217 results about "Logging while drilling" patented technology

A method for constructing a high fidelity logging while drilling (LWD) log that includes obtaining a temporal well depth log and a plurality of temporal LWD logs from a drilling operation. The method further includes obtaining a temporal record of operational drilling parameters from the drilling operation. The method further includes determining, using a first machine-learning model, a temporal history of the drilling operation and constructing, using the temporal well depth log and the plurality of temporal LWD logs, a plurality of temporal property logs at each depth in the plurality of depths. The method further includes processing the plurality of temporal property logs with, at least, a second machine-learning model to form a plurality of corrected temporal property logs and aggregating the plurality of corrected temporal property logs to form a plurality of high fidelity LWD logs.

The invention discloses a logging-while-drilling reservoir parameter dynamic prediction method based on double attention convolution LSTM, and the method comprises the steps: obtaining logging-while-drilling data and drilling data in real time, and carrying out the preprocessing of the data; establishing a DTW dynamic time window model based on a gradual transition strategy, and adaptively adjusting the length of an input sequence according to the stratum change speed; a double attention convolution LSTM model is combined with the DTW dynamic time window model to establish a feature-time double attention mechanism, and two dimensions of features and time are adaptively fused based on the convolution LSTM; setting a buffer area, storing data and controlling data quality; setting an online increment fine tuning strategy; and performing instance training, and performing multi-angle evaluation on the performance of the double attention convolution LSTM model by adopting multiple indexes. According to the scheme, the influence of features and time on the prediction accuracy is fully considered, and the prediction accuracy is improved.

The present invention relates to a computer implemented method, the main objective of which is to predict real-time LWD profiles in the intervals from the drill tip to the limit of the profile offsets. This becomes a methodology that serves as yet another input to improve assertiveness in decision-making during well drilling operations.

The invention discloses an intelligent while-drilling comprehensive fracturing dessert identification method, which comprises the following steps of enabling logging data of different small layers in a target block reservoir to correspond to a dessert comprehensive evaluation coefficient and production well gas production rate data, and establishing an intelligent dessert identification model training database; and a neural network model is established, part of data in the intelligent fractured dessert recognition model training basic database serves as a training set to be input into the neural network model for training, establishment of a deep learning model is completed, and the intelligent fractured dessert recognition model is formed. In the drilling construction process, logging-while-drilling data are fed back in real time, the logging-while-drilling data serve as input parameters and are uploaded to the intelligent fracturing dessert recognition model, and corresponding dessert comprehensive evaluation coefficients and production well gas production rate data are output in real time; and intelligent while-drilling comprehensive fracturing dessert identification is realized according to the output dessert comprehensive evaluation coefficient and the production well gas production rate data. According to the method, real-time sweet spot identification in the while-drilling process is comprehensively realized.

An integrated drilling system includes a rotary steerable control unit and an electromagnetic LWD control unit deployed in an external collar. The rotary steerable control unit is deployed below the electromagnetic LWD control unit and is configured to control a direction of drilling of the integrated drilling system. A near bit electromagnetic antenna is deployed in a recess on the collar circumferentially about the rotary steerable control unit. At least one electromagnetic transmitter and at least one electromagnetic receiver are deployed in corresponding recesses in the collar circumferentially about the electromagnetic LWD control unit with the at least one transmitter and at least one receiver configured to make electromagnetic logging measurements while drilling. An electrical jumper provides an electrical connection between the near bit electromagnetic antenna and the electromagnetic LWD control unit.

The invention discloses a while-drilling electromagnetic wave advanced detection sensitivity analysis method, and belongs to the field of oil-gas exploration and development. The method comprises the following steps: constructing a while-drilling electromagnetic wave advanced detection model, quantifying the influence of different measurement parameters on advanced detection signals, then analyzing the response characteristics of the advanced detection signals, extracting key sensitivity factors, and defining a single-parameter sensitivity function and a multi-parameter coupling sensitivity function; the sensitivity of advanced detection signals is qualitatively and quantitatively analyzed from the four angles of the distance to the interface, the formation resistivity, the interlayer and the stratigraphic dip angle, so that the while-drilling electromagnetic wave advanced detection range is optimized, and the adaptability in the well logging process is enhanced. And meanwhile, the advanced detection second-order sensitivity is approximately solved by adopting a central difference formula, influence factors suffered by advanced detection signals are analyzed from a numerical angle, the interaction of multi-parameter coupling is analyzed, and a scientific basis is provided for electromagnetic wave logging while drilling accurate inversion and instrument design.

The invention relates to the technical field of logging while drilling, and discloses a near-bit stratum detection method, system and device, electronic equipment and a medium, and the method comprises the steps: transmitting a seismic wave to a to-be-detected stratum in front of a drill bit through an underground vibroseis, and receiving a reflected wave signal of the to-be-detected stratum through a geophone; calculating the relative position of the stratum in front of the drill to the drill in real time according to the reflected wave signal; acquiring a first lithologic seismic wave characteristic parameter of the reflected wave signal and a second lithologic seismic wave characteristic parameter of a known typical stratum; matching the first lithologic characteristic wave characteristic parameter with the second lithologic seismic wave characteristic parameter, and determining the formation lithology and the geological structure of the formation to be detected; outputting the stratum information of the to-be-measured stratum including the distance data, the stratum lithology and the geological structure; the seismic waves are not affected by various complex geological environments, the stratum information of the stratum to be measured can be accurately obtained, the drilling risk is reduced, and the drilling efficiency and safety are improved.

The invention relates to the technical field of logging while drilling, and particularly provides a logging while drilling electromagnetic wave resistivity logging inversion method. The method comprises the following steps: constructing an XGBoost feature screening module, and optimizing a data set through the XGBoost feature screening module to obtain an optimized data set; according to the method, a BiLSTM-Transformer model is constructed, an optimized data set is input into the model, an inversion result is obtained, the inversion precision and the calculation efficiency are improved, and inversion of the target stratum resistivity, the adjacent layer surrounding rock resistivity and the boundary distance under the anisotropic stratum model is achieved.

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 provides a petroleum drilling geomechanical characteristic estimation method based on deep learning, and aims to solve the problems of high measurement cost and poor real-time performance of shear wave velocity Vs in traditional geomechanical analysis by fusing logging while drilling LWD data and real-time drilling engineering parameters. According to the method, a Transformer model is adopted to carry out depth correction on logging-while-drilling data, depth offset of a drill bit and a logging sensor is eliminated, and real-time drilling parameters such as torque T, bit pressure WOB and drilling speed ROP are combined and input into a multi-layer perceptron MLP network to predict the shear wave speed Vs. And further calculating key geomechanical parameters based on the predicted shear wave velocity Vs. In practical application, the method improves the shear wave velocity prediction accuracy to 97.2%, the mean absolute error MAE of the shear modulus is reduced from 0.186 to 0.059, and the bulk modulus is reduced from 0.189 to 0.040. The method can be used for outputting stratum elastic parameters, optimizing bit pressure, pre-warning well wall instability and adjusting a well track, well drilling safety and efficiency are improved, and meanwhile dependence on an expensive well logging technology is reduced.

Systems and methods include obtaining well log data and core sample data of a subsurface formation; generating, based on the well log data and the core sample data, an unconfined compressive strength log for the subsurface formation; using an unsupervised machine learning model to form rock type clusters based on the unconfined compressive strength log and the well log data; forming a training dataset including the well log data, the training dataset labeled based on the rock type clusters; training a supervised machine learning model using the training dataset. While drilling a well in the subsurface formation, logging-while-drilling data is obtained from drilling equipment used to drill the well; and rock types in the subsurface formation are determined using the supervised machine learning model and the logging-while-drilling data.

The invention discloses a formation pressure prediction method and device, electronic equipment and a storage medium. The method comprises the steps that logging-while-drilling data of a target area are acquired; performing variable sequence characteristic quantification on the continuous time sequence logging-while-drilling data by using a recurrent neural network to obtain sequence characteristics; on the basis of the sequential features, weighted values of all logging parameters in the logging-while-drilling data are constructed through an attention mechanism, and then stratum deposition features are constructed through a preset weight parameter matrix; inputting the stratum deposition characteristics into a prediction model to predict and obtain a stratum pressure prediction value of the target area; wherein the prediction model is obtained based on a full-connection network through training of formation feature representation marked with actual formation pressure. The method can efficiently and accurately realize formation pressure prediction, and can be widely applied to the technical field of data prediction.

The invention discloses a rotary steerable drilling trajectory prediction method based on deep learning and knowledge distillation, and belongs to the technical field of drilling trajectory prediction, and the method comprises the following steps: collecting rotary steerable drilling site ground data and while-drilling well logging data, and carrying out data preprocessing; constructing a teacher model and training; the teacher model comprises a well drilling feature enhancement module and a sequence change prediction module; a teaching assistant model is constructed and trained, and the teacher model is assisted to carry out multi-interlayer data adaptive compression; a composite knowledge distillation framework and a student model are built, the student model is trained, and the trained student model is a lightweight borehole trajectory prediction model; during field application, ground data and logging-while-drilling data are preprocessed and then sent into the lightweight well track prediction model, a well track prediction value in the rotary steering drilling process is obtained, and therefore drilling operation parameters are adjusted in time according to a prediction result. According to the method, high-precision and light-weight well track prediction is realized.

The invention relates to the technical field of logging-while-drilling instruments, in particular to a signal construction method based on an azimuth logging-while-drilling instrument. The method comprises the following steps: forming a plurality of groups of measurement modes under different source distances on the basis of a multi-transmitting multi-receiving antenna system of a while-drilling azimuth logging instrument, and compensating a calculation definition formula of a voltage component; symmetrical compensation combinations are added on multiple groups of measurement modes under different source distances, symmetrical positive compensation and symmetrical inverse compensation are carried out on signals, and a combined strategy of multi-source-distance focusing and symmetrical compensation combinations is constructed; according to the joint strategy, the geological signal is defined, the error is reduced, and the measurement precision is improved.

The utility model discloses a novel mining logging-while-drilling instrument which comprises a measuring instrument body, the measuring instrument body is installed in a groove formed in the outer side of an extending shell, and the outer side of the extending shell is in threaded connection with a protection frame. The bottom of the lower end of the extending shell is connected with the top of a shock absorber arranged in a clamping groove formed in the middle of the upper end of the connecting short section, meanwhile, a threaded cylinder is installed in the middle of the lower end of the connecting short section, a shock-proof spring is arranged on the outer side of the threaded cylinder, the inner side of the threaded cylinder is connected with the drill bit body, and meanwhile the lower end of the shock-proof spring is attached to the upper end of the drill bit body. According to the novel mining logging-while-drilling instrument, a shock absorber, a positioning ring, a positioning rod and a buffer spring are matched for use, so that when a drill bit body conducts drilling, stress is dispersed, damage to an extension shell is reduced, meanwhile, through matched use of a threaded cylinder, a connecting ring, an inserting rod, an inserting seat and a positioning block, the drilling efficiency is improved, and the drilling efficiency is improved. The drill bit body and the connecting short section are connected more stably, and the use practicability is improved.

The invention discloses a reservoir fracture distribution prediction method and system based on big data, and relates to the technical field of oil and gas field development, and the method comprises the steps of multi-source data collection and fusion, multi-scale feature extraction and optimization, hybrid model construction and three-dimensional fracture probability body generation, and fracture distribution prediction and visual display. According to the method, prediction blind areas are reduced by collecting multi-source heterogeneous data, physical constraints are achieved by introducing a Griffith criterion so as to enhance geological rationality, dynamic data and static geological data of fracturing construction are subjected to combined modeling, dynamic fusion of multi-source data is achieved, timeliness of crack prediction is improved, in addition, the physical constraint hybrid model is adopted, and the prediction efficiency is improved. And spatial characteristics and dynamic response are considered through a CNN-GBDT hybrid architecture, a fracture mechanics criterion is embedded to enhance interpretability, real-time access of logging-while-drilling data in the drilling process is supported, and key technical support can be provided for unconventional oil and gas development.

The embodiment of the invention discloses a quality control method and device for logging-while-drilling data and computing equipment. The method comprises the following steps: acquiring actually measured signal values of different sampling orientations acquired by the electromagnetic wave logging-while-drilling instrument at a target depth; performing waveform fitting on the actually measured signal values of different sampling orientations to generate a waveform coefficient corresponding to the target depth; fitting signal values of different sampling directions are generated based on the waveform coefficients; extracting a waveform baseline from the waveform coefficient, processing the measured signal value by using the waveform baseline to obtain a corrected measured signal value, and processing the fitted signal value by using the waveform baseline to obtain a corrected fitted signal value; calculating a data error of the sampling orientation according to the corrected actual measurement signal value and the corrected fitting signal value of the sampling orientation; and generating a quality index value of the target depth according to the data errors of different sampling orientations at the target depth. According to the scheme, accurate quality detection and accurate control of the logging-while-drilling data can be achieved, and the subsequent logging data analysis accuracy is improved.

The invention discloses a guiding method, a guiding system, a guiding device and a guiding medium based on a dynamic three-dimensional geologic model for logging while drilling. According to the guiding method, the guiding system and the guiding device, a three-dimensional geologic model around a horizontal well is constructed by utilizing conventional logging data of a vertical well around the horizontal well; latest horizontal well drilling and logging data and horizontal well conventional logging-while-drilling data information are supplemented into the model, and a three-dimensional geologic model body is continuously iterated and updated, so that the unification of the three-dimensional geologic model, drilling, logging and logging-while-drilling understanding is realized; the spatial relationship between the current drilling direction and a high-quality reservoir is judged in a mode of slicing along the track of the forward drilling horizontal well, decision data is provided for horizontal well geosteering, and the purpose of improving the drilling rate of an oil layer and a gas layer of the horizontal well is achieved.

A method for constructing a high fidelity logging while drilling (LWD) log that includes obtaining a temporal well depth log (701) and a plurality of temporal LWD logs (702) from a drilling operation. The method further includes obtaining a temporal record of operational drilling parameters (704) from the drilling operation. The method further includes determining, using a first machine-learning model (706), a temporal history (708) of the drilling operation and constructing, using the temporal well depth log (701) and the plurality of temporal LWD logs (702), a plurality of temporal property logs (710) at each depth in the plurality of depths. The method further includes processing the plurality of temporal property logs (710) with, at least, a second machine-learning model (714) to form a plurality of corrected temporal property logs (716) and aggregating the plurality of corrected temporal property logs (710) to form a plurality of high fidelity LWD logs (722).

According to the logging-while-drilling data lag compensation method based on deep learning provided by the invention, the prediction precision of the lag logging-while-drilling data is improved by combining the drilling engineering data and the historical logging-while-drilling data. According to the method, an encoder-decoder neural network model based on a self-attention mechanism is utilized, lag logging-while-drilling data is predicted in combination with drilling engineering features, and prediction precision is improved through a convolutional layer. Results show that when the method is used for predicting the gamma curve in the logging-while-drilling data, the root mean square error within the prediction range of 30 meters is lower than 0.589, and the average absolute percentage error is lower than 1.587. The problem of lag of the logging while drilling data is effectively solved, the operation risk under the complex stratum condition is reduced, the drilling strategy can be optimized in real time, and the safety and efficiency of the drilling process are improved.

The present application relates to the field of logging while drilling and intelligent steering control technology in oil and gas drilling engineering, in particular to a rotary steering drilling adaptive trajectory control method for image processing. It comprises: receiving original logging while drilling image data frames of downhole transmission channels; generating a high-resolution predicted geological texture map; synchronously generating a feature uncertainty distribution map representing the pixel probability distribution characteristics in the high-resolution predicted geological texture map; calculating the matching degree of the high-resolution predicted geological texture map and a preset stress-induced artifact feature library; generating a sensor contamination marker signal; calling a safety baseline geological model constructed before drilling; calculating the geological texture structure difference value relative to the safety baseline geological model; generating a geological illusion entropy; receiving the geological illusion entropy and the sensor contamination marker signal; and driving a downhole steering tool according to the activated mode. The present application ensures that the steering instruction is always based on the real existing geological information, and avoids the deviation of the drilling trajectory caused by the fictitious texture.

The invention relates to the technical field of centralizers, in particular to a logging-while-drilling tool anti-disengaging damping centralizing device and a using method, the logging-while-drilling tool anti-disengaging damping centralizing device comprises at least two centralizing damping short sections, and each centralizing damping short section comprises an outer sleeve, a centralizing damping part and a fastening adjusting part. The fishing device is reasonable and compact in structure and convenient to use, the logging-while-drilling instrument string can be fixedly installed in the middle of the inner side of the centralizing and damping short section through the centralizing and damping part, the fastening and adjusting part and the stop part, and when underground complexity and drilling tool jamming occur, the fishing device and the upper end of the logging-while-drilling instrument string are clamped and fixed together, and the centralizing and damping short section is fixed to the centralizing and damping short section. When a well logging while drilling instrument string is fished out of a well, the well logging while drilling instrument string can be separated from the centralizing and damping part by dragging the fisher upwards, penetrates through the inner side of a small water hole of the accident handling tool upwards and is fished out of the well quickly, and then underground complex and drill jamming accidents are handled through the accident handling tool, so that the fishing operation efficiency of the well logging while drilling instrument string is effectively improved; and the logging while drilling instrument string is prevented from being buried underground to cause heavy property loss.

The present invention discloses a horizontal rotary test bench for logging while drilling instruments, which improves the technical problem of electromagnetic interference to logging instruments. The device comprises a front support seat, a middle support seat and a rear support seat which are arranged in sequence, and a limiting part is respectively arranged on the middle support seat and the rear support seat, and the two limiting parts are used to jointly support and limit the logging instrument and keep the logging instrument horizontal; a shielding box is arranged on the front support seat; a power shaft, one end of which is located inside the shielding box and the other end extends to the outside of the shielding box; a motor power source is arranged in the shielding box and is used to control the rotation of the power shaft; a transmission part, one end of which is connected to the power shaft and the other end is used to connect to the logging instrument, and the transmission part is used to transmit the torque of the power shaft to the logging instrument, so that the logging instrument rotates along its own axis. The present invention can reduce electromagnetic interference, ensure the debugging accuracy of the logging instrument, and thus ensure the smooth progress of the drilling operation.

The invention discloses a section cluster optimization design method based on geological guidance mechanical specific energy intelligent correction, which comprises the following steps: determining a target stable point set according to a multi-scale local stability index in each lithologic layer section, and obtaining the lithologic layer section by performing lithologic layered clustering on logging while drilling data along a horizontal well section and corresponding well depth data; in each lithologic layer section, according to the mechanical specific energy median and / or the mechanical specific energy prediction result of the target stable point, performing layered correction on the original mechanical specific energy, the mechanical specific energy prediction result being obtained based on prediction of the target stable point set; according to the geological dessert labels and the corresponding well depth data, fracturing sections are divided; and in the fracturing section, according to the mechanical specific energy after layering correction and the geological dessert label, a cluster arrangement strategy is formulated, and perforation clusters are optimally designed based on the cluster arrangement strategy. According to the method, the mechanical specific energy can be corrected accurately and efficiently at low cost, so that the accuracy and practicability of fracturing segment cluster optimization design can be improved based on the corrected mechanical specific energy.

The invention discloses a three-dimensional crustal stress intelligent prediction method fusing physical information, and relates to the technical field of reservoir numerical simulation. The method comprises the following steps: acquiring three-dimensional crustal stress, logging-while-drilling parameters related to the three-dimensional crustal stress and lithologic parameters of developed reservoirs in the same block, matching the three-dimensional crustal stress, the logging-while-drilling parameters and the lithologic parameters, and then performing data preprocessing on the three-dimensional crustal stress, the logging-while-drilling parameters and the lithologic parameters; on the basis of a CAE self-encoder, feature extraction is conducted on the preprocessed logging-while-drilling parameters and the preprocessed core parameters, and parameters obtained after dimension reduction are obtained; based on an AVE auto-encoder, performing data enhancement on the parameters after dimension reduction and the preprocessed three-dimensional crustal stress to generate more samples; based on a PINNs neural network, training is carried out in combination with an Adam optimizer, and a trained model is used as a prediction model. According to the method provided by the invention, the prediction precision and robustness are improved when the method faces heterogeneous and anisotropic reservoirs, so that accurate crustal stress prediction is provided for efficient development of compact conglomerate reservoirs.

The present disclosure belongs to the field of geological prospecting and particularly relates to an intelligent real-time updating method and system for a stratigraphic framework with geosteering-while-drilling, aiming to solve the problems of insufficient precision in position and dipping angle of a stratigraphic framework due to differences in parameters measured by different instruments for well logging and mud logging while drilling. The method of the present disclosure comprises: obtaining existing well data, and acquiring well logging data and images imaged while-drilling in real time; constructing an initial stratigraphic framework model, eliminating abnormal values, and conducting dimensionality reduction; and based on dimensionality reduction well logging data, conducting non-linear clustering through a density peak clustering method, obtaining a marker layer primary prediction result through a marker layer prediction model of a depth belief network and conducting correction, to obtain a corrected stratigraphic framework model and to adjust a drilling trajectory.

The invention belongs to the technical field of logging instruments, and particularly relates to a logging-while-drilling device. The logging-while-drilling device comprises a shell, the shell is detachably arranged on a downhole tool, and at least one antenna is arranged in the shell; a plurality of magnetic bars are uniformly arranged in the shell along the circumferential direction, and the central axis of each magnetic bar is parallel to the central axis of the shell; and the measuring circuit is arranged in the underground tool in a sealing manner and is connected with the antenna. The operation and maintenance difficulty of the antenna can be reduced, and installation is convenient.

The invention provides a logging-while-drilling data transmission system and method based on an underwater acoustic communication technology, and the method comprises the steps: enabling logging-while-drilling data to be intelligently compressed through an annular underwater acoustic communication transmitting transducer disposed at the upper end of a logging-while-drilling short section and an annular underwater acoustic communication receiving transducer at a well mouth, and converting the data into a sound wave signal at a well bottom; the drilling fluid is sent from the well bottom to the well mouth in an underwater acoustic communication or acoustic wave mode through a drilling fluid channel in the drill hole. The real-time transmission efficiency of the logging-while-drilling data can be greatly improved through the rate of underwater acoustic communication, and the logging-while-drilling data can be rapidly provided for well drilling engineers in real time. Real-time processing and comprehensive explanation are carried out on logging while drilling data transmitted in real time on a drilling site, and real-time optimization and adjustment of a well track can be carried out according to a comprehensive explanation result, so that intelligent geosteering drilling is realized, the drilling rate of a high-quality reservoir is finally improved, and the oil and gas yield of a single well is increased.

The invention discloses a while-drilling pressure formation force monitoring method and a while-drilling pressure formation force monitoring device. The method comprises the steps that logging-while-drilling parameters of at least one normal-pressure well section in drilled sections of a well to be monitored are obtained, and the first drilling fluid outlet temperature slope of the normal-pressure well section is determined according to the logging-while-drilling parameters of the normal-pressure well section; acquiring logging-while-drilling parameters of the current drilling well section of the to-be-monitored well, and determining a second drilling fluid outlet temperature slope of the current drilling well section according to the logging-while-drilling parameters of the current drilling well section; according to the first drilling fluid outlet temperature slope and the second drilling fluid outlet temperature slope, the formation pressure coefficient change condition is determined; and determining whether the formation pressure is normal or not according to the formation pressure coefficient change condition and a preset formation pressure coefficient change condition threshold value. According to the pressure transition zone logging parameter response characteristics, the formation pressure change can be found in the actual drilling process, and therefore the abnormal pressure early warning effect is achieved.

The invention discloses a while-drilling azimuth acoustic logging data acquisition method, and belongs to the technical field of while-drilling logging. The invention discloses a while-drilling azimuth acoustic logging data acquisition method. The method comprises the following steps: S1, acquiring natural gamma intensity, formation resistivity, three-axis vibration signals and a tool face angle of a current depth formation; s2, geological events of the current stratum are recognized according to the natural gamma intensity, the stratum resistivity and the three-axis vibration signals, and the geological events comprise a first geological event and a second geological event; s3, a first collection strategy is executed on the first geological event to collect waveform data, a second collection strategy is executed on the second geological event to collect waveform data, the first collection strategy and the second collection strategy both adopt an equal azimuth interval collection scheme, and the azimuth interval of the first collection strategy is larger than that of the second collection strategy; and S4, transmitting the waveform data acquired by the first acquisition strategy to a time difference statistical value, compressing the waveform data acquired by the second acquisition strategy, and preferentially transmitting the waveform data.