551 results about "Geophysical prospection" patented technology

The invention is suitable for the technical field of geophysical exploration, and provides a ground-air transient electromagnetic airborne receiving coil motion noise extraction method, which comprises the following steps: designing a receiving device carrying an IMU (Inertial Measurement Unit) sensor, the receiving device comprising a receiving coil, the IMU sensor and a synchronous clock; measuring a vector geomagnetic field in a transient electromagnetic detection area based on attitude angle data of the receiving device; and extracting the motion noise of the airborne transient electromagnetic coil based on the vector geomagnetic field and the attitude angle data. The invention designs a ground-air transient electromagnetic receiving device, and provides a method for extracting motion noise of an airborne receiving coil based on the ground-air transient electromagnetic receiving device, so that the problem that the motion noise is generated due to the fact that the coil cuts a geomagnetic field is effectively solved. Compared with a mode of directly separating the motion noise from the induced electromotive force signal, the method provided by the invention can directly extract the motion noise from the generation mechanism level of the motion noise, and effectively avoids the problem of incomplete noise extraction or target signal loss.

The invention relates to the technical field of geophysical exploration, in particular to an exploration surveying and mapping method based on remote sensing and a surveying and mapping instrument thereof. The exploration surveying and mapping method based on remote sensing comprises the following steps: step 1, multi-platform collaborative data dynamic acquisition; step 2, multi-modal data fusion and feature enhancement: vegetation noise filtering is performed on the laser radar point cloud data, and a surface terrain model under vegetation coverage is reconstructed; seismic wave speed data and ground penetrating radar dielectric constant data are combined to construct an underground medium physical property combined distribution model; associating the reflectivity characteristics of the multispectral image with the underground physical property parameters, and identifying a geological abnormal region; and step 3, hidden geologic body dynamic modeling and risk assessment. By means of the method, real-time monitoring and risk assessment of the complex geologic body can be achieved, and the geological disaster prediction and prevention and control capacity is greatly improved.

The invention discloses a semi-supervised seismic wave impedance inversion method and system based on Swin Transform iterative gradient correction, and belongs to the technical field of earthquakes in geophysical exploration. According to the method, the impedance gradient is iteratively corrected in the model space through the deep neural network, and complex nonlinear prior information is captured; and each anisotropic structure direction regularization item is established, and constraint is carried out along the direction of the stratum structure, so that the space consistency of the prediction result is ensured. Meanwhile, the USTNet network designed by the invention combines the advantages of the local feature capture capability of the convolutional neural network and the global modeling capability of Transform, and reduces the non-uniqueness of solutions. The network is used for inverting synthetic data and actual data, and the effectiveness of the method is verified.

The invention discloses a geological disaster real-time monitoring method and system based on a ground sensing network, and belongs to the technical field of geophysical exploration, and the method comprises the steps: obtaining an acceleration parameter and a moisture content parameter of each sensor node; according to the change rate of the acceleration parameter and the moisture content parameter, identifying an environment sudden change event, generating an environment trigger signal to activate an emergency sampling mode of a target node and an adjacent node, and constructing a dynamic monitoring cluster; requesting a plurality of nodes in the dynamic monitoring cluster to synchronously measure similar parameters, and comparing measurement results to generate a compressed alarm packet; adjusting weight factors of different monitoring parameters by using the compressed alarm packet and pre-acquired real-time environment parameters, and generating an environment calibration risk index; and when the environment calibration risk index exceeds a preset risk threshold value, outputting a geological disaster early warning instruction. According to the method, multi-parameter cooperative triggering, dynamic cluster response, weight adaptive evaluation and compression transmission technologies are adopted, and the monitoring precision, timeliness and environmental adaptability can be comprehensively improved.

The invention relates to the technical field of mine safety monitoring and geophysical exploration, in particular to a mine water disaster intelligent alarm system responding to multi-dimensional physical field parameter abnormity, which comprises a full-space data acquisition module for acquiring monitoring area observation data and calling a background geological physical model; the ideal reference reconstruction module is used for constructing an ideal physical field reference in a non-abnormal state; the double difference extraction module is used for calculating an observation residual error of observation data relative to a reference and a theoretical residual error of simulation response relative to the reference; the inversion coupling verification module is used for driving the theoretical residual error to approach to the observation residual error and extracting parameter sensitivity characteristics; the intelligent alarm judgment module is used for analyzing sensitivity characteristics and convergence states; generating an alarm instruction if the feature is determined to be the entity fluid abnormal feature; if it is determined that the target abnormal interference feature is not the target abnormal interference feature, signal suppression processing is executed; according to the invention, the false alarm rate of mine water disaster detection is greatly reduced.

The invention relates to a geotechnical engineering geological investigation system and an investigation method thereof, which are used for solving the problems of drilling redundancy, repeated model correction and long period caused by traditional uniform hole distribution. The system comprises a geophysical exploration module, a rock-soil body structure feature extraction module, a geological abnormal area identification module, a survey detection point dynamic optimization module, a drilling sampling analysis module and a geotechnical engineering stability evaluation module. Earth material exploration is carried out on representative points to obtain a comprehensive geophysical prospecting data set, inversion is carried out according to the comprehensive geophysical prospecting data set to obtain a three-dimensional rock-soil structure, an abnormal area is recognized, accordingly, the drilling layout is dynamically optimized, and stability evaluation is completed at a time after a small amount of directional drilling sampling is carried out. By adopting the system, a high-precision geologic model and a stable evaluation result can be obtained with fewer drilled holes in a preliminary exploration stage, the cost is remarkably reduced, and the period is shortened.

The invention discloses a shallow velocity model construction method based on joint inversion, and relates to the technical field of geophysical exploration. According to the method, high-frequency Rayleigh wave information and far-earthquake cross convolution waveforms in natural earthquakes are introduced into joint inversion, the influence of parameters on a speed structure model is considered, interference of other types of waves on Rayleigh waves is avoided, noise segments dominant by Rayleigh wave energy are effectively screened out, and the method is suitable for large-scale popularization and application. The difficulty of extracting the ellipticity of the high-frequency Rayleigh wave from a single waveform is effectively solved; the three-dimensional velocity structure model of the shallow imgabs0 # and the three-dimensional velocity structure model of the shallow imgabs1 # of the whole earth crust can be effectively simulated through joint inversion, especially for a sedimentary layer, research of deep structure scientific problems of a research area and exploration and development of oil and gas resources are facilitated, the seismic oscillation simulation precision can be improved, and earthquake resistance and disaster reduction work in an earthquake area can be assisted.

The invention discloses a three-dimensional intelligent seismic velocity modeling method based on a two-dimensional self-attention U-shaped network and low-rank adaptation, and belongs to the technical field of seismic services of geophysical exploration. The problems that in the prior art, a traditional three-dimensional intelligent seismic velocity modeling method is low in efficiency and insufficient in model generalization ability are solved. The method comprises the following steps: generating a three-dimensional hybrid geological velocity model, obtaining multi-shot seismic record data based on a wave equation, obtaining a three-dimensional initial velocity model through Gaussian filtering, and obtaining an imaging result by adopting reverse time migration; carrying out dimension reduction processing on the three-dimensional data, and constructing a multi-dimensional pre-training sample set; carrying out pre-training by utilizing the training set to obtain an optimized LAUNet framework; and performing fine tuning by adopting a dual-stage collaborative optimization mechanism, and obtaining a fine-tuned LAUNet framework through a LoRA * method. The method effectively improves the model inversion efficiency, and can be applied to the establishment of a three-dimensional intelligent seismic velocity model.

The invention discloses an underground physical characteristic prediction method and system combining seismic waves and drilling data, and relates to the technical field of geophysical exploration, and the method comprises the steps: collecting original seismic records, carrying out the preprocessing, obtaining a three-dimensional seismic data body, carrying out the complex channel analysis of the three-dimensional seismic data body, extracting the instantaneous amplitude, instantaneous phase and instantaneous frequency attributes, and carrying out the calculation of the instantaneous amplitude, instantaneous phase and instantaneous frequency attributes. Fault features are identified through a coherent body algorithm, an earthquake feature matrix is obtained, depth alignment and correction are carried out on density logging, interval transit time and neutron porosity curves of drill holes, and a standardized drill hole data table is generated; and based on the seismic feature matrix and the standardized drilling data table. According to the method, deep complementation of the earthquake macroscopic information and the borehole local truth value is realized through the geometric perception multi-modal graph neural network and the dynamic gating fusion mechanism, the problems of insufficient cross-modal feature fusion and misalignment of physical rules in the prior art are solved, and the prediction precision and reliability under complex geological conditions are remarkably improved.

The invention relates to the field of geophysical exploration, and discloses a seismic data noise suppression method, which comprises the following steps: screening adjacent shot interference from an original single shot record by using a tau-p-q domain sparse inversion method to obtain a primary single shot record; linear interference is screened out from the primary single-shot record in a frequency domain transformation mode, and a secondary single-shot record is obtained; extracting an energy threshold value of the secondary single-shot record by utilizing a frequency division energy statistics mode, and performing primary noise suppression on the secondary single-shot record by utilizing the energy threshold value to obtain a de-noised single-shot record; and respectively extracting a primary effective signal and a surface wave signal from the de-noised single-shot record, extracting a standard single-shot record from the primary effective signal and the surface wave signal by using a frequency division noise automatic identification and attenuation method and an adaptive spectrum editing method, and ending noise suppression. The invention further provides a noise suppression device and equipment for seismic data, a medium and a program. According to the invention, the accuracy of seismic data imaging can be improved.

The invention relates to the technical field of geophysical exploration equipment, and particularly discloses a double-top umbrella type multi-angle adjustable transient electromagnetic transmitting coil array detection device which comprises a main supporting system, a framework supporting system, a coil system, a multi-angle adjusting mechanism and a rapid storage system. The device has the beneficial effects that accurate adjustment in a continuous angle range is realized, and the adaptability of the device to different exploration environments is improved; a double-coil system design is adopted, so that two typical working modes are realized; in structural design, a double-top umbrella type folding structure is combined with a light-weight material, so that the weight of equipment is reduced. According to the device, conversion of multiple detection modes is achieved, traditional multiple fixed angle devices are replaced, the equipment investment cost is reduced, and the equipment operation efficiency is improved.

The invention relates to a transient electromagnetic and seismic wave multi-mode joint inversion imaging method based on physical information Transform, and belongs to the crossing field of geophysical exploration and artificial intelligence. Comprising the following steps: carrying out anomaly detection, interpolation, filtering and normalization preprocessing on transient electromagnetic and seismic wave original data; extracting features representing electrical property, elasticity and cross physical significance; serializing the spatial data through a gridding and alternating fusion strategy, and constructing an enhanced code fusing absolute and relative positions and physical attributes; a physically constrained encoder-decoder architecture is designed to carry out multi-scale forward modeling-inversion; and quantizing the uncertainty of an inversion result by adopting a Bayesian Monte Carlo method, and generating a confidence map. According to the method, through physical rule driving and multi-modal depth complementary fusion, the fine recognition capability and interpretation reliability of hidden disaster-causing geologic bodies such as underground goaf and collapse columns are effectively improved while the physical consistency of data is kept.

The invention discloses a deep rock mass fracture imaging method and system based on micro-seismic monitoring, and belongs to the technical field of geophysical exploration, and the method comprises the steps: collecting multi-channel micro-seismic event waveform data, obtaining a main seismic phase direct waveform and a scattering tail waveform through wave field separation, and carrying out the imaging of a deep rock mass fracture. Determining a three-dimensional space coordinate and an energy distribution form of the seismic source through joint inversion, carrying out clustering analysis, and constructing an initial three-dimensional space distribution form; each seismic source is regarded as an active excitation source, a scattering tail wave waveform is regarded as a reflection signal, scatterer three-dimensional point cloud data is generated through reverse time migration processing, analysis is carried out in combination with an initial three-dimensional space distribution form, and an enhanced fracture structure is formed; and finally, through topology analysis and orientation clustering, discrete scatterers are eliminated, and a fracture development map is generated. According to the method, a technical path of combining a main seismic phase direct wave inversion seismic source and a scattering tail wave inversion scatterer is adopted, high-precision and high-fidelity imaging of a deep rock mass movable fracture can be realized, and physical activity is revealed.

The invention discloses a seismic wave velocity-resistivity joint inversion method based on a time dimension, belongs to the technical field of geophysical exploration, and can solve the problem that the dynamic change of a geological structure cannot be determined in the prior art. The method comprises the following steps: constructing a seismic wave velocity distribution model according to seismic exploration data of a target area, and constructing a resistivity distribution model according to electromagnetic exploration data of the target area; determining an objective function of seismic wave velocity-resistivity joint inversion according to the seismic wave velocity distribution model and the resistivity distribution model; updating and iterating the seismic wave velocity distribution model and the resistivity distribution model according to the seismic exploration data and the electromagnetic exploration data of the plurality of periods until the objective function is minimized; and according to the corresponding seismic wave velocity distribution model and the resistivity distribution model when the target function is minimized, respectively determining seismic wave velocity inversion results and resistivity inversion results of the target area in multiple periods. The method is used for inverting the seismic wave velocity and the resistivity.

The invention relates to the field of petroleum geophysical exploration, in particular to a chromatography velocity modeling method, device and equipment. The tomography velocity modeling method comprises the following steps: acquiring depth migration imaging gathers of a plurality of azimuth angles of a research work area according to an initial tomography velocity model; determining a dominant azimuth angle based on the depth migration imaging gather of the plurality of azimuth angles of the research work area; constructing an azimuth angle weight matrix according to the dominant azimuth angle; and updating the initial chromatography velocity model according to the azimuth angle weight matrix. According to the embodiment of the invention, the dominant azimuth angles can be determined according to the depth migration imaging gathers of the plurality of azimuth angles of the research work area, the weight matrix is constructed according to the dominant azimuth angles so as to determine the tomography speed updating amount, more stable and higher-precision tomography speed inversion is realized, the tomography speed modeling efficiency is improved, and the modeling cost is reduced. And the actual production application of the complex exploration orientation distinguishing grid chromatography velocity inversion technology is promoted.

The invention discloses a method for generating a reflection angle domain point spread function based on an LSTM network, and belongs to the technical field of geophysical exploration, and the method comprises the following steps: S1, selecting a reference point, and constructing a label through ray tracing and wave equation forward modeling; s2, training an LSTM (Long Short Term Memory) network as a ray tracing agent model of the whole space of an imaging domain; s3, predicting a travel time gradient and an amplitude factor through a ray tracing agent model; s4, combining the seismic source and the geophone in pairs, and calculating a reflection angle through the travel time gradient; s5, solving an illumination wave number vector, and solving a wave number domain point spread function in combination with the illumination intensity; s6, performing inverse Fourier transform on the wavenumber domain point spread function to obtain a spatial domain point spread function; and S7, solving a deconvolution problem to optimize the angle gather. According to the method, the calculation efficiency of solving the Green function through seismic wave ray tracing can be improved, the imaging response described by the point spread function is eliminated from the imaging result, and the balance of the resolution of the imaging result and the illumination intensity can be improved.

The invention belongs to the technical field of geophysical exploration, and particularly relates to a method and a system for quantitatively measuring intrinsic parameters of bedrock fractures based on all-angle domain amplitude and phase joint inversion. The method comprises the following steps: acquiring geological radar reflection data of a target fracture at a plurality of incident angles; synchronously extracting data sequences of amplitude change along with angles and phase change along with angles; establishing a fracture reflection theoretical model; constructing a target function jointly constrained by the amplitude residual and the phase residual; and adopting a global optimization algorithm to minimize the target function, and synchronously inverting to obtain the fracture opening, the filler dielectric constant and the occurrence parameter. According to the invention, through the combined constraint of the amplitude and the phase, the inversion multiplicity is effectively inhibited; accurate system effect correction is adopted, so that the reliability of large-angle data is ensured; according to the method, multi-parameter synchronous inversion without prior hypothesis is realized, the inversion precision is small in relative error, the method is obviously superior to a traditional method, and the method has important engineering application value.

The invention belongs to the technical field of geophysical exploration, and provides an ultra-wideband active electromagnetic intelligent detection method and platform, and the technical scheme comprises the steps: configuring detection parameters of an unmanned plane transient electromagnetic detection module and an unmanned plane ground penetrating radar module according to a cooperative detection demand; based on the configured detection parameters, performing preliminary detection on the specified detection area to obtain transient electromagnetic data and ground penetrating radar data; interpreting the transient electromagnetic data and the ground penetrating radar data to generate an imaging result; and determining the depth and position of the detection target based on an imaging result, re-determining an abnormal region range based on the depth and position of the detection target, and determining an optimal detection parameter combination of the unmanned aerial vehicle transient electromagnetic detection module and the unmanned aerial vehicle ground penetrating radar module according to the abnormal region range. According to the method, the unmanned aerial vehicle cooperative detection technology, the multi-frequency detection technology and the imaging technology are combined, the limitation of the prior art is solved, a new refined cooperative detection method is provided, and the method is suitable for various application scenes.

The invention discloses a consistency detection method, device and system for large-scale seismic signal acquisition equipment, and relates to the technical field of geophysical exploration. The method is executed by computer equipment in a large-scale seismic signal acquisition equipment consistency detection system, and after background noise original data continuously and synchronously acquired by a plurality of seismic signal acquisition equipment is received, an accumulated power spectrum variance value of each acquisition equipment is obtained through preprocessing and multi-step calculation in sequence; and finally, according to the accumulated power spectrum variance value of each acquisition device and the distance from each acquisition device to the layout center position, determining the acquisition device with an abnormal relationship in the relationship dimension of the accumulated power spectrum variance and the acquisition time or the relative distance. The purpose of efficient, reliable and automatic consistency detection on large-scale seismic signal acquisition equipment can be achieved, and then the detection result can accurately reflect the performance state of a seismic instrument.

The invention discloses a hidden ore body multi-source data fusion prediction method and system, and belongs to the technical field of geophysical exploration data processing, and the method comprises the steps: carrying out the standardization of obtained multi-source exploration data, and generating standardized data; quantifying errors of the standardized data in spatial positions and attribute values to generate a multi-source data set; constraining the multi-source data set according to a physical rule to obtain physical constraint embedded data; performing multi-scale feature extraction on the physical constraint embedded data to generate a multi-source feature map; performing cross-source and cross-scale association on the multi-source feature map to generate a fusion feature vector; and based on the fusion feature vector, predicting the mineralization probability, the physical property parameters and the uncertainty distribution, and generating a prediction result map. According to the method, multi-source data standardization, physical law constraint embedding, multi-scale feature fusion and uncertainty quantification technologies are adopted, and a three-dimensional mineralization prediction result with reasonable geology and controllable risk can be generated.

The invention discloses a stratigraphic water content layering inversion method based on a shallow seismic full waveform, and relates to the technical field of geophysical exploration data processing, and the method comprises the following steps: 1, under the same survey line condition, synchronously obtaining a seismic wave full waveform, complex impedance and an induced polarization frequency spectrum; 2, constructing a layered initial model containing a layer boundary line and an in-layer water content initial value; based on the layered initial model, executing dual-domain quantile alignment interface keeping iteration until convergence, and obtaining a final layer boundary line and an in-layer water content field; the double-domain quantile alignment interface maintaining iteration comprises the following steps: updating an in-layer moisture content field and a layer boundary line according to a seismic wave full waveform; and performing total variation regularization processing on the updated in-layer water content field to maintain the transition characteristic of the layer boundary line. According to the method, an efficient and reliable solution with actual guidance value is provided for mineral resource exploration, geological structure detection, groundwater survey and engineering geology evaluation.

The invention relates to the technical field of oil and gas geophysical exploration, in particular to a high-resolution seismic inversion recognition method for a thin and small reservoir of an oil reservoir. The method comprises the following steps: performing digital core model construction on a thin and small reservoir core sample to obtain a three-dimensional digital core model; carrying out multi-mineral component quantitative analysis on the thin and small reservoir core sample to obtain mineral components and distribution data; performing fracture geometric analysis on the three-dimensional digital core model to obtain fracture geometric analysis data; constructing a microscopic rock physical model according to the fracture geometric analysis data and the mineral composition and distribution data, and calculating physical model parameters to obtain microscopic rock physical parameters; and calculating matrix pore elastic parameters according to the microscopic rock physical parameters to obtain pore-containing dry rock elastic parameters. According to the method, the problems that a traditional method is low in resolution and influences of reservoir fluid and fractures are ignored are effectively solved, and high-precision recognition and fine description of the thin and small reservoir are achieved.

The invention relates to the technical field of hydrogeology, in particular to a karst underground water system characteristic analysis method and system. The method comprises the following steps: identifying an X-shaped joint controlled by a structural composite part through hydrogeological survey and geophysical exploration; plane distribution of underground water is determined, the position of an underground water main runoff zone on the plane is determined through drilling verification, and vertical feature extraction analysis is conducted on the underground water main runoff zone; analyzing the concentration and distribution characteristics of pollutants in the underground water, and identifying a pollutant transport channel; according to the vertical characteristics, multiple layers of water outlet sections in the vertical direction of the aquifer and relative water separation sections between the water outlet sections are determined; constructing a three-dimensional model of the hydrogeological structure, simulating underground water flow and pollutant migration, and predicting dynamic change characteristics of a future underground water system according to a simulation result; an on-site monitoring network is constructed, long-term monitoring is carried out, and the risk of the underground water system is identified. According to the technical scheme, the comprehensiveness and accuracy of karst underground water system analysis can be improved.

The invention relates to the technical field of geomagnetic vector measurement, and discloses an error correction method of a cross-shaped magnetic gradient tensor measurement system. According to the method, a coupling model containing a sensitivity error, a non-orthogonal error, a zero offset error and an array non-alignment error of a single fluxgate sensor is established, and a fitness function is designed to solve error parameters by utilizing the characteristics of high global search capability and high convergence speed of a firefly optimization algorithm (FA). Compared with the existing particle swarm optimization and the least square method, the method has the advantages that the correction precision of zero offset and non-alignment errors is remarkably improved, the single-sensor zero offset error estimation deviation is smaller than 2%, the array non-alignment angle error deviation is smaller than 1.5%, expensive equipment support is not needed, and real-time on-site implementation can be achieved. The method is suitable for the fields of magnetic anomaly detection, geophysical exploration and the like, and has the advantages of low cost, simplicity and convenience in operation and remarkable correction effect.

The invention belongs to the technical field of geophysical exploration, and discloses a transient electromagnetic vertical component detection data one-dimensional real-time accurate inversion method and system. Processing the established stratum model, training the constructed Seq2seq network by using a back propagation algorithm, and training transient electromagnetic optimal inversion models with different numbers of layers; performing background field extraction on all measurement points of the actually measured data, constructing simulated background field data, and extracting pure abnormal field ratio data; multiplying the obtained actually measured pure abnormal field ratio data by the obtained simulated background curve to reconstruct brand new total field data; the reconstructed brand-new total field data is corrected to be consistent with the time domain of the sample library; an inversion model of the corresponding layer number is selected, and the resistivity-thickness of the stratum is calculated in real time; and carrying out visual display on an inversion result. According to the invention, inversion precision is improved, and real-time inversion of transient electromagnetic detection data is realized.

The invention discloses a magnetic method data physical property inversion method and system based on a deep learning terrain disturbance layer, and relates to the technical field of geophysical exploration, and the method comprises the steps: building a magnetic anomaly data set, generating an underground three-dimensional magnetic anomaly model through a mixed hexahedron model and a terrain disturbance function, and obtaining corresponding magnetic anomaly data through forward modeling, each group of magnetic anomaly data corresponds to different terrain parameter combinations; constructing a deep learning inversion network model based on UNet; and training the deep learning inversion network model based on the magnetic anomaly data, taking the trained training set parameters as the weight of the deep learning inversion network, verifying the effect by using the verification set after the training is finished, and predicting the effect according to the test set. According to the method, a traditional same-dimensional random projection inversion method is combined with a deep learning network structure, and dynamic transformation of terrain parameters is realized by using a terrain disturbance layer, so that the network keeps high inversion precision and stability under different terrain fluctuation conditions.

The invention discloses a magnetic data boundary identification method and system based on a physical prior selection module, and relates to the technical field of geophysical exploration, and the method comprises the steps: building a magnetic anomaly data set through underground target magnetic anomaly data with different parameters; generating magnetic measurement data through a magnetic anomaly forward modeling calculation formula, and forming a magnetic measurement data set; constructing a boundary recognition network model based on UNet + +, and integrating the physical prior selection module to the boundary recognition network model; inputting the training set sample, the verification set sample and the test set sample into a physical prior selection module for operator transformation, and generating a corresponding transformation result graph; and calculating the structural similarity index of each transformation result graph and the corresponding sample label, and splicing the transformation result graph with the maximum structural similarity index and the corresponding sample according to the channel dimension to generate a corresponding multi-channel feature. According to the method, the boundary recognition network model is established and the physical prior selection module is added, so that the robustness of the boundary recognition network model to complex noise is improved.

The invention provides an electromagnetic detection system based on a sea-bottom crawler, belonging to the field of geophysical exploration technology, comprising: a survey vessel, a sea-bottom crawler, a transmitting antenna, a receiving node array, a control chip, and a power supply; the survey vessel is connected to the sea-bottom crawler through a traction rope, and the tail of the sea-bottom crawler is provided with a drag cable, on which the transmitting antenna and the receiving node array are mounted, and both the control chip and the power supply are configured in the integrated electronic cabin of the sea-bottom crawler; the power supply provides electrical energy to the sea-bottom crawler, transmitting antenna, receiving node array, and control chip, and the control chip is electrically connected to the transmitting antenna, the receiving node array, and the power system of the sea-bottom crawler; the control chip is configured to have an electromagnetic detection interference compensation module for performing interference elimination and compensation on reflected waves received by the receiving node array. It solves the technical problem of insufficient detection accuracy in existing technologies.

The invention belongs to the technical field of geophysical exploration transient electromagnetic detection, particularly relates to an ultra-wide coal face roof electrical tomography system and method, and is suitable for high-precision detection of a hidden geological structure of a working face roof with the width exceeding 300 meters and the depth within 100 meters in an underground coal mine. A transient electromagnetic perspective detection technology is adopted, and full-coverage imaging of an electrical structure of a working face roof is realized through alternate arrangement of transmitting-receiving roadways and dynamic data fusion; a time-space mapping relation is established in combination with a smoke ring effect diffusion model, and omnibearing imaging of the top plate is achieved; aiming at the refined detection of the hidden geologic structure of the top plate of the ultra-wide coal face (the width is greater than or equal to 300 meters), bidirectional detection and grid subdivision are adopted, and a single-side detection blind area is eliminated through roadway transposition of a transmitting end and a receiving end, so that grid full-coverage imaging in a detection range is realized.

The invention belongs to the technical field of oil and gas geophysical exploration, and discloses a horizontal well constrained seismic inversion method and system, and the method comprises the steps: intercepting a logging curve of a horizontal section; channel spacing resampling is carried out on the intercepted horizontal section logging curve; numbering sampling points of the resampled logging curve, and constructing a horizontal section data set; constructing a target inversion function based on the horizontal segment data set; and substituting the post-stack seismic data set into the target inversion function, and performing inversion to obtain a wave impedance prediction value corresponding to each channel of seismic data. According to the inversion method, the characteristic that the horizontal well crosses a seismic channel is considered, a horizontal well transverse constraint multi-channel target inversion equation is constructed, the horizontal well transverse change constraint seismic transverse inversion is utilized, the horizontal well constraint seismic inversion method and device are researched and developed, a high-precision and high-resolution wave impedance inversion result is obtained, and the method and the device are suitable for large-scale popularization and application. And powerful technical support is provided for comprehensive evaluation of oil and gas fields and well location deployment.