147 results about "Oil exploration" patented technology

The invention relates to a construction method, device, equipment and medium of a complex geological reservoir model, and relates to the technical field of oil exploration and development. Comprising the following steps: combining obtained riverway scale parameter data obtained by field actual measurement, a three-dimensional digital outcrop profile of an outcrop profile of a research area, a geological knowledge database of configuration units at all levels of a sub-facies reservoir of the research area, and sedimentary microfacies distribution of the outcrop profile of the research area obtained by combining the riverway scale parameter data to obtain X, Y, Z, Z, Z and Z; performing two-dimensional training image slicing in three directions of Z and Z; and performing three-dimensional training image simulation on the two-dimensional training image slices by using an s2Dcd-DS coupling algorithm, and performing three-dimensional geological modeling by using a multi-point geostatistics modeling algorithm to obtain a three-dimensional geological model. According to the construction method provided by the invention, the complex geological conditions and structural characteristics of the complex geological reservoir such as the plains of the braided river delta can be effectively represented, and oil and gas distribution, well location deployment and remaining oil excavation of the braided river reservoir can be guided.

The invention provides a rare earth silicon germanate scintillating material and a preparation method and application thereof, in particular to a rare earth silicon germanate scintillating material with high thermal stability and strong radiation resistance and a preparation method and application thereof, the general formula of the rare earth silicon germanate scintillating material with high thermal stability and strong radiation resistance is RE2 (1-x-delta / 2) Ce2xGedeltaSi (1-y + delta) Gey-deltaOz, in the formula, 0 lt; x is more than or equal to 0.05, y is more than or equal to 0.15 and less than or equal to 0.5, delta is more than or equal to 0 and less than or equal to 10 <-4 >, z is more than or equal to 4.95 and less than or equal to 5.05, RE represents a rare earth element, and the rare earth element is selected from at least one of lanthanum (La), lutetium (Lu), yttrium (Y) and gadolinium (Gd). The rare earth silicon germanate scintillating material provided by the invention has the characteristics of strong radiation damage resistance, high scintillation light output, low afterglow and the like while greatly improving the thermal stability, and can be used in occasions with extremely high requirements on the thermal stability or radiation resistance of the material, such as high-energy physical experiments, nuclear medicine imaging, oil exploration wells and the like.

The invention provides a method for constructing a geoelectric structure prediction model based on time-frequency electromagnetism, and belongs to the field of oil exploration. The method comprises the following steps: firstly, establishing an initial reservoir model based on a model-driven geophysical inversion process; then geophysical data and a corresponding reservoir model data set are collected, classified and standardized, and construction of the data set is completed; establishing a reservoir geoelectric structure prediction model based on the deep learning model; and finally training the reservoir geoelectric structure prediction model by using the data set to obtain an optimized reservoir geoelectric structure prediction model. Wherein the reservoir comprises an ultra-deep carbonate rock reservoir; the invention further provides a method for constructing the model for predicting the geoelectric structure of the ultra-deep carbonate reservoir. Compared with the prior art, according to the geoelectric structure prediction model constructed by the method, when observation data is input, an inversion result can be obtained without executing an iteration process, and the reservoir oil-water relationship can be further analyzed according to the inversion result.

The invention provides a method and system for identifying a volcanic institution facies belt boundary, and belongs to the technical field of oil exploration and development. The method comprises the following steps: dividing a drilled facies belt according to three-dimensional seismic reflection characteristics and a preset type of lithofacies proportion of a drilled well; constructing a near-source facies belt pseudo well and a far-source facies belt pseudo well based on the division result of the drilled facies belt and the multiple types of drilled lithofacies; based on the near-source facies zone pseudo well and the far-source facies zone pseudo well, determining a value range corresponding to a preset type of lithofacies proportion of the volcanic institution; based on the three-dimensional seismic data volume of the volcanic institution, a planar graph representing a facies belt is obtained; according to the value range corresponding to the preset type lithofacies proportion of the volcanic institution, volcanic institution facies belt division is carried out on the planar graph representing the facies belt, and the boundary between the near-source facies belt and the far-source facies belt is obtained. Therefore, the boundary between the near-source phase belt and the far-source phase belt is accurately and effectively defined, the near-source favorable phase belt of the volcanic institution is quickly focused, and a foundation is laid for an exploration target.

The present application relates to the technical field of oil exploration, and more particularly to a pipe expanding type screw drill stator forming equipment, comprising: an outer mold structure, comprising an outer mold sleeve, the inner side of the outer mold sleeve having an inner profile line; a mold sleeve driving structure connected with the outer mold structure, used for driving the outer mold structure to rotate along its axis; an inner membrane core, provided in the outer mold sleeve, having a guide neck expanding section and a profile line section, the outer side of the profile line section having an outer profile line; a heating structure, provided at the front side of the guide neck expanding section; a forming support structure, used for supporting the outer mold structure, the mold sleeve driving structure, the inner membrane core and the heating structure; in the processing state, the pipe blank to be processed is heated by the heating structure, expanded in diameter by the guide neck expanding section, and then enters between the outer mold sleeve and the inner membrane core, the outer mold sleeve is driven to rotate by the mold sleeve driving structure, and the stator with the inner and outer profile lines is formed under the action of the inner and outer profile lines, which can solve the problems of deviation, low precision and low processing efficiency of the existing stator forming process.

The invention provides an oil exploration AI modeling system and method based on machine learning, and the method comprises the steps: comparing a time-delay seismic monitoring data volume of a target exploration work area with a reference seismic data volume, and generating a time-lapse seismic difference data volume; constructing a topological connection diagram according to a grid structure of the initial oil reservoir geologic model, and constructing a graph neural network by taking the difference data volume as an observation constraint of node attribute change, and further reasoning to obtain an attribute dynamic correction amount of each grid unit in the initial oil reservoir geologic model; generating a dynamically updated three-dimensional oil reservoir geologic model according to the attribute dynamic correction, and identifying a boundary section needing to be re-evaluated according to gradient change characteristics of the attribute dynamic correction in space; and generating an oil reservoir geologic model parameter adjustment instruction through the boundary section and the dynamically updated three-dimensional oil reservoir geologic model. By adopting the scheme of the invention, fault-crossing attribute error transmission can be avoided.

The utility model relates to the field of oil exploitation, in particular to an underground sampling device for oil exploitation. The underground sampling device for oil exploitation comprises a shell, the shell comprises a mounting pipe, the front end and the rear end of the mounting pipe are in threaded connection with an end socket and a tail pipe respectively, a plurality of through openings are formed in the outer side wall of the mounting pipe in a surrounding mode, and a hanging ring is fixedly mounted at the upper end of the end socket; a sampling barrel is slidably connected into the mounting pipe, the outer diameter of the sampling barrel is consistent with the inner diameter of the mounting pipe, the sampling barrel comprises a plurality of collecting barrels, collecting grooves are formed in the collecting barrels, liquid inlets communicated with the collecting grooves are formed in the outer side walls of the collecting barrels, and the collecting barrels are in threaded connection in sequence end to end. According to the device, petroleum at different depth layers in a well can be sampled for multiple times in one-time well descending operation, repeated well descending operation is not needed, compared with a traditional sampling mode, time and labor cost are greatly saved, and the working efficiency of petroleum sampling is improved.

The invention relates to the technical field of oil exploration, and provides an analysis method and device for safe tripping-in of a well completion pipe string, and the method comprises the steps: obtaining the actual hook load data and well section information of an open hole section based on a drifting process; constructing a tubular column friction torque calculation model of the drifting drilling tool assembly; on the basis of the tubular column friction resistance torque calculation model, the actual hook load data of the open hole section and the well section information of the well, the well hole open hole section friction resistance coefficient is calibrated; on the basis of well section information and the well hole open hole section friction resistance coefficient, a solving model of the axial force of the well completion pipe string and a critical load value calculation model of well completion pipe string buckling are built; and on the basis of the solving model of the axial force of the well completion pipe string and the calculation model of the critical load value of buckling of the well completion pipe string, whether the well completion pipe string is safely tripped is determined. According to the method, the friction resistance coefficient in the drifting stage is determined, the invisible shaft cleaning state is known, the current friction resistance coefficient is used for evaluating the to-be-tripped well completion pipe string, and therefore operation risks and operation complexity are avoided, and the operation efficiency is improved.

The utility model relates to the technical field of camping houses, and discloses a camping house for petroleum exploration, which comprises a living box body, two entrances and exits are symmetrically arranged on the side edges of the living box body, closing doors are rotatably mounted on the entrances and exits, a box body supporting assembly is arranged at the bottom of the living box body, and a box body is arranged on the box body supporting assembly. A box body supporting assembly is arranged at the bottom of the living box body, a moisture-proof height adjusting assembly is arranged on the box body supporting assembly, the box body supporting assembly and the moisture-proof height adjusting assembly are arranged at the bottom of the living box body, and a polyurethane foam plate and a waterproof sealing plate are arranged at the bottom of a supporting bottom plate in the box body supporting assembly. The polyurethane foam plate can improve the moisture-proof capacity of the bottom of the supporting bottom plate, so that the distance between the bottom of the living box body and the ground can be flexibly adjusted according to user requirements, the ventilation capacity of the bottom of the living box body is improved, and the box body supporting assembly at the bottom of the living box body can be effectively prevented from being easily affected with damp for a long time to be damaged; the service life is prolonged.

The invention relates to the technical field of oil exploration and development, in particular to a winding type belt driving tower crane roller and a kinetic parameter calculation method thereof, and mainly solves the problems that an existing belt friction type driving roller of a tower crane is low in efficiency, and a kinetic parameter calculation method of the belt friction type driving roller cannot be suitable for a belt winding type roller. The device comprises a barrel, three belts are wound on the outer surface of the barrel, beam hanger end belts are arranged on the two sides, a counterweight end belt is arranged in the middle, one end of each beam hanger end belt is fixed to the barrel, the other end of each beam hanger end belt is connected with a beam hanger, one end of each counterweight end belt is fixed to the barrel, and the other end of each counterweight end belt is connected with a counterweight. According to the winding type belt driving tower crane roller, friction type driving is changed into belt tension driving, driving is more reliable, the efficiency of a tower crane is greatly improved, meanwhile, various characteristic values of the suspension point end and the balance weight end of the tower crane can be accurately obtained through a kinetic parameter calculation method, and scientific reference bases are provided for optimal selection of operation parameters of the tower crane.

The invention discloses a production well oil-water two-phase output condition evaluation method and system, and relates to the technical field of oil exploratory wells, and the method comprises the steps: solving a pressure value, a pressure change rate, a temperature value and a temperature change rate at a non-perforation stable section of a target production well based on temperature-pressure profile test data; inputting the pressure value, the pressure change rate, the temperature value and the temperature change rate into a production well oil-water two-phase output condition evaluation model to obtain the liquid production capacity, the oil production capacity, the water production capacity and the water content of each section of the target production well; based on the liquid production capacity, the oil production capacity, the water production capacity and the water content, the oil-water two-phase output condition of the target production well is evaluated.

The application belongs to the technical field of oil exploration, and discloses a method for improving the precision of a velocity model by using azimuth information, which comprises the following steps: improving the signal-to-noise ratio of shot gather data; establishing an initial velocity model in the depth domain; improving the signal-to-noise ratio of pre-stack depth migration profiles; outputting reflection angle gathers; picking up azimuth residual depth differences; obtaining azimuth residual depth differences after ray tracing; obtaining new velocities and velocity updating amounts; obtaining final velocities; and performing depth migration processing, and iteratively updating the new velocities until the reflection angle gathers and common offset gathers are flattened. The application improves the velocity inversion precision of middle and deep layers and effectively improves the velocity inversion precision of shallow layers. The application is suitable for establishing a velocity model in the depth domain.

The application relates to the technical field of mechanical equipment, in particular to a drilling fluid centrifuge device for oil exploitation, which comprises a screw propeller, a rotating drum, a driving assembly, a cleaning assembly I and a cleaning assembly II. According to the working principle of the existing horizontal screw centrifuge, the screw propeller rotates in the same direction as the rotating drum, but the rotating speed is lower than that of the rotating drum. Three roller brushes are rotationally connected to the outer side of the screw propeller, the right ends of the three roller brushes are rotationally connected to a tripod, the tripod is fixedly connected to the right end of the screw propeller, a gear is fixedly connected to the position close to the right end of the three roller brushes, a tooth ring is fixedly connected to the inner wall of the right end of the rotating drum, the tooth ring is engaged with the gear, so that the tooth ring is driven to rotate when the rotating drum rotates, and then the engagement between the tooth ring and the gear drives the gear to rotate, so that the gear drives the roller brushes to rotate, and the stationary ring layer on the inner wall of the rotating drum is further cleaned when the roller brushes rotate.

The present application belongs to the technical field of oil exploration, and discloses a method for evaluating the development degree of sand-mudstone reservoir-cap assemblage, which specifically comprises the following steps: conducting regional data analysis for a study area, and mastering the core / cuttings data, logging data and oil testing and production testing data of drilled wells, as well as the seismic data and seismic interpretation horizon data of the whole work area; conducting pre-stack deterministic inversion based on Zeoppritz equation to obtain the data body of the ratio of P-wave velocity to S-wave velocity in the work area; extracting the numerical value of the ratio of P-wave velocity to S-wave velocity along the sandstone layer interpreted by the seismic data to obtain the plan view of the sandstone reservoir; extracting the numerical value of the ratio of P-wave velocity to S-wave velocity along the mudstone layer interpreted by the seismic data to obtain the plan view of the mudstone cap rock; quantifying the relative development degree of the reservoir-cap assemblage by a development degree index calculation formula, constructing the plan view of the development degree index of the sand-mudstone reservoir-cap assemblage, and quantitatively dividing the development degree of the reservoir-cap assemblage. The present application can clearly define the development range of high-quality reservoir-cap assemblage, delineate the favorable exploration area, and further guide the well site deployment of exploration wells.

The invention discloses an ocean platform-pipe column-seabed equipment multi-body coupling experiment device and method, and the device comprises an experiment frame which comprises a top pedestal, a bottom pedestal, and a supporting mechanism disposed between the top pedestal and the bottom pedestal; the drilling simulation rotating system comprises a motor and a simulation drill rod, the motor is installed on the top base, the upper end of the simulation drill rod is detachably connected with the motor, and the lower end of the simulation drill rod is provided with a simulation underwater wellhead through a connecting device; seabed soil is contained in the soil box; and the detection device is used for detecting working parameters of the simulation drill rod, and the working parameters comprise any one or combination of the following parameters: stress parameters, rotation speed and torque. Experimental simulation requirements of deep-sea oil exploration and development can be met, so that actual production is guided, and the drilling efficiency and the success rate are improved.

The application provides a sample classification method and device for first arrival wave deep learning, and relates to the technical field of oil exploration. The method comprises the following steps: acquiring training sample data and classification information to which the training sample data belongs; the training sample data comprises first arrival sample data and first arrival label data corresponding to the first arrival sample data; a classification network model is trained by using the training sample data and the classification information to obtain a training result; and the training result is used for classification prediction processing on to-be-classified first arrival sample data to obtain a first arrival sample classification result. The application can accurately and efficiently classify and screen the first arrival sample data, enriches the type feature information of the first arrival sample data, and improves the pertinence and effectiveness of first arrival wave sample deep learning.

The invention discloses a green power data center energy consumption sensing method and equipment based on offshore oil exploration, and the method comprises the steps: deploying green power grids on sea surface islands, and supplying power to a green power data center for offshore oil exploration; calculating the green power output of each green power grid and the offshore oil exploration task load of the green power data center, and determining the green power margin of each green power grid; whether the green power margin of the green power grid with the shortest distance to the green power data center meets the requirement of the green power data center for dynamically adjusting the server frequency is judged, and if yes, the green power grid with the shortest distance serves as the optimal green power grid; otherwise, adopting a minimum green power waste priority strategy to select an optimal green power grid; and dynamically adjusting the server frequency of the green power data center according to the green power margin of the optimal green power grid, and executing the offshore oil exploration task of the green power center. According to the energy consumption perception of the green power data center, the server frequency is dynamically adjusted to match the green power output, and the green power utilization rate is improved.

The invention belongs to the technical field of oil exploration and development, and discloses a method for establishing a porosity model of a karst fracture-vuggy carbonate reservoir. The method comprises the following steps: firstly, carrying out drilling curve correction on a drilling well which only has a small part of drilling emptying and leakage and obtains logging information, and then fitting a relatively reliable porosity curve as a hard data constraint for porosity modeling to carry out modeling; and then the fracture porosity is calculated by adopting a sensitive seismic attribute engraving method and then converted into a probability body, and finally a porosity model is established through combination, so that the method has a relatively high practical application value for fracture-vug type carbonate rock porosity modeling.

The application discloses a kind of based on multi-scale attention prototype network small sample core image classification method.For the classification dilemma caused by few core samples and difficult to label, the application proposes a prototype measurement scheme that fuses multi-scale features and attention enhancement.The method uses a differentiated enhancement strategy, uses pre-trained ResNet-18 as the backbone network, extracts shallow and middle layer features, and embeds CBAM modules in the deep layer to calibrate spatial and channel weights and strengthen key texture focusing.The three layers of features are cascaded and fused to construct an AttnMS-ProtoNet model.During classification, the N-way K-shot sampling is used to simulate the small sample scenario, the class prototype is generated by calculating the mean of the support set, and the learnable temperature coefficient is introduced to dynamically scale the normalized cosine similarity and adaptively expand the class boundary.Model training is completed through label smoothing and stepwise learning rate.This method effectively alleviates overfitting and significantly improves the accuracy of core image classification, providing technical support for oil exploration and reservoir evaluation.

The invention discloses an intelligent drift diameter detection device and method, and relates to the technical field of oil exploration. One end of a drift diameter gauge of the device is connected with a flexible connecting piece, and the other end of the flexible connecting piece can be fixed on a wire arrangement assembly; the wire arranging assembly can adjust the length of the flexible connecting piece according to the tensile force of the flexible connecting piece so as to adjust the position of the drift diameter gauge. A driving part is arranged on the side, close to the supporting assembly, of the drift diameter gauge, and the driving part can drive the drift diameter gauge to move towards the to-be-detected pipe or move away from the to-be-detected pipe. The drift diameter gauge can achieve the effect of automatically detecting the pipe to be detected through the drift diameter gauge, meanwhile, whether the drift diameter gauge is clamped in the pipe to be detected or not is automatically detected according to the tensile force of the flexible connecting piece, if the clamping condition occurs, the drift diameter gauge can be restored to the initial position through the wire arrangement assembly and the flexible connecting piece, and it can be seen that the detection accuracy is improved. The intelligent drift diameter detection device has the advantage of high automation degree.

The application discloses a well control velocity modeling method based on structure guidance and application thereof, and belongs to the technical field of seismic data processing in oil exploration. The application utilizes logging, VSP velocity and seismic velocity analysis, establishes a space variable factor field based on structure guidance, further uses the space variable factor field to constrain a multi-azimuth grid tomography residual velocity field, optimizes velocity update quantity, completes multi-azimuth grid tomography multi-round iteration of the well control velocity field based on structure guidance, and obtains the well control velocity model based on structure guidance. The well control velocity model obtained by using the modeling method provided by the application can consider the longitudinal resolution and the lateral change law of the velocity field, ensures that the updated velocity field is consistent with the well velocity, and the velocity change trend is also consistent with the seismic geology. The application can be used for establishing a high-precision velocity field and a Q field and for "true" surface TTI prestack depth migration, and is further applied to the fields of prestack inversion and calculation of geomechanical parameters.

The invention provides a method and system for depicting an optimal oil gas enrichment area based on strike-slip fracture, and belongs to the technical field of oil exploration and development, and the method comprises the following specific steps: S1, calibrating a drilled well, and selecting an auxiliary layer according to a calibration result; s2, performing coherence calculation on the points on the auxiliary layer to obtain an auxiliary layer plane coherence graph, and making the color of the points with higher coherence darker, namely depicting strike-slip fractures on the auxiliary layer plane coherence graph; and S3, obtaining a target layer reservoir plane distribution diagram, superposing the auxiliary layer plane coherence diagram and the target layer reservoir plane distribution diagram, and selecting a place which has strike-slip fracture and is a development area as an oil and gas enrichment area. According to the method, the position and the trend of the strike-slip fracture can be clearly displayed on the auxiliary layer plane coherence map through the auxiliary layer coherence technology, after the reservoir plane coherence map is stacked, the oil and gas enrichment area can be more accurately recognized, and then efficient development of the oil reservoir in the later period is guided.

The application provides a reservoir property detection method and device, electronic equipment and storage medium, and belongs to the technical field of oil exploration and development. The method comprises the following steps: acquiring real-time P-wave azimuth AVO gather data of a well area; inputting the P-wave azimuth AVO gather data into an AVO inversion model which has been constructed, and obtaining reservoir property parameters of the target well area by inversion, wherein the reservoir property parameters comprise S-wave velocity reflectivity, P-wave velocity reflectivity and density reflectivity, and a restriction condition and a weight coefficient are added to an inversion objective function of the AVO inversion model. The application starts from the most basic mathematical level, adds a restriction condition and designs a weight coefficient to the original objective function of least squares, improves the coefficient matrix, so that the sensitivity of the solution of the inversion objective function to errors is reduced, the influence of data errors on the result is determined, noise interference is coped with, and the sensitivity of the solution of the inversion objective function to errors and noise is greatly reduced.

The application discloses an intelligent magnetic detection device for oil exploration, and relates to the technical field of oil exploration, which comprises supporting legs, a detection track fixed on the top of the supporting legs and used for guiding during detection, a driving mechanism arranged on the top of the detection track and used for controlling the detection position within the exploration range to effectively explore, and a detection mechanism arranged on one side of the driving mechanism and used for detecting oil and gas reservoirs and improving the detection accuracy. The detection track is provided with a vortex structure, so that the staff does not need to continuously adjust the position of the device for detection during the exploration, and the detection mechanism is arranged to keep the magnetic detection head vertical and downward during detection, so as to guarantee the measurement accuracy.

The application discloses a velocity and Q fluctuation equation inversion method based on local domain travel time, relates to the technical field of oil exploration, and comprises the following steps: obtaining seismic data through viscoacoustic forward modeling; calculating travel time difference and obtaining time difference accompanying source; calculating inverse propagating wave field and gradient; updating velocity model and Q model. The method is based on wave equation travel time inversion, uses travel time information, avoids the problem of cycle skipping of full waveform inversion under the condition of large time difference, and reduces the dependence on the initial model; the local domain travel time difference is calculated by using the DTW algorithm, the corresponding time difference can be accurately calculated, the cross-correlation algorithm tends to large-amplitude in-phase axis under the condition of large time difference is avoided, and the inversion precision is improved; the method uses travel time information to simultaneously update the velocity and Q, avoids a large amount of Fourier transform calculation in the frequency domain method, and greatly improves the inversion efficiency.

This invention relates to the field of cuttings acoustic wave measurement technology, specifically an automatic positioning and sampling device and method for measuring transverse and longitudinal waves of cuttings. It includes symmetrically arranged slide rails, a synchronization unit slidably mounted on the slide rails via a sliding adjuster, a B-type acoustic wave sensor mounted on the synchronization unit, and an A-type acoustic wave sensor corresponding to the B-type sensor. A rack is provided on the back plate, and a stepper motor moves up and down along the rack. It also includes a thickness measurement module and a thickness calculation module, with the thickness calculation module connected to the sliding adjuster. The thickness measurement module, thickness calculation module, and stepper motor are all connected to an integrated control unit. Through zero-point calibration, cuttings loading and positioning, automatic sensor adaptation and adjustment, and closed-loop pressure monitoring, precise coincidence of measurement points, sensor coaxiality, and precise pressure control are achieved. This invention reduces manual intervention, improves the accuracy and efficiency of cuttings acoustic wave time difference measurement, and provides reliable data support for drilling engineering guidance and reservoir evaluation in oil exploration.

The invention discloses a wave velocity determination method, device and equipment of water hammer pressure waves and a storage medium, which are applied to the field of oil exploration, and the method comprises the following steps: acquiring pump stop water hammer pressure wave data acquired by double sensors; processing the pump stop water hammer pressure wave data based on a wavelet threshold noise reduction method to obtain a reconstructed wavelet signal; determining a cross-power spectrum function between the reconstructed wavelet signals and an auto-power spectrum function of each reconstructed wavelet signal; performing weighting processing on the cross-power spectrum function based on a weighting function determined by the cross-power spectrum function and the auto-power spectrum function to obtain a frequency domain weighting function, and performing inverse Fourier transform on the frequency domain weighting function to obtain a generalized cross-correlation time domain function; based on the generalized cross-correlation time-domain function, the delay inequality of the pump stopping water hammer pressure wave data is determined, and based on the delay inequality, the wave velocity of the water hammer pressure wave is determined. Noise reduction is carried out on the pressure wave signals through a wavelet threshold method, cross-correlation delay calculation is carried out on the pressure wave signals after noise reduction, manual reading errors are avoided, and the water hammer wave velocity calculation precision is improved.

The invention relates to the technical field of oil exploration and development, and discloses a gamma logging curve correction and prediction method based on federal cross-domain collaboration. Aiming at the problems that traditional prediction depends on single-oil-field data, data scarcity and privacy leakage, historical logging-while-drilling data of multiple oil fields are collected and preprocessed, and a gamma logging curve is corrected in combination with the distance between a drill bit and a sensor; a time sequence prediction model based on a self-attention mechanism is constructed, a federated learning framework is established, and a parameter strategy is initialized; and respectively training a global model and a local model, and comparing and determining a final model through index evaluation such as a relative error. According to the method, on the premise that data privacy is protected, the gamma logging curve prediction precision is improved through the cross-oil-field data, and the real-time geological modeling requirement is met.

The utility model relates to the field of oil exploration, in particular to a station switching mechanism for oil well coring, which comprises a shell, a logging and sampling power component used for drilling and sampling the side wall of an oil well is arranged on one side inside the shell, and a plurality of coring barrels arranged in an array mode are arranged on the lower side of the logging and sampling power component. A first clamping pin on a telescopic arm is clamped into a clamping groove, corresponding to the first clamping pin, in a coring barrel assembly, so that the coring barrel assembly moves towards one side along with the telescopic arm pushed by a hydraulic cylinder, and when a next coring barrel moves to the lower side of a logging sampling power assembly, a V-shaped inclined plane of a second clamping pin is pushed through an extrusion inclined plane on a guide rod; when the telescopic arm moves towards the other side, the coring cylinder assembly is prevented from moving along with the telescopic arm, and then switching of coring cylinders on the lower side of the whole logging sampling power assembly is completed.

The present application relates to the technical field of informationization of oil exploration and development and digital processing of whole life cycle management of industrial assets, in particular to a whole life cycle operation and maintenance management system for an oil downhole transmitter, comprising: an asset data management module for building a whole life cycle data lake serving asset value analysis; a benchmark valuation modeling module for generating a theoretical asset value curve of the transmitter under the assumption of no environmental stress; a risk quantification correction module for outputting a risk-adjusted theoretical residual value; a management performance analysis module for calculating a management performance residual after stripping the influence of environmental risks; a decision and execution module for automatically generating differentiated management instructions for asset disposal, inventory strategy adjustment or supplier evaluation, and driving downstream enterprise resource planning systems or inventory control systems to perform closed-loop operations; the present application effectively solves the phenomenon of shirking operation and maintenance responsibilities due to poor well conditions.