259 results about "Seismic inversion" patented technology

The invention relates to the field of shale oil and gas, and discloses a method for identifying a shale oil and gas reservoir dessert, which comprises the following steps: acquiring a core CT image, three-dimensional seismic data and production dynamic data, and carrying out cross-scale preprocessing; constructing a fractional-order non-local seepage field model to represent nano-to-kilometer-level flow characteristics; predicting seepage field parameters through a Lie group symmetry constrained neural network; establishing a cross-scale coupling model of the quantum adsorption effect and the macroscopic seepage law; dynamically updating model parameters based on real-time monitoring data; and executing multi-target collaborative optimization to generate a sweet spot three-dimensional distribution and development scheme. According to the method, a fractal dimension dynamic constraint cross-scale data fusion technology is adopted, the effect of accurate mapping of nanopore and macroscopic fracture network parameters is achieved, and the problem of misalignment of CT scanning and seismic inversion data space registration is solved through pore communication fractal analysis.

The invention relates to the technical field of unconventional oil-gas exploration, and discloses a well-seismic integrated horizontal well geosteering risk evaluation method, which comprises the following steps: S1, acquiring three-dimensional seismic data, measurement while drilling data and geological logging data through a well-seismic integrated data acquisition platform; s2, constructing a horizontal well geosteering dynamic model based on multi-source heterogeneous data, and integrating a seismic inversion result and real-time drilling parameters; by establishing a well-seismic data dynamic fusion mechanism and a multi-source risk quantification model, the problem of space-time dislocation of seismic inversion and measurement-while-drilling data is solved, the recognition precision of a fault boundary, a lithologic interface and a pressure abnormal zone is ensured to be matched with drilling position changes in real time, risk misjudgment caused by model updating lag in a traditional method is eliminated, and the accuracy of the method is improved. The accuracy and timeliness of geosteering decision making of the complex structure area are improved; by monitoring well track deviation and geological model prediction deviation in real time, the risks of well wall instability and target deviation are avoided, and the operation safety of the horizontal well in the full life cycle is guaranteed.

The present disclosure discloses a seismic inversion method based on joint constraint of a physical model and priori information. The method includes: extracting seismic wavelets based on seismic data, and determining an amplitude scaling factor of the wavelets; counting priori information of impedance parameters; establishing an initial impedance parameter model by using seismic structural interpretation information and logging data; obtaining a simplified approximate equation based on an interface weak elasticity difference hypothesis, forward modeling a seismic gather by using the simplified equation, and calculating an inversion residual; rewriting an objective function into a function related to the impedance parameters by using a generalized linear inversion idea, solving the impedance parameters by using an iterative reweighted least squares algorithm, and updating the impedance parameters; and repeating the above steps until the inversion residual reaches the requirements or reaches the maximum number of iterations, and outputting a final processing result.

The invention relates to a depth domain time-lapse seismic joint inversion method and device, equipment and a storage medium, and the method comprises the steps: extracting depth domain seismic wavelets according to obtained logging data, and building a depth domain seismic wavelet matrix; based on the depth domain seismic wavelet matrix, well-seismic calibration is carried out on the basic logging data and the monitoring logging data; solving a difference between the corrected basic logging data and the corrected monitoring logging data, determining differential logging data, performing full-band interpolation according to the differential logging data and the corrected basic logging data to construct an initial model, and obtaining a low-frequency model according to the initial model; establishing a time-lapse seismic simultaneous inversion objective function based on the forward operator of the time-lapse seismic simultaneous inversion; and substituting the low-frequency model into the target function for iterative solution, and outputting a time-lapse seismic inversion result meeting an iteration ending condition, thereby overcoming the limitation of the existing time-lapse seismic method while reducing the workload of time-domain time-lapse seismic inversion processing.

The invention is suitable for the technical field of volcanic rock reservoir gas saturation and permeability prediction, and provides a volcanic rock reservoir gas saturation and permeability seismic inversion method and system, and the method comprises the following steps: collecting data, and building a rock physical model of a volcanic rock reservoir; establishing a rock physical parameter in-well inversion method, and calculating a permeability indication parameter # imgabs0 # and a micro-fracture porosity parameter # imgabs1 #; based on the parameters # imgabs2 # and # imgabs3 #, constructing a gas-bearing seismic indication factor # imgabs4 # and a permeability seismic indication factor # imgabs5 # in combination with logging data; the quantitative relation between the # imgabs6 # and the gas saturation # imgabs7 # and the quantitative relation between the # imgabs8 # and the permeability # imgabs9 # are established through measured data in the well; in combination with rock physics and seismic reflection theories, a PP wave reflection coefficient formula about # imgabs10 # and # imgabs11 # is constructed; the pre-stack seismic inversion method suitable for the volcanic rock reservoir is developed, seismic indication factors # imgabs12 # and # imgabs13 # are calculated, and the seismic indication factors # imgabs14 # and the seismic indication factors # imgabs13 # are quantified into gas saturation # imgabs14 # and permeability # imgabs15 #. According to the method, the quantitative prediction of the spatial distribution of the volcanic rock reservoir gas saturation and permeability is realized.

An approach for calibrating prestack seismic inversion is provided. This method includes selecting various features from inverted elastic properties to generate reservoir properties; fully connected neural network models are used to learn the mapping between the features and ground truth data at well locations; and the prediction is applied to generate one or more final models for the reservoir characterization of the whole survey region.

The invention provides a deep coal seam fracture density azimuth seismic inversion method and device, and relates to the technical field of seismic exploration, and the method comprises the steps: obtaining pre-stack seismic trace set data and logging data of a research work area; constructing an elastic stiffness matrix of which each stratum is a VTI medium based on the logging data; processing the porosity of the coalbed methane reservoir in the logging data and an elastic stiffness matrix of the coalbed methane reservoir as a VTI medium according to a linear slip theory to obtain an elastic stiffness matrix of the coalbed methane reservoir as an orthotropic medium so as to determine an initial model parameter vector; combining a reflection coefficient approximation formula based on pre-stack seismic trace set data and orthoanisotropy to construct an objective function used for inverting model parameters; solving the target function to obtain a target model parameter vector of the research work area; and the target model parameters of the coal bed gas reservoir are processed by using the target prediction model to obtain the fracture density of the coal bed gas reservoir, so that an effective technical means is provided for inversion of the fracture density of the deep coal bed.

The invention is suitable for the technical field of oil and gas resource exploration, and provides a tight sandstone gas reservoir microfracture prediction method based on elastic modulus frequency dispersion inversion. According to the method, a rock physical model is constructed based on an equivalent embedded body stress averaging theory, frequency dispersion attributes are defined through elasticity modulus differences in a non-relaxed state and a relaxed state, and a microfracture parameter influence mechanism is disclosed; inversion is driven by a non-relaxed state model, the calculated elastic modulus frequency dispersion attribute and the microfracture density are in significant positive correlation, the quantitative correlation of the two is verified through measured data, and the inversion precision of the microfracture characteristics in the well is improved; an L-BFGS algorithm is introduced to carry out seismic inversion, frequency dispersion attribute quantitative prediction of pre-stack seismic data is realized, physical consistency between logging and seismic data is ensured, traditional limitation is broken through, a micro-fracture development area of a gas production well target layer is successfully identified in practical application, and the method has a good application prospect. And an effective solution is provided for high-precision prediction of the regional scale of the compact sandstone gas reservoir microcracks.

The invention discloses a stochastic finite fault source model establishment method, which comprises the following steps of S1, determining a geometrical shape of a seismic fault based on regional geological data and seismic monitoring data, and estimating a non-planar fault parameter and a fault plane average sliding amount in combination with historical data and an empirical formula; s2, estimating distribution and sliding strength of concave-convex bodies and obstacles on the fault surface according to historical seismic inversion data, and obtaining the sliding amount of each sub-fault by randomly disturbing the average sliding amount; s3, the discrete fault plane serves as a sub-fault unit, and after an initial fracture point and the average fracture speed are determined, random fracture initial time conforming to normal or power law distribution is generated based on a random number method; s4, calculating the seismic oscillation time history of each sub-fault by adopting a random point source method, superposing contributions, introducing the influence of a shallow velocity structure V30, and generating a three-dimensional seismic oscillation field; and S5, comparing actual strong earthquake record adjustment parameters, and outputting a multi-risk-level earthquake motion parameter evaluation result after iterative optimization. According to the method, by fusing randomness and empirical data, the simulation precision of the seismic source model on the uncertainty of the seismic process is improved, the influence of the potential maximum-magnitude earthquake possibly occurring in the active fault zone in the future can be effectively estimated, the seismic oscillation simulation precision and the calculation efficiency can be improved, and the method is suitable for engineering structure aseismic design and seismic disaster evaluation.

The invention relates to the technical field of seismic inversion, and particularly discloses a variational reasoning full-waveform inversion method and device based on geological prior information, and the method comprises the steps: constructing a plurality of filters; acting the plurality of filters obtained by construction on a seismic migration section to calculate a correlation coefficient matrix; according to a logging information fitting theory variation function, performing low-rank approximation on the calculated correlation coefficient matrix to obtain a correlation coefficient matrix after low-rank approximation; randomly generating a plurality of speed samples based on the correlation coefficient matrix after low-rank approximation; calculating the gradient of the objective function according to the plurality of speed samples; according to the gradient of the objective function, calculating the gradient of posteriori distribution by using a Bayesian formula; and based on the gradient of the full waveform inversion posteriori distribution, utilizing a Stein variational gradient descent algorithm to carry out multiple times of iterative updating on the plurality of speed samples, and outputting a target speed model obtained by inversion of the plurality of speed samples. According to the scheme, the multiplicity of inversion is reduced, and the inversion efficiency is improved.

The invention discloses a construction-constrained depth-domain multi-channel collaborative seismic inversion method and system, and the method comprises the steps: firstly constructing a depth-domain wavelet matrix, generating a synthetic record consistent with an actual seismic feature in combination with an impedance model, and constructing a pre-training data set; gaussian noise is superposed on the synthetic data, and layer dislocation is simulated; then, a plane wave decomposition method is adopted to extract construction inclination angle information from the enhanced data, and a transverse space constraint relation is established; embedding and constructing an inclination angle constraint term in the space-time neural network, and training a multi-channel collaborative inversion model through synthetic data; extracting inclination angle data of a real seismic record, fusing logging and horizon interpretation results, and establishing a depth domain low-frequency initial impedance model; and finally, actually measured seismic data, construction constraint information, an initial model and well data are combined, network parameters are adjusted through transfer learning, and finally high-precision and high-stability impedance inversion is achieved. The problems of insufficient result stability, low resolution, error accumulation effect and the like in the existing seismic inversion method are solved.

The invention relates to the technical field of seismic exploration, and provides a five-dimensional seismic data prediction method and device. The method comprises the following steps: carrying out inclination angle imaging enhancement processing on five-dimensional seismic data; carrying out azimuth time window analysis based on the inclination angle imaging data, and calculating coherent attributes; carrying out gradient mode attributes on the basis of coherent attributes, and carrying out orientation attribute fusion; five-dimensional phase control step-by-step inversion is carried out under fusion attribute constraint; and predicting an oil and gas reservoir of the fractured volcanic rock based on an inversion result. According to the method, the fractured oil and gas reservoir is predicted based on the five-dimensional seismic data, interrelation between adjacent seismic traces is considered, and underground medium parameters are accurately obtained in combination with seismic sensitive attributes and a multi-trace inversion method, so that the problems that single attribute prediction is high in multiplicity of solutions and space description of a fracture system is not comprehensive enough are solved, and the prediction accuracy of the fractured oil and gas reservoir is improved. And meanwhile, the seismic inversion stability and continuity are improved, and high-precision fractured reservoir prediction is realized.

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

The invention provides a pre-stack seismic inversion method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining multiple pre-stack seismic angle stack data, target layer position interpretation data and logging data; synthetic record calibration is carried out to obtain synthetic record calibration data and seismic wavelets corresponding to each piece of pre-stack seismic angle superposition data, and a seismic wavelet matrix is constructed; based on the seismic wavelet matrix, calculating to obtain a time domain positive operator; based on the frequency spectrum of each seismic wavelet, calculating to obtain a frequency domain positive operator; according to the pre-stack seismic angle superposition data, correlation parameters are obtained through calculation; and constructing a target function, and determining a pre-stack seismic inversion result at least according to the correlation parameters, the time domain forward operator, the frequency domain forward operator, the pre-stack seismic angle superposition data and the target layer position interpretation data. Based on the technical scheme of the invention, the longitudinal resolution and the transverse resolution of the elastic parameter inversion can be improved.

The invention relates to the field of oil and gas field exploration and development, in particular to a fracture-cavity type reservoir mechanical parameter seismic inversion method based on logging ground stress constraint. On the basis of array acoustic logging, the current crustal stress is calculated; inverting different types of seismic attributes based on the pre-stack seismic data; by optimizing the seismic attribute and the threshold value, the geometric shape carving of the fracture-cavity body is realized; based on the fracture-cavity body seismic attribute sensitivity degree, different types of fracture-cavity body seismic recognition standards are established; establishing rock mechanical parameter assignment models of different types of fractured-vuggy bodies through rock mechanical parameter inversion cycle verification; and considering stress constraint to optimize different types of fracture-vug body rock mechanical parameter assignment models, and finally realizing fracture-vug type reservoir three-dimensional rock mechanical parameter inversion. The invention provides a fracture-vug reservoir mechanical parameter seismic inversion method based on logging ground stress constraint. The method has reference value in multiple aspects of fracture-vug reservoir geomechanical modeling, ground stress field numerical simulation, engineering dessert evaluation and the like.

The invention relates to the field of oil and gas geophysical exploration, and particularly discloses a reservoir physical property parameter seismic inversion evaluation method and device, and the method comprises the steps: building a rock physical model based on the geological features of a work area reservoir; based on the rock physical model, sequentially carrying out inversion test on seismic traces beside a modeling well, a non-modeling well and all wells in a work area to determine parameters of the rock physical model and an inversion algorithm; utilizing the rock physical model and an inversion algorithm to perform seismic inversion on the physical property parameters of the work area reservoir to obtain an inversion result; and extracting a work area well connection profile and reservoir section plane attributes from the inversion result, and then performing analysis. According to the reservoir physical property parameter seismic inversion evaluation method, on the basis of problems needing to be noticed in the reservoir physical property parameter seismic inversion process of the rock physical model and the quality control mode, the trial and error processes in the technical inversion process can be reduced, the working efficiency of reservoir physical property inversion is improved, and the technical practicability is improved.

A method for determining a seismic inversion volume of a subsurface. The method includes obtaining seismic data of subsurface that includes multiple wells, generating an inverted seismic volume based on the seismic data, and obtaining wellbore measurement data from multiple wells in the subsurface. The method further includes determining residual values representing a difference between values of the wellbore measurement data and the inverted seismic volume data at each of the wellbore sites, generating residual volume data by transforming the residual values, the transforming comprising an interpolation of the residual values between each of the wellbore sites using an inverse distance squared function, and generating corrected seismic volume data based on a difference between values of the residual seismic volume data and the inverted seismic volume data.

The invention discloses a method and a device for inverting a high-order frequency dispersion curve of a seafloor node Schelt wave. The method comprises the following steps: determining the distance between reference points according to seismic data arrangement information, and setting a plurality of reference points on a target section where a seismic survey line is located; according to the maximum offset distance and the minimum offset distance, common receiving point sub-gathers are screened from a common receiving point Schelt channel set of each seabed node, sub-gathers are intercepted from the common receiving point sub-gathers according to the reference point position information and the maximum distance, and the sub-gathers with the length not smaller than the minimum length form the gathers of the reference points; determining a frequency dispersion energy spectrum of each sub-gather in the reference point gather to obtain a superposed frequency dispersion energy spectrum of the reference point; and picking up a high-order frequency dispersion curve by superposing a frequency dispersion energy spectrum, and carrying out seismic inversion modeling. According to the method, through screening of available trace gathers of reference points and determination and superposition of frequency dispersion energy spectrums, an energy-enhanced superposed frequency dispersion energy spectrum is obtained, so that high-resolution seismic modeling can be realized based on extracted high-order frequency dispersion curve inversion.

The invention discloses a seismic exploration method based on drilling information structure constraint, which comprises the following steps of: stopping drilling at any time to excite seismic waves in a drilling process by adopting a seismic source while drilling, and continuously changing the position of the seismic source in the drilling process so as to acquire seismic wave data in a plurality of time periods; carrying out independent inversion imaging by using conventional seismic inversion in a first serial number acquisition time period, and carrying out time-shifting seismic source data inversion imaging of borehole information structure constraint in a subsequent moment, namely introducing an inversion result of a previous time period and the structure constraint of borehole information up to a current acquisition time period into a traditional seismic inversion objective function; according to the method, the difference of the next time period is effectively regulated and controlled, so that the resolution of structural constraint inversion is higher, the change condition of abnormal body exposure in the drilling process is accurately captured, the abnormal body in the detection range can be effectively distinguished finally, mutual verification of drilling and geophysical prospecting data is realized, and accurate detection of a drilling detection area is realized.

The invention is suitable for the technical field of geophysical exploration, and provides a rock physics-driven time-frequency domain longitudinal wave velocity dispersion attribute prediction method, which comprises the following steps of: establishing a rock physics model; under the driving of the rock physical model, inverting the porosity of the microfractures in the well, calculating the skeleton elastic modulus of the rock containing the fractures, and predicting a frequency-dependent longitudinal wave velocity logging curve; constructing a time-frequency domain longitudinal wave velocity seismic inversion initial model; constructing a TF-AVO theoretical formula, developing a time-frequency domain longitudinal wave velocity seismic inversion method based on an L-BFGS algorithm, and performing longitudinal wave velocity inversion by taking the initial model as prior information; analyzing the relative change of the frequency-varying longitudinal wave speed under different frequencies, and quantitatively predicting the frequency dispersion attribute of the longitudinal wave speed; and on the basis of logging data, calibrating a longitudinal wave velocity dispersion attribute prediction result, and carrying out reservoir oil and gas detection. The method has higher precision and resolution, the stability and reliability of longitudinal wave velocity dispersion attribute prediction are remarkably improved, and the dependence on strong amplitude response is overcome.

The invention discloses an earthquake brine reservoir response feature recognition method based on deep learning, which breaks through the technical limitation of weak response of traditional acoustic logging to brine reservoir features by fusing induction logging data and an earthquake inversion result, and improves the accuracy of reservoir recognition. The improved UNET + + network structure effectively integrates multi-scale geologic features by using dense jump connection and a channel attention mechanism, enhances the capture ability of thin-layer brine weak reflection signals, and improves the accuracy of boundary recognition; a bidirectional LSTM and spatial feature alignment technology is introduced, deep fusion of logging vertical features and a seismic transverse section is realized, a horizon matching relation is optimized, and the risk of misjudgment caused by abnormal speed is effectively reduced; based on a depth supervision mechanism and a joint training strategy, a three-dimensional reservoir space distribution model is generated, depiction of a deep pore-fissure type brine reservoir is achieved, exploration efficiency is greatly improved, and reliable technical support is provided for brine resource positioning under complex geological conditions.

The invention relates to the technical field of earthquake prediction, in particular to an earthquake continuous monitoring and predicting system which comprises the following steps: S1, a data center receives a real-time signal transmitted by an earthquake monitoring beacon and acquires multi-dimensional physical information of stratum change; s2, the data processing center carries out noise reduction preprocessing on the information; and S3, gridding the multi-beacon signal, and carrying out cross calculation to determine an underground vibration signal source point and a corresponding geological fluid mode. According to the invention, through building the inversion model and carrying out inversion verification by using the collected seismic wave signals, finer geological structure information can be obtained. The earthquake prediction system performs earthquake rehearsal according to the earthquake inversion model, and early warns the occurrence of an earthquake by monitoring characteristic signals extracted from the earthquake rehearsal, so as to provide more accurate warning information for people and provide support for rescue work after the occurrence of the earthquake.

Systems and methods for predicting reservoir properties in a subsurface formation include accessing, from a data store, seismic inversion data and well log data for the subsurface formation. A training dataset is generated including data extracted from the seismic inversion data based on locations of wells in the subsurface formation and the well log data from the wells. The training dataset includes, for a set of wells in the subsurface, seismic inversion data with corresponding labeled data representing total porosity values and electro-facies values. A neural network is trained based on the training dataset, and porosity values for the reservoir are predicted based on the seismic inversion data and the trained neural network.

The invention relates to the technical field of seismic exploration, and relates to an oil and gas seismic impedance inversion method, in particular to a space-time correlation adaptive MCMC wave impedance inversion method. According to the method, the problems of instability, low calculation efficiency, high multiplicity of solutions and insufficient uncertainty quantization of a traditional random inversion method in the prior art are solved. The method comprises the following steps: constructing a space-time correlation covariance matrix; constructing a target function of the fitting degree; performing iterative inversion; and post-processing an inversion result. According to the method, an inversion strategy based on a Bayesian framework is adopted, space-time correlation covariance is constructed as a prior constraint, spatial correlation and stratum vertical continuity describing impedance parameters are displayed, a physical model is combined to ensure that a prediction result meets the matching performance of observed seismic data, meanwhile, deep fusion with a delay rejection self-adaptive MCMC algorithm is carried out, and the prediction accuracy is improved. And collaborative innovation of physical model constraint and statistical optimization in seismic wave impedance inversion is realized. And the requirement of high-precision seismic inversion is met.

The invention provides a crack attribute seismic inversion method and system based on model-data dual drive, and relates to the technical field of seismic reservoir identification, and the method comprises the steps: obtaining pre-stack seismic data; inputting the pre-stack seismic data into the model-data dual-drive fracture attribute inversion network, and performing fracture weakness parameter inversion to obtain a prediction result of a fracture weakness parameter; the model-data dual-drive fracture attribute inversion network takes pre-stack seismic data as the input of the inversion network, and introduces an initial model as an inversion constraint; seismic features are obtained by using the pre-stack seismic data; initial model features are obtained through the initial model, the seismic features and the initial model features are fused, and fracture parameter predicted values are obtained; and inputting the predicted value into a forward model for forward simulation to obtain a synthetic azimuth seismic record difference value, introducing the synthetic azimuth seismic record difference value into a consistency loss function, and performing parameter updating on an inversion network to obtain a final model-data dual-drive fracture attribute inversion network.

A method implements seismic inversion using quantum computing. The method includes encoding a first objective function and trace values as a first Ising model Hamiltonian, annealing the first Ising model Hamiltonian to obtain a first result, and decoding the first result to output reflectivity values. The method further includes encoding a second objective function and the reflectivity values as a second Ising model Hamiltonian, annealing the second Ising model Hamiltonian to obtain a second result, and decoding the second result to output acoustic impedance values.

The invention provides a seismic inversion method based on horizontal well information explicit constraint and a related device. The method comprises the following steps: calculating corresponding wave impedance data by acquiring longitudinal wave velocity curve and density curve data of a whole well section of a horizontal well in a target work area; generating a synthetic seismic record according to the longitudinal wave impedance data corresponding to the vertical well section and the longitudinal wave impedance data corresponding to the inclined well section, and performing well-seismic calibration to obtain a well-seismic calibration result; establishing a logging response forward modeling equation set by combining the wave impedance data; establishing a seismic response forward equation set according to the convolution theoretical model; forming a well-seismic combined vertical wave impedance forward modeling equation set by combining the two equation sets; constructing a low-frequency longitudinal wave impedance model according to the well seismic calibration result, the wave impedance data and preset seismic horizon interpretation; performing seismic inversion on the well-seismic combined vertical wave impedance forward equation set and the low-frequency longitudinal wave impedance model by using a Bayesian inversion theory to obtain a wave impedance inversion solution; therefore, the accuracy of seismic inversion is improved.

The invention discloses a multi-well consistency correction method, system and equipment based on Warisstein distance, and relates to the field of oil and gas field exploration and development, and the method comprises the steps: constructing an equal-width histogram of a standard well based on a logging curve of the standard well; according to the equal-width histogram of the standard well and the logging curves of the multiple to-be-corrected wells, on the basis of an empirical distribution function method, with the minimum Warisstein distance between each to-be-corrected well and the standard well as the target, an annealing algorithm is adopted to conduct iterative optimization on parameters of the consistency mapping function, and optimal parameters corresponding to each to-be-corrected well are obtained; inputting a consistency mapping function to obtain an optimal matching correction model corresponding to each well to be corrected; and inputting the logging curve of each to-be-corrected well into the corresponding optimal matching correction model to obtain a corrected logging curve of each to-be-corrected well, and completing multi-well consistency correction. According to the method, the accuracy of the corrected logging curve can be improved, so that a solid data foundation is laid for subsequent seismic inversion and reservoir prediction.

The present invention relates to a method, device, medium and equipment for high-resolution seismic inversion of thin-layer structures. The method comprises the following steps: constructing a thin interbedded sand body model, forward-synthesizing seismic records based on the thin interbedded sand body model to obtain seismic traces s; forming training data from the seismic traces s and impedance data z to prepare a training set {s, z} T and validation set {s,z} V ; The training set is used to train a neural network model, and the validation set is used to validate the neural network model; the neural network model is used to obtain predicted impedance, and the predicted impedance is converted into a reflection coefficient sequence; the reflection coefficient sequence is convolved with the forward wavelet to generate a seismic record, and the generated seismic record and the input seismic trace set constitute a supervisory term constraint model to drive the inversion process.

The invention discloses a geosteering method for a low-permeability sandstone reservoir gas horizontal well, and belongs to the technical field of oil and gas development. The invention discloses a geosteering method for a low-permeability sandstone reservoir gas horizontal well. The geosteering method comprises the following steps: designing an initial trajectory based on seismic inversion and adjacent well data; gR, RT, DT and CNL data while drilling are collected in real time; space-time calibration is implemented through a deep matching algorithm, and quality control is performed by using multi-parameter cross validation; calculating a reservoir matching degree index SMI based on a geological rule and a machine learning model, and generating an adjustment suggestion when the SMI is lower than a threshold value; verifying feasibility by combining drilling engineering constraints, and dynamically optimizing the trajectory by taking a high-quality reservoir contact rate greater than or equal to 90% as a target; and after drilling is completed, the reservoir drilling encounter rate is quantitatively analyzed. According to the method, multi-source data accurate fusion and intelligent trajectory adjustment are achieved, the problem of low-permeability sandstone reservoir trajectory control is solved, and the drilling efficiency and the recovery efficiency are improved.