nuclear decoupling framework, and belongs to the field of geophysical detection and acoustic detection. The method comprises the following steps: (1) inputting observation data and initializing seabed elastic parameters; (2) determining an integral interval and decomposing the integral interval into a plurality of sub-intervals; (3) calculating an oscillation nuclear local integral matrix corresponding to the incident angle of the observation data; (4) calculating a slowly-varying kernel local mean vector; (5) calculating a spherical wave reflection coefficient of oscillation-gradual change kernel decoupling; and (6) constructing a target function by using the decoupled spherical wave reflection coefficient, and solving the target function. In the objective function solving process, only the steps (4) and (5) need to be repeatedly executed after the seabed elastic parameters are updated, the oscillation nuclear local integral matrix in the step (3) does not need to be repeatedly calculated, redundant calculation about oscillation nuclear integration is avoided, and the calculation efficiency is improved.

The invention belongs to the technical field of physical exploration, and particularly discloses a deep geophysical prospecting weak abnormal signal enhancement method and system, and the method comprises the steps: generating a geostructured prior guide field, carrying out the targeted decomposition of an original geophysical prospecting signal, and synchronously estimating an uncertainty region, thereby achieving the real-time enhancement of a weak abnormal signal while maintaining the fidelity of background information; focusing the enhanced resources in the information fuzzy region; the decomposition signals are input into a dynamic learning model, and random noise and structured interference generated by multiplicity are effectively suppressed through antagonistic learning; the enhanced sub-band signals are fused into reconstructed signals with high geological interpretability by using a deep reconstruction network through a self-attention mechanism and compound loss function optimization; a closed-loop feedback mechanism is established, newly disclosed high-confidence anomaly features are fed back and integrated to a prior field, an iteration guide field is formed to drive multi-round iteration, step-by-step mining and locking of weak anomalies are achieved, and finally a high-reliability result is stably converged.

The invention relates to the field of oil and gas geophysical exploration, and particularly discloses a reservoir physical property parameter seismic inversion evaluation method and device, and the method comprises the steps: building a rock physical model based on the geological features of a work area reservoir; based on the rock physical model, sequentially carrying out inversion test on seismic traces beside a modeling well, a non-modeling well and all wells in a work area to determine parameters of the rock physical model and an inversion algorithm; utilizing the rock physical model and an inversion algorithm to perform seismic inversion on the physical property parameters of the work area reservoir to obtain an inversion result; and extracting a work area well connection profile and reservoir section plane attributes from the inversion result, and then performing analysis. According to the reservoir physical property parameter seismic inversion evaluation method, on the basis of problems needing to be noticed in the reservoir physical property parameter seismic inversion process of the rock physical model and the quality control mode, the trial and error processes in the technical inversion process can be reduced, the working efficiency of reservoir physical property inversion is improved, and the technical practicability is improved.

The invention discloses a surface modeling method based on high-speed top interface reflection time, and relates to a geophysical exploration method, in particular to a surface modeling method based on high-speed top interface reflection time, which comprises the following steps of: acquiring early seismic exploration acquisition data of a research area, picking up cannon first arrival time and calculating a uniform reference surface static correction value; processing the original single-shot record based on the uniform reference surface static correction value to obtain the first arrival time of the large shot and the minimum offset reflection time after static correction; calculating the weathered layer velocity of the shot point, and obtaining the weathered layer velocities of all detection points; within the minimum offset range of each shot point; the high-speed top interface elevation of each shot point is calculated, and a surface layer model is established according to the weathered layer speeds of all the detection points, the weathered layer thickness of each shot point and the weathered layer thickness parameters of each detection point. According to the method, the technical problems of high exploration cost and low model precision in near-surface modeling of the area are effectively solved.

The invention discloses a permafrost roadbed structure design method based on railway long-term deformation control, which comprises the following steps of: carrying out comprehensive investigation and physical and mechanical property analysis on frozen soil through geological plotting, geological drilling and comprehensive geophysical prospecting; according to investigation and analysis results, determining layered distribution characteristics of the permafrost of the foundation; according to the layered distribution characteristics of the permafrost of the foundation, parameters of a roadbed structure are set; calculating and analyzing the cooling capacity demand of the permafrost roadbed; setting a railroad bed deformation control standard; and according to the cooling capacity requirement and the railway roadbed deformation control standard, combining the parameters of the roadbed structure, and designing to obtain the hot rod roadbed structure. The scientific and intelligent permafrost hot rod roadbed design method can be realized, long-term deformation control and dynamic adaptability guarantee is provided for railway engineering in cold regions, the operation and maintenance cost is reduced, and the service life of the roadbed is prolonged.

The invention is applicable to the field of oil and gas geophysical exploration, and provides a shale solid skeleton and organic matter elastic parameter synchronous prediction method, which comprises the following steps of: constructing a rock physical model for representing a shale reservoir solid skeleton elastic modulus and an organic matter elastic modulus; developing an in-well inversion method based on the rock physical model; combining a rock physical model and a scattering function theory, and establishing a reflection coefficient formula represented by shale solid skeleton elasticity modulus, organic matter elasticity modulus and density parameter linearization; a reflection coefficient formula and a Bayesian linear inversion theory are combined to develop an earthquake rock physical inversion method; applying synthetic seismic data, and testing and verifying the effectiveness of the seismic rock physical inversion method constructed in the step E; and then the method is applied to actual seismic data to predict the elasticity modulus of a shale gas reservoir solid skeleton and organic matters in a research area, and an effective method is provided for brittleness evaluation of a shale gas reservoir engineering dessert and organic matter enrichment prediction of a geological dessert.

The utility model provides an engineering geophysical prospecting geological radar protection device. The engineering geophysical prospecting geological radar protection device comprises a base, an obstacle crossing structure, a protection shell, a clamping structure and a geological radar detector body. Obstacle crossing structures are arranged on the two sides of the base respectively; a cavity is formed in the top of the base, and a protective shell is arranged in the cavity; a geological radar detector body and a clamping structure are arranged in the protective shell, and the clamping structure is used for clamping the geological radar detector body. According to the geological radar protection device, through the arrangement of the obstacle crossing structure, the geological radar protection device can adapt to different terrains, especially complex terrains, the terrain adaptability of the geological radar protection device is enhanced, and the obstacle crossing structure has a certain buffering effect in the obstacle crossing process, so that the stability of the device is guaranteed; through the clamping structure, the device can be suitable for geological radar detector bodies of different sizes, the applicability of the protection device is improved, clamping fixation is completed by screwing an insertion rod into a threaded groove, the structure is simple, and operation is convenient.

The invention discloses a geophysical prospecting signal denoising method based on VMD (variational mode decomposition) combined with an improved wavelet threshold function, and belongs to the technical field of mineral exploration geophysical prospecting signal process.The method includes the steps that firstly, a decomposition mode number K of a signal is determined through VMD in a self-adaptive mode, a plurality of IMFs (intrinsic mode components) are obtained, and then according to the frequency characteristic and noise distribution of each IMF component, a wavelet threshold function is obtained; and carrying out targeted noise suppression by adopting an improved wavelet threshold function containing an adjustment parameter alpha, and finally, carrying out linear superposition reconstruction on all the processed IMF components to obtain a de-noised geophysical prospecting signal. Experimental verification shows that compared with a traditional method, the method has the advantages that the signal-to-noise ratio and the correlation coefficient of the noisy geophysical prospecting signals can be effectively increased, the root-mean-square error can be effectively reduced, the inherent defects of the traditional method are overcome, the geologic features of the geophysical prospecting signals can be effectively reserved, the method is suitable for various mineral exploration scenes, and reliable data support is provided for anomaly recognition in mineral exploration.