404 results about "Geophysical prospecting" patented technology

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 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 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 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 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 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 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 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.

The invention relates to the technical field of geophysical exploration, in particular to a semi-aviation transient electromagnetic detection system based on cooperation of a robot dog and an unmanned aerial vehicle, and the system consists of a robot dog platform, an unmanned aerial vehicle platform and a ground control station. The robot dog platform comprises a high-power transient electromagnetic transmitter, a line source laying module, a voice warning module and a mobile positioning module, and can automatically lay a line source and inject pulse current to the ground; the unmanned aerial vehicle platform comprises a visual field auxiliary module, a flight driving module and a receiving coil, and the coil can be dragged according to a preset route to collect electromagnetic data; the ground control station is used for job scheduling and data processing. Wiring-transmitting-receiving integrated collaborative operation is realized through the robot dog and the unmanned aerial vehicle, and the robot is suitable for detection of a complex mountain environment.

The present application is suitable for oil and gas geophysical exploration field, and provides a shale solid skeleton and organic matter elastic parameter synchronous prediction method, the method comprises the following steps: constructing a petrophysical model representing the elastic modulus of shale reservoir solid skeleton and the elastic modulus of organic matter; developing an inversion method in the well based on the petrophysical model; combining the petrophysical model and the scattering function theory, establishing a reflection coefficient formula linearly characterized by the elastic modulus of shale solid skeleton, the elastic modulus of organic matter and the density parameter; combining the reflection coefficient formula and the Bayesian linear inversion theory, developing a seismic petrophysical inversion method; applying synthetic seismic data, testing and verifying the effectiveness of the seismic petrophysical inversion method constructed in step E; then applied to actual seismic data, predicting the elastic modulus of shale gas reservoir solid skeleton and organic matter in the study area, providing an effective method for the brittleness evaluation of shale gas reservoir engineering sweet spot and the organic matter enrichment prediction of geological sweet spot.

The invention discloses a mine sewage transportation channel multi-parameter collaborative inversion method and system based on dynamic step length adjustment and a storage medium, and the method comprises the steps: collecting geophysical prospecting data reflecting the multi-physical property characteristics of an underground medium in a detection region of a hidden sewage transportation channel of an abandoned mine, and constructing a standardized multi-parameter characteristic data set through position matching; and building a multi-parameter joint inversion framework, establishing a comprehensive objective function fusing data fitting precision, parameter collaborative constraint and numerical stability, and introducing cross gradient constraint to realize physical property parameter model space structure association. An improved gradient descent method is adopted for iterative solution, a first-order iteration information and second-order function feature double-factor coupled dynamic step length adjusting mechanism is constructed, step length is regulated and controlled in a staged mode, invalid abnormal data are removed in combination with clustering analysis, iteration is conducted till convergence conditions are met, and the iteration effect is optimized in a staged mode. And finally, a multi-parameter fusion inversion model fitting actual geological features is obtained. And technical support is provided for detection of the hidden sewage transportation channel of the abandoned mine.

The invention discloses a rock and soil medium parameter testing and reinforcing method which comprises the following steps: step 1, arranging a plurality of in-situ testing holes and object detection lines on a side slope, a foundation or a filling site, and performing in-situ tests and geophysical prospecting tests, including in-situ drilling shear tests, penetration tests and pore pressure observation, the mechanical property, the permeability characteristic and the pore water pressure parameter of the soil layer are obtained; 2, according to the obtained soil layer parameters, the needed initial grouting pressure, flow and slurry concentration are calculated; 3, grouting equipment is used for injecting grout into the soil layer, and the deformation amount, the pressure change and the permeability change of the soil layer are monitored in the grouting process; 4, according to data monitored in real time, the grouting pressure and flow are adjusted so as to ensure the grouting uniformity and the reinforcing effect, compared with a traditional empirical grouting method, the method has the advantages that the reinforcing uniformity and the anti-seepage effect can be remarkably improved, energy consumption and risks are reduced, and good universality and engineering application value are achieved.

The invention provides a geophysical exploration data query method and system based on big data, and belongs to the technical field of exploration data management.The method comprises the steps that firstly, a logic association chain is constructed based on task and application scene association features of exploration data; receiving a user query request and analyzing to generate a demand analysis text containing dominant and implicit demand elements; positioning an initial data unit according to the dominant demand elements; taking the initial data unit as an initial expansion associated data branch; and screening branch data units based on the implicit demand elements to form a target set, and outputting a query result containing the target set and associated branches, thereby improving the accuracy and comprehensiveness of geophysical exploration data query.

The invention discloses a rapid forward modeling method for a gravity field of a rectangular coordinate system based on an isoparametric transformation global discrete grid, and belongs to the technical field of geophysical exploration. According to the method, a measuring network composed of dggrid grids is manufactured to cover the whole measuring area range by selecting the measuring network forming form and the side length, the exploration depth is selected as D, the dggrid grids extend to the ground by an n < z + 1 > layer to form dggrid units of an n < z > layer, and the corresponding thickness of the dggrid units is D / n < z >. And calculating the abnormal response of all the dggrid units at each observation point by utilizing isoparametric transformation based on a dggrid unit interpolation type function, an integral point and an integral weight coefficient obtained by a hexagonal prism integral formula. Compared with a square grid, the dggrid grid has excellent angular resolution, the discrete distance measurement of the dggrid grid is better close to the Cartesian distance, and the dggrid grid also has the advantage of displaying uniform and clear adjacency. Compared with conventional direct calculation, the rectangular coordinate system gravitational field forward modeling based on the isoparametric transformation global discrete grid has extremely high acceleration potential.

The invention relates to the technical field of data processing, discloses an earth and rockfill dam leakage positioning method based on joint inversion and data fusion, and aims to solve the problems of limitation and non-uniqueness of an existing single geophysical prospecting method in leakage hidden danger positioning. Converting the first apparent resistivity into a first apparent resistivity; second apparent resistivity distribution of the earth-rock dam is obtained through a high-density electrical method; acquiring electromagnetic wave velocity distribution by adopting a ground penetrating radar method, and converting the electromagnetic wave velocity distribution into third apparent resistivity; performing data standardization processing on the apparent resistivity to obtain standardized apparent resistivity data; performing dimension reduction fusion on the standardized apparent resistivity data corresponding to each apparent resistivity by adopting a principal component analysis method to obtain simulated apparent resistivity distribution; and determining the position of the leakage hidden danger channel in the earth-rock dam based on the pseudo-apparent resistivity distribution. The method improves objectivity, accuracy and reliability of leakage positioning, and is particularly suitable for danger removal and reinforcement of earth and rockfill dams.

The invention discloses a tunnel plateau complex geology accurate exploration method based on ultra-deep horizontal drilling, which comprises the following steps: step (1) horizontal drilling layout: selecting a construction site on the ground of a to-be-tunneled tunnel, and planning a horizontal drilling track along a tunnel line; (2) horizontal drilling and multi-dimensional geological exploration are constructed, specifically, according to the planned horizontal drilling track, a petroleum drilling machine is used for constructing horizontal drilling; logging operation is carried out in the horizontal drilling construction process, and comprehensive logging and transient electromagnetic detection are carried out after horizontal drilling construction is completed; and step (3), integration and analysis of geological exploration data information: integrating and analyzing the data information collected by multi-dimensional geological exploration, determining geological conditions along the tunnel line, and identifying geological abnormal sections. According to the invention, the problems of discontinuous exploration and poor accuracy of traditional vertical drilling and geophysical prospecting means can be solved, and high-precision and continuous exploration of geological conditions near the tunnel line is realized.

The invention discloses an underground geophysical prospecting sampling data quality monitoring method and system, and relates to the field of underground geophysical prospecting, and the method comprises the steps: collecting underground geophysical prospecting sampling data in real time; extracting time sequence characteristics of the sampling data; based on a traditional geophysical prospecting data quality evaluation rule, carrying out preliminary screening and identification on the extracted time sequence features, and combining a preset static threshold value to judge whether the data is suspected abnormal data or not; and inputting the suspected abnormal data into a deep learning time sequence anomaly detection model, and determining abnormal data by comparing an output result of the deep learning time sequence anomaly detection model with a dynamic threshold value. According to the invention, full coverage and real-time monitoring of underground geophysical prospecting sampling data are realized by using a multi-channel real-time acquisition and full-amount intelligent monitoring process, so that the problems of incomplete coverage and low efficiency of traditional manual sampling inspection are thoroughly solved, the labor intensity of workers is reduced, and the working efficiency is improved. The monitoring efficiency can be improved; and no abnormal omission of massive sampling data is ensured.

The invention discloses a tunnel shield interval boulder prediction method, medium and equipment, and the method comprises the steps: S1, obtaining the high-density electrical method apparent resistivity data of a detection region, and carrying out the inversion to obtain an apparent resistivity two-dimensional profile; s2, integrating the two-dimensional profile into a three-dimensional space, and constructing a continuous three-dimensional resistivity data volume; s3, extracting a threshold value abnormal region according to a preset threshold value A, and determining a boulder suspicious region A; s4, background signal propagation characteristics of the boulder-free area are measured through ultrasonic waves, a threshold value B is set, and if the background signal propagation characteristics exceed the threshold value B in the actual measurement process, the boulder-free area is marked as a boulder suspicious area B; and S5, obtaining an intersection of the abnormal coordinates of the boulder suspicious area A and the boulder suspicious area B, generating a closed three-dimensional boulder suspicious area, and outputting a result in a three-dimensional visualization manner. According to the method, the problems of high false anomaly rate, insufficient spatial information, strong subjective dependence and the like of a traditional single geophysical prospecting method are systematically solved, and the accuracy, the reliability and the engineering applicability of boulder detection are remarkably improved.

The invention discloses a tunnel unfavorable geologic body catastrophe identification method based on an alteration geological evolution sequence, and relates to the technical field of tunnel disaster prevention and reduction, and the method comprises the steps: carrying out the comprehensive advanced geological forecast of an unexcavated section of an excavated tunnel where an unfavorable alteration geologic body is found until a geophysical prospecting abnormal region is found; recording measuring points are arranged in the tunneling direction of the side wall of the excavated section of the tunnel, the three-dimensional coordinates of the measuring points and the tunnel mileage are positioned, and recording data are recorded; carrying out structural plane plotting, rock strength test, underground water state measurement and mineralogy test at the catalog measuring point to obtain in-situ test data; enabling the catalog data to correspond to the in-situ test data according to the tunnel mileage, extracting an undesirable alteration quantitative index, and drawing an alteration evolution sequence diagram; and constructing a bad alteration identification criterion, and if the identification criterion is met, performing trend extrapolation on the bad alteration quantitative index, and constructing a catastrophe evaluation system. According to the method, the engineering attributes and catastrophe of the poor alteration geologic body in front of the tunnel face can be effectively identified.

The application discloses a land geophysical exploration method, an electronic device and a readable storage medium, and belongs to the technical field of land geophysical exploration. The land geophysical exploration method comprises the following steps: detecting a first seismic wave generated by vibration at a preset position of the underground or the ground and transmitted to the ground; detecting a second seismic wave transmitted by the vibration to the air above the ground; calculating a ground parameter in a set range of the preset position according to the first seismic wave and the second seismic wave; and calculating an underground velocity model and a density model according to the ground parameter. The second seismic wave transmitted to the air from the ground is detected by utilizing the characteristics that the sound speed and the density of the air are consistent under the same meteorological condition, so that the subsequent inversion algorithm is more accurate, and the underground velocity model and the density model are more accurate.

The application discloses a kind of geotechnical medium parameter test and reinforcement method, contain following steps, step 1: multiple in-situ test holes and geophysical prospecting test lines are laid in slope, foundation or filling site, in-situ test and geophysical prospecting test are carried out, including in-situ borehole shear test, permeability test and pore pressure observation, to obtain the mechanical properties of soil layer, permeability and pore water pressure parameter;Step 2: according to the obtained soil layer parameter, the initial pressure, flow and slurry concentration required for grouting are calculated;Step 3: using grouting equipment, slurry is injected into soil layer, and the deformation of soil layer, pressure change and permeability change are monitored during grouting process;Step 4: according to the real-time monitoring data, adjust the grouting pressure and flow, to ensure the uniformity of grouting and reinforcement effect, compared with traditional empirical grouting method, the application can significantly improve the uniformity of reinforcement and anti-seepage effect, reduce energy consumption and risk, with good universality and engineering application value.

The invention provides a dynamic monitoring system and method for a submarine optical cable array reservoir, which is applied to the technical field of marine geophysical prospecting, and comprises a wet-end subsystem positioned underwater and a dry-end subsystem positioned on a base bank, the dry end subsystem comprises a light source module used for generating an optical signal; the modulation transmitting module is used for modulating the optical signal to obtain modulated pulse light; the underwater wet end subsystem comprises an optical cable transmission module used for transmitting modulation pulse light; the optical fiber four-component node module is used for dynamically and continuously monitoring the reservoir for a long time, and modulating the acquired sound pressure signal and the triaxial vibration signal onto the modulated pulse light in response to the received modulated pulse light to form a return light signal; the dry end subsystem further comprises a modulation-demodulation module used for receiving the return optical signal and demodulating the return optical signal to obtain four-component monitoring data. According to the invention, sound pressure and three-axis vibration response can be integrated on the same node, and passive four-component synchronous acquisition is realized.

This invention relates to the field of geophysical exploration and oil and gas geological analysis technology, and discloses a method for predicting fractured reservoirs in carbonate buried hills based on geological guidance and multi-scale fusion. The method includes: constructing a three-dimensional geological guidance constraint body using paleogeography and fault systems as geological priors; characterizing the fracture response mechanism using Gabor wavelet frequency division and structural tensor; constructing sensitive attributes and predicting the fracture body using a multi-branch convolutional neural network that fuses multi-source seismic attributes; and calculating the fracture complexity index based on the predicted fracture body to classify and zone the buried hill fractures. This invention introduces geological guidance constraints to improve the geological consistency of the prediction results; utilizes multi-scale Gabor frequency division and structural tensor analysis to achieve multi-scale fracture characterization; enhances model interpretability and prediction accuracy by fusing multi-source attributes through a multi-branch convolutional neural network; and achieves quantitative reservoir classification through the fracture complexity index, effectively guiding well location deployment and drilling decisions.

This invention belongs to the field of geophysical exploration technology and discloses a method for identifying structural ridges. The method includes selecting a target layer structural map, setting gridding parameters to grid the target layer structural map, and smoothing it once according to the gridding parameters to obtain structural map A; setting gridding parameters to grid structural map A, and smoothing it three times according to the gridding parameters to obtain structural map B; setting gridding parameters to grid structural map B, and smoothing it once according to the gridding parameters to obtain structural map C; subtracting structural map C from structural map A to obtain the remaining structures after removing structural trends; assigning a value of 0 to areas where the remaining structures have negative values ​​to obtain a structural ridge distribution map. This invention is simple and obtains the distribution of structural ridges, reflecting the distribution of dominant hydrocarbon migration channels and the distribution of micro-amplitude structures, providing important reference for the prediction of remaining hydrocarbons. This invention is applicable to the identification of structural ridges.

The present application relates to oil and gas geophysical exploration technology field, specifically disclose a kind of tight sandstone gas reservoir fluid mobility gradient attribute prediction method and system, the method includes constructing fluid mobility term's reflection coefficient expression, and deduce the formula for calculating fluid mobility using dispersion attribute, construct and frequency and seismic wave incidence angle related fluid mobility gradient attribute;Establish double-pore petrophysical model, generate synthetic seismogram, apply frequency-variable AVO inversion to the synthetic seismogram, extract bulk modulus dispersion attribute and shear modulus dispersion attribute;Fluid mobility changing with frequency and incidence angle is calculated, based on gradient attribute calculation formula and fluid mobility, fluid mobility gradient attribute is calculated.The present application makes full use of the response of the seismic wave dispersion and attenuation caused by permeability and gas saturation, constructs the seismic gradient attribute and calculation method of fluid mobility, realizes the high-precision prediction of fluid mobility by applying the elastic and dispersion petrophysical information of seismic signal.