783 results about "Transverse wave" patented technology

The invention provides a deep coalbed methane reservoir double-pore structure parameter prediction method and device, relates to the technical field of coalbed methane reservoir development, and solves the technical problem of low precision of a prediction result of pores of a deep coalbed methane reservoir. The method comprises the steps that based on the initial organic matter content, the clay content and the brittle mineral content, an equivalent medium theoretical model is used for establishing a coal bed gas reservoir double-pore coal rock physical model; calculating matrix porosity, fracture porosity and fracture aspect ratio according to logging observation longitudinal wave and transverse wave velocities in the logging data, and taking well-side matrix porosity, fracture porosity and fracture aspect ratio as pore parameter prior information of the coal bed gas reservoir double-pore coal rock physical model; and based on the specified three-dimensional seismic horizon data and the pore parameter prior information, pre-stack seismic inversion is carried out by using a pre-stack Bayesian inversion method through the coal bed gas reservoir double-pore coal rock physical model, and a coal bed gas reservoir double-pore reservoir prediction result is obtained.

The invention provides a welded joint ultrasonic phased array automatic detection device and method, and the method comprises the steps: selecting a longitudinal wave mode or a transverse wave mode on an interface of a control computer, inputting sample parameters, calculating acoustic beam excitation delay, and setting the acoustic beam excitation delay in an ultrasonic transmitting / receiving module; a mechanical scanning mechanism is driven according to the set parameters, so that a phased array probe moves on the surface of the welding joint according to a preset path; ultrasonic waves are sent to the welding joint according to the acoustic beam excitation delay, echo signals are received, the echo signals are processed to obtain scanning signals, and the scanning signals are uploaded to the control computer; processing the scanning signal to generate a scanning image, segmenting and identifying the scanning image, and extracting incomplete fusion and incomplete penetration defect areas in the scanning image; and performing three-dimensional visual imaging on the defect area and analyzing a characteristic curve extracted from the primary echo amplitude of the echo signal to obtain three-dimensional data of the defect area and storing the three-dimensional data.

The invention relates to the technical field of oil exploration, and discloses a rock mechanical parameter logging intelligent evaluation method considering continental facies shale fabric characteristics. The method comprises the following steps: 1, dividing shale lithofacies, identifying and determining the bedding development thickness of a sample through an optical microscope, determining a granularity experiment of the sample through granularity analysis, and forming mineral composition and bedding factor lithofacies division; 2, constructing a typical logging facies based on a rock electricity response relationship, and dividing the imaging logging facies of the research area according to natural gamma curves of conventional logging and imaging logging, core deposition structure characteristics and imaging logging image characteristics; 3, testing the longitudinal and transverse wave velocities and the porosity of different shale lithofacies, and calculating the dynamic elastic modulus and the Poisson's ratio. Through fine division and description, the method for accurately evaluating the bedding development condition, the particle size characteristics and the mineral components of the shale sample is provided, the testing time is short, the cost is low, and accurate evaluation of shale can be achieved.

The invention discloses an orthotropic rock physical modeling method. The method comprises the following steps: S1, obtaining tight reservoir parameters; s2, estimating the elastic modulus of the mixed minerals; s3, enabling the mixed mineral to be equivalent to a VTI background rock matrix caused by a thin layer; s4, matrix pores are added into a VTI background rock matrix; s5, embedding the vertical crack into the VTI background'dry 'rock skeleton to obtain an OA medium'dry' rock skeleton; s6, calculating the bulk modulus and saturated rock density of the mixed fluid; s7, adding the mixed fluid into the OA medium'dry 'rock skeleton to obtain OA medium saturated rock; s8, calculating longitudinal and transverse wave velocities and anisotropy parameters of OA medium saturated rocks; and S9, calculating OA medium saturated rock. According to the method, the tight reservoir with the orthotropic characteristic can be simulated, the Thomsen parameter and the fracture weakness parameter of the tight reservoir can be obtained, and data support is provided for fracture evaluation, anisotropic parameter inversion, permeability prediction and the like of the tight reservoir.

The invention provides an airfield pavement detection method based on an earthquake background noise imaging technology, and relates to the technical field of airfield pavement detection. Comprising the following steps: acquiring seismic background noise data of an airport pavement to be measured; preprocessing the seismic background noise data to obtain preprocessed noise data; carrying out cross-correlation calculation on the preprocessed noise data and carrying out empirical Green function extraction; according to the empirical Green function, a surface wave group velocity frequency dispersion curve is extracted by adopting spatial autocorrelation and multiple filtering methods; inverting shear wave velocity distribution of each layer of the pavement based on the surface wave group velocity dispersion curve, and constructing a three-dimensional velocity model; determining a shear wave velocity distribution diagram according to the three-dimensional velocity model; and determining a detection result of the airfield pavement to be detected according to the transverse wave velocity distribution diagram. According to the invention, the problems of low detection precision and poor real-time performance of a common detection technology in the prior art are solved.

The invention provides a multiple longitudinal and transverse wave joint detection method based on a seabed crawler, which belongs to the technical field of geophysical exploration, and constructs an original longitudinal and transverse wave signal matrix by transmitting multi-frequency longitudinal and transverse wave signals and receiving stratum reflection signals. Fourier transform is utilized to extract frequency characteristics, physical analysis is carried out in combination with a wave equation, and a longitudinal and transverse wave interference matrix is constructed and weighted fusion is carried out. And constructing an error compensation matrix according to the crawl device attitude data, and performing interference compensation on the joint interference matrix. And performing time-frequency analysis through wavelet transform, extracting specific time-frequency features, inputting the specific time-frequency features into a pre-trained stratum classification prediction model, realizing anti-interference prediction on the type and thickness of the seabed stratum structure, finally drawing a seabed three-dimensional geological profile map according to a prediction result, and marking a key geological structure and a resource distribution region. The technical problem that accurate recognition and resource distribution positioning of the seabed stratum structure are affected due to much external interference in the seabed geological exploration process is solved.

The invention relates to the technical field of cast-in-place pile detection, and discloses a cast-in-place pile integrity detection system based on a multi-mode ultrasonic array, and the system comprises a deformable multi-mode ultrasonic probe which is used for adaptively adjusting the posture through an intelligent material driver; the intelligent coupling injection module is used for automatically cleaning the inner wall of an internal channel of the cast-in-place pile; the multi-source data processing module is used for receiving the original ultrasonic waveform data and the real-time position information of the ultrasonic probe; the deep learning recognition module is used for generating a recognition result including defect categories and preliminary features; the defect positioning and evaluating module is used for constructing a defect model comprising defect space coordinates, geometric dimensions and severity parameters; and the diagnosis decision module is used for providing targeted repair suggestions. The ultrasonic signals are transmitted and received through the integrated longitudinal wave transducer, the transverse wave transducer and the Rayleigh wave transducer, the internal structure information of the pile body is obtained, in this way, the ultrasonic beam coverage range is expanded, and the detection blind area of the area between the sounding pipes in a traditional method is effectively made up.

The invention provides a digital rock core equivalent characteristic parameter prediction method based on voxel and point cloud combination. The method specifically comprises the following steps: calculating equivalent characteristic parameters of a digital rock core by using a finite element method and a lattice Boltzmann method; and converting the pore and matrix contact surface into a point cloud data set. And calculating point cloud feature parameters. A point cloud information constrained multi-gating multi-expert hybrid prediction network is constructed, and a same variance uncertainty loss function is constructed. And training the prediction network by taking the bulk modulus, the shear modulus, the longitudinal wave velocity, the transverse wave velocity, the porosity, the density and the permeability as prediction targets until the loss function is converged. According to the technical scheme, the problems that crosstalk is generated between tasks and the prediction precision is low when digital core equivalent characteristics are predicted through multiple parameters in the prior art are solved.

The invention relates to the technical field of earthquake prediction, in particular to a crustal stress azimuth earthquake prediction method based on a transverse wave speed change rate, which comprises the following steps: calculating a speed value of a transverse wave and a propagation distance, extracting a difference value to generate a change rate set, calculating an offset rate, screening a continuous overrun section, identifying a disturbance path section, and performing interpolation restoration to generate a purification sequence. Extracting forward and reverse propagation trends and counting direction identifiers, and generating a crustal stress main stress direction map; according to the method, a change rate set is generated through a sliding window segmentation speed sequence, data continuity is enhanced, local features are reserved, a sudden change area is screened and accurately positioned in combination with a continuous offset rate, multi-path lithology difference identification and disturbance repair are carried out, non-structural interference is eliminated, and forward and reverse path cross validation is carried out to screen a direction consistent section, so that the discrimination robustness is improved; the velocity direction is dynamically associated with the structure trend, synchronous analysis of the stress field and fault activity is realized, multi-stage processing is combined with dynamic threshold and direction verification, and the derivation precision and timeliness are improved.

The invention relates to the technical field of applied geophysics, in particular to a logging-while-drilling shear wave velocity processing method, device and equipment and a storage medium. The method comprises the following steps: dividing a parameter range and a step length, determining a stratum parameter combination, and taking the stratum parameter combination as a data set sample feature; constructing a frequency dispersion data set according to the obtained data set sample labels; performing data cleaning on the frequency dispersion data set, and correcting error samples in the data set; establishing a neural network, training a frequency dispersion data set, and verifying the feasibility of the model; an inversion objective function is established through a joint inversion method, the shear wave velocity is inversed by adopting a low frequency band, and the mud velocity is inversed by adopting a high frequency band; an optimization method is added, so that the number of forward calculation times in inversion is reduced, and the inversion efficiency is improved; and replacing the current depth point with the next depth point, and returning to execute the optimization method until the transverse wave velocity processing of the full depth section is completed. According to the method, the rapid frequency dispersion correction under the well logging while drilling is realized, the calculation efficiency is improved, and the calculation cost is saved.

The invention discloses a bolt pre-tightening force testing method based on an electromagnetic ultrasonic pre-tightening force measuring system, and the method comprises the steps: collecting the waveform data of transverse and longitudinal waves generated by an electromagnetic ultrasonic probe, and only processing the current frame echo data and historical accumulated data each time through a data averaging algorithm. The storage space only needs to store the historical accumulated data received by the electromagnetic ultrasonic probe once, so that the processing speed and the signal-to-noise ratio of the data are improved; and automatically identifying and calculating the wave peak sound time enveloped by the transverse and longitudinal wave echoes of the bolt through a peak value algorithm, fitting to obtain a calibration curve corresponding to the bolt of the model specification through the ratio of the transverse and longitudinal wave sound time to the bolt pre-tightening force corresponding to the time period, and measuring the pre-tightening force of other bolts of the same model specification by using the calibration curve. The method is easy and convenient to operate, effective transverse waves and longitudinal waves can be excited at the same time, and measurement precision and accuracy are high.

The invention discloses a material high-temperature longitudinal wave and transverse wave sound velocity measurement device and method based on laser ultrasound, and the method comprises the steps: controlling an Nd: Yag pulse laser to emit laser, exciting sound waves in different modes through a thermal elastic / thermal etching effect under the protection of inert gas, and transmitting the sound waves to the upper and lower surfaces through internal transmission and reciprocating reflection of a measured material; an incident laser point and a laser detection point are adjusted to be on the same axis, and the double-wave mixing interferometer is moved to measure received sound waves of different modes for multiple times in a linear scanning mode; laser ultrasonic longitudinal wave and transverse wave mode decomposition is realized through variational mode decomposition; and obtaining two groups of array data by using a cross-correlation algorithm, and performing linear fitting calculation on a result to obtain parameters of the to-be-tested material. Separation and signal post-processing of different modes of sound waves excited by laser ultrasound are achieved, and the method is suitable for simultaneous measurement of longitudinal wave and transverse wave sound velocities; the influence of thermal expansion of the material at high temperature can be neglected, and the measurement uncertainty introduced by the influence factor is reduced.

An on-line monitoring method and system for pre-tightening stress of a blade root bolt of a wind turbine generator. The method comprising: step S1, on the basis of a material type of a measured bolt, calculating bolt parameters in a zero-load state; and step S2, collecting related data of the measured bolt, and calculating to obtain an axial stress of the bolt to complete monitoring. The transit time of ultrasonic longitudinal and transverse waves in the bolt is measured by using the acoustic elasticity theory, and the axial stress of the bolt is obtained by performing ratio calculation on the basis of the transit time of longitudinal and transverse waves, so that the pre-tightening force of the blade root bolt is monitored in real time. The pre-tightening force of the fastened bolt of the blade root is monitored by using a double-wave method, which reduces the complexity of measurement, and facilitates the large-scale application of engineering projects.

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

The invention belongs to the field of polar acoustic measurement, and relates to a method for estimating the sound velocity and thickness of an ice layer by using airwaves and ice layer bending waves, which comprises the following steps of: acquiring broadband pulse sound signals by using a sensor fixed on an ice surface; recording the distance between the detonating device and the ice surface sensor; performing time-frequency analysis on the broadband pulse signal acquired by the ice surface sensor; obtaining a time-frequency spectrum of the signal through time-frequency analysis, calculating the propagation velocity of the airwave, converting the time-frequency spectrum into a group velocity spectrum, and extracting a group velocity dispersion curve of the bending wave; initializing the longitudinal wave velocity, the transverse wave velocity, the ice layer thickness and the seawater sound velocity of the ice layer; calculating an expected group velocity curve according to the sound propagation model, and constructing a cost function; and optimizing the cost function by adopting a particle swarm algorithm, and outputting a final parameter estimation value. The method can be realized only by using a single sensor, and the synchronization of transmitting equipment and receiving equipment is not required; the sound velocity and thickness of the ice layer can be inverted by using the relationship between the group velocity and the acoustic parameters.

The invention discloses a multi-wave chromatography and reflection combined detection method and device for a thin-covering-layer urban active fault and a medium. The method comprises the steps that longitudinal wave seismic data and transverse wave seismic data are collected; recording vertical component data based on the longitudinal wave seismic data for first arrival travel time pickup and tomography inversion to obtain a longitudinal wave velocity structure model Vp; extracting Rayleigh surface wave frequency dispersion through the vertical component data and carrying out multichannel surface wave analysis inversion to obtain a transverse wave velocity structure model Vs; calculating a longitudinal and transverse wave velocity ratio parameter structure model Vp / Vs, and calculating to obtain a Poisson's ratio parameter structure model v; obtaining a longitudinal wave (P wave) reflection profile and a transverse wave (S wave) reflection profile; identifying and summarizing into an interpretation fracture set Fc, and recording key elements; and by taking the interpretation fracture set Fc as a structural skeleton, completing unified registration and superposition display on Vp, Vs, Vp / Vs and v, a longitudinal wave reflection profile and a transverse wave reflection profile, and outputting a shallow underground structure comprehensive interpretation map of the thin covering layer region.

The invention provides a geophysical recognition method for medium-deep under-compacted low-speed mudstone, which comprises the following steps of: obtaining representative longitudinal wave velocity, transverse wave velocity and density of low-speed mudstone and gas-bearing sandstone in logging information through statistical analysis of data, and designing a theoretical model of a superposition relationship between the low-speed mudstone and the gas-bearing sandstone in combination with geological information, so as to obtain the geophysical recognition result of the low-speed mudstone and the gas-bearing sandstone. Performing convolution forward modeling and pre-stack forward modeling on the model, respectively calculating to obtain post-stack seismic attributes and pre-stack seismic attributes of the model, performing sensitive attribute optimization on the attributes, taking the obtained sensitive attributes as learning samples, and identifying the superposition relationship by using probability self-organizing neural network clustering. According to the method, the pre-stack attributes are added into sensitive attribute optimization, so that the fuzzy self-organizing neural network can more accurately recognize the gas-bearing sandstone and low-speed mudstone stacking relation, the low-speed mudstone and the gas-bearing sandstone can be effectively distinguished, and support is provided for subsequent effective reservoir prediction.

The invention discloses an ultrasonic dual-wave reliability measurement method for a bolt stress. A first ultrasonic dual-wave transducer is configured to transmit and receive an ultrasonic transverse wave or an ultrasonic longitudinal wave, a second ultrasonic dual-wave transducer is configured to receive the ultrasonic transverse wave or the ultrasonic longitudinal wave, and the transverse wave or longitudinal wave generated by the first ultrasonic dual-wave transducer is propagated in a measured bolt. If a difference between TOF for which the first ultrasonic dual-wave transducer receives the echo signal and double of TOF for which the second ultrasonic dual-wave transducer receives the echo signal in a same mode is not greater than a quarter of one transmission period T, the measured TOF satisfies verification requirements. Reliability of time-of-flight data of the ultrasonic wave can be verified, and various measurement errors can be prevented.

The invention discloses a thin reservoir prediction method based on pre-stack frequency extension processing, and the technical scheme is that on the basis of improving the resolution to process seismic data, reservoir rock physical analysis is carried out through actually measured transverse wave data, a rock physical model is constructed, thin reservoir identification sensitive parameters are determined, and a bridge between logging and earthquake is built; for seismic data, pre-stack seismic certainty inversion of sand group thickness resolution capability and pre-stack statistical high-resolution inversion of single sand body thickness are respectively carried out, a sensitive parameter data body is obtained through calculation, and according to a rock physical quantity plate, the spatial description precision of the thin sand body is effectively improved. The method is high in operability and easy to apply, and has good application prospects for similar ultra-deep and ultra-thin layer sand bodies such as cretaceous systems and triassic systems of tahe oil fields in the Tarim Basin; and meanwhile, the method is also suitable for sweet spot identification and reservoir space fine description of ultra-deep and thin reservoirs of basins in the middle and western parts, and is of great significance for improving the drilling success rate, productivity construction and the like.

The invention provides a full-section detection method, device and equipment for reinforcing a steel rail welding seam and a storage medium, and relates to the technical field of nondestructive testing. The method comprises the following steps: respectively arranging a plurality of first phased array probes on rail head treads and rail bottom surfaces of a first steel rail and a second steel rail, and arranging a second phased array probe right above a welding seam; the detection method comprises the following steps: determining optimal parameters of a transducer based on the material of the steel rail, the size of the cross section of the steel rail and the sound pressure intensity at a preset focusing depth position; determining the optimal scanning angle range of the first phased array probe based on the propagation velocity of the ultrasonic longitudinal wave in the wedge block and the steel rail, the propagation velocity of the ultrasonic transverse wave in the steel rail and the Snell's law; and controlling the first phased array probe to carry out sector scanning imaging within the optimal scanning angle range, and controlling the second phased array probe to carry out zero-degree line scanning imaging, so as to detect the full section of the welding seam. According to the invention, the welding seam can be accurately detected without dismounting the clamping plate.

The present invention relates to a Rayleigh wave dispersion curve inversion method and system based on geological statistics, and belongs to the technical field of seismic shear wave velocity inversion. First, an inversion equation is constructed based on a dispersion equation, and iterative optimization is performed using the inversion equation to obtain the first seismic shear wave velocity structure of each station. Then, multiple second initial seismic shear wave velocity structures of each inter-station point to be estimated are determined based on the first seismic shear wave velocity structure and position of all stations, and the second Rayleigh wave dispersion curve is calculated using the dispersion equation. Finally, all the second Rayleigh wave dispersion curves corresponding to the inter-station point to be estimated are used as input, and the optimal second Rayleigh wave dispersion curve is determined using the second objective function to determine the second seismic shear wave velocity structure of each inter-station point to be estimated. The present invention can simultaneously obtain the seismic shear wave velocity structure of stations and stations, and can greatly improve the lateral resolution.

The invention relates to the technical field of unconventional shale oil and gas resource exploration, in particular to a shale shear wave velocity estimation method considering clay directional arrangement influence. According to the technical scheme, a shale compaction model is constructed, a shale directional arrangement background medium is formed, an orientation distribution function is used for simulating the elastic tensor of the background medium under different directional arrangement degrees, and the anisotropic speed of the background medium is calculated; calculating a longitudinal wave speed and a transverse wave speed in an equivalent isotropic background medium according to the anisotropic speed, and then calculating a bulk modulus and a shear modulus of the equivalent isotropic background medium; and adding clay-related pores and sand-related pores into an equivalent isotropic rock matrix by using an Xu-White model to obtain a bulk modulus and a shear modulus of dry shale, and finally simulating the shear wave velocity of the shale under the influence of directional arrangement of the clay. According to the invention, a new rock physical model is established to simulate the influence of clay directional arrangement, pore morphology, mineral and fluid properties on longitudinal and transverse wave velocities in shale.

The invention discloses an ultrasonic orthogonal scanning measurement method for mechanical properties of a fiber reinforced composite material. The method comprises the following steps: aiming at a composite material unidirectional plate to be detected, fixing receiving (transmitting) points on the surface of one side of a material, positioning the transmitting (receiving) points on the surface of the other side of the material, performing linear scanning along any two orthogonal directions, and recording transmission quasi longitudinal wave and quasi transverse wave time domain waveform signals which are acquired by combining each pair of transmitting and receiving points and are propagated along different paths; establishing an acoustic model for quantitatively describing the quantitative relationship between the ultrasonic trend and the independent elastic constant, thickness and fiber direction angle of the to-be-tested fiber reinforced resin matrix composite so as to simulate an ultrasonic data acquisition experiment and generate a corresponding simulated ultrasonic data set; and updating the independent elastic constant, the thickness and the fiber direction angle value of the composite material by taking the similarity degree between ultrasonic data sets obtained by experiments and simulation as a target function. According to the invention, multi-parameter high-precision in-situ nondestructive measurement of mechanical properties, thickness and fiber orientation of materials can be synchronously realized.

The invention relates to a buried hill reservoir permeability evaluation method and system based on Stoneley wave time difference intelligent prediction, processing equipment and a storage medium. The method comprises the following steps: preprocessing core physical property, conventional logging and electric imaging logging data in a target area; array acoustic logging data are processed, and longitudinal wave, transverse wave and stoneley wave time difference of each well in the target area is extracted; establishing an intelligent stoneley wave time difference prediction model, and predicting the stoneley wave time difference of the interval with poor stoneley wave data quality of each well; determining the effective fracture development position and the fracture width of each well; carrying out a crack plate model experiment, and calculating the total permeability of the stratum at the effective crack development position according to the effective crack development position and the crack width of each well; inverting the total permeability of the buried hill reservoir; on the basis of the plunger sample core permeability and the total stratum permeability calculated at the effective fracture development position, permeability inversion results of the effective fracture non-development position and the effective fracture development position of each well are calibrated, and the method can be widely applied to the field of oil and gas exploration and development.

The invention provides an azimuth transverse wave remote detection data processing method, system and device and a medium. The method comprises the steps that an instrument is adopted to collect novel four-component transverse wave data (xx, xy, yx and yy) of a target well section; under a coordinate system (x, y) of the instrument, synthesizing an XX reflected wave signal with an angle defined relative to the x-axis direction of the instrument by using the orthogonal dipole four-component reflected signal, and defining the XX reflected wave signal as an angle when the reflected wave signal reaches the maximum amplitude; obtaining two cross component signals xy and yx by using novel four-component shear wave data (xx, xy, yx and yy), performing sliding windowing on the cross component signals xy and yx, performing Fourier transform on the signals in the window to obtain phase spectrums, and comparing the phase spectrums of the two cross component signals to obtain an actual phase difference; according to a novel four-component data combination mode, changing the orientation of the reflector, theoretically calculating the theoretical phase difference between the two cross component signals xy and yx, and establishing a rule chart of the cross component signals along with the orientation change of the reflector outside the well based on the theoretical phase difference; and judging the real azimuth angle of the reflector according to the rule plate.

The utility model discloses an oil tank truck wave-proof plate structure which comprises a transverse wave-proof plate and a longitudinal wave-proof plate, the transverse wave-proof plate is provided with a second oil passing hole, the longitudinal wave-proof plate is provided with a first oil passing hole and an opening, a rotating shaft is connected in the opening in a left-right swinging mode, and a rubber pad is fixedly connected in the opening. Through holes are formed in the two sides of the transverse wave-proof plate, and the rotating shaft is rotationally connected with the through holes. By means of the structure, in the driving process, fluid is buffered, impact force is continuously reduced, compared with the prior art, the service life is longer, the stability of the interior of the tank body is guaranteed, and the driving safety is improved.

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 belongs to the technical field of seismic exploration, and particularly discloses an elastic wave vector seismic exploration data static correction method, which comprises the following steps: S1, establishing a longitudinal wave micro-logging surface velocity model; s2, establishing a three-component micro-logging shear wave surface velocity model; s3, performing low-frequency static correction on the longitudinal wave seismic data; s4, performing low-frequency static correction on the transverse wave seismic data; s5, performing low-frequency static correction on the converted wave seismic data; s6, calculating residual static correction values of shot points and detection points of the longitudinal wave field, the converted wave field and the transverse wave field; and S7, calculating total static correction values of shot points and detection points of the longitudinal wave field, the converted wave field and the transverse wave field. According to the method, the static correction problem of various wave field seismic data in elastic wave vector seismic exploration is effectively solved, and the calculation efficiency and the imaging precision are improved. The method is suitable for static correction of seismic exploration data.

The invention relates to the technical field of geological exploration, in particular to a deep water ultra-shallow natural gas reservoir rock physical shear wave velocity prediction method, which comprises the following steps: calculating the equivalent bulk modulus, shear modulus and density of a mixed matrix of various minerals according to the shale content; calculating the bulk modulus and the shear modulus of the skeleton; calculating the bulk modulus and the shear modulus of the saturated rock through the model, and calculating the density of the saturated rock through the density of the rock matrix; distributing longitudinal and transverse velocities in a suspension state and a bearing state, and calculating equivalent longitudinal and transverse wave velocities; taking the longitudinal wave velocity as a known condition, and constructing an inversion objective function by using the equivalent longitudinal wave velocity; comparing the actual longitudinal wave speed with the calculated longitudinal wave speed; and realizing nonlinear inversion of the shear wave velocity according to an algorithm, and obtaining the shear wave velocity of the work area to be inverted. According to the method, rock physical models in a particle suspension state and a bearing state are considered at the same time, and shear wave velocity prediction and direct inversion of the shear wave velocity of the deepwater ultra-shallow natural gas reservoir are realized.

According to the method, a deep learning network model and a seismic inversion result are introduced into three-dimensional pore pressure, elastic parameter data such as logging density, longitudinal and transverse wave velocity and the like and three-dimensional elastic attribute data obtained through seismic inversion are collected as a data set, and the network model is optimized and trained by using an optimization algorithm; the trained model is applied to a test area, a three-dimensional pore pressure prediction result is calculated and output, more comprehensive geologic feature attributes are provided by using multi-source data such as logging and earthquakes, deep features can be learned from the multi-source data, and pore pressure prediction can be better carried out.