97 results about "Seismic interpretation" patented technology

The present application belongs to the technical field of geophysical well logging data processing, and particularly relates to a multi-scale dual-branch neural network well logging curve reconstruction method based on seismic constraint, which comprises reading in well-seismic and interpreted horizon data, target interval sublayering and facies belt division based on three-dimensional seismic interpretation, pyramid multi-scale training set sample construction by fusing multi-curve and well flanking seismic trace information, residual-Transformer dual-branch neural network training model establishment taking a composite loss function as the core, three-stage progressive training strategy and reconstruction of target well missing section and result evaluation. The method still maintains high stability and robustness under the condition of complex heterogeneous reservoirs; on the basis of seismic data constraint, geological sublayering and facies belt division and other interpretation information are fused, so that the reconstruction result is more in line with geological laws; and the obtained reconstructed curve provides reliable support for re-interpretation of old data and full use of incomplete well logging data.

The invention discloses a seismic image super-resolution reconstruction method based on a double-branch multiple attention network, and belongs to the technical field of seismic exploration, and the method comprises the steps: constructing a data sample library for model training; adopting a super-resolution backbone network and a gradient branch auxiliary network to construct a double-branch multiple attention network model; and training the double-branch multiple attention network model by adopting the data sample library and the mixed loss function to obtain a network model for realizing seismic image super-resolution reconstruction and high-frequency texture information reconstruction, and performing reconstruction based on the trained network model to obtain a seismic image subjected to super-resolution reconstruction. According to the method, a gradient branch is introduced as an auxiliary network, so that the super-resolution reconstruction effect is enhanced. Meanwhile, a mixed loss function is adopted to train the network, and a loss function for constraining high-frequency information is particularly introduced, so that the common structural deformation problem in a super-resolution task is effectively solved, the generation of artifacts is prevented, and a new technical approach is provided for high-precision seismic interpretation.

A method for the time-depth conversion of a concealed structure in a foreland thrust belt with a low exploration degree. The method comprises: obtaining velocity variation characteristics of a study area; using seismically interpreted horizons and fault data in a time domain to establish a geological structure model; by means of a stratigraphically controlled and fault-block-division-based velocity assignment method, converting the geological structure model into an interval velocity model; establishing virtual well control points in the study area, and extracting from the interval velocity model an interval velocity curve at each virtual well control point (S400); converting the interval velocity curve at each virtual well control point into an average velocity curve (S500); using a stratigraphically controlled and fault-block-division-based virtual well control point spatial interpolation method to construct a three-dimensional average velocity volume; and performing time-depth conversion on target horizons. Further provided is an apparatus for the time-depth conversion of a concealed structure in a foreland thrust belt with a low exploration degree. By means of an obtained depth-domain structural map, the identification of a concealed structure in a foreland thrust belt with a low exploration degree can be realized, thereby providing reliable depth data for the detailed description of traps.

A method for estimating higher-order dependencies from input data includes receiving input data. The method also includes generating multi-tapered spectral estimates based upon input data. The method also includes determining dependencies based at least partially upon the multi-tapered spectral estimates. The method also includes building or updating a deep learning foundation model to employ the dependencies.

The invention provides a well control constrained seismic data frequency expanding method based on broadband wavelets, and the method comprises the steps: S1, determining the feasibility of frequency expanding through the analysis of an amplitude spectrum and a signal-to-noise ratio spectrum of original seismic data in combination with the drilling condition of an actual work area; s2, performing high-frequency seismic forward modeling on the geologic model of the multi-well target sand body to determine a wavelet dominant frequency capable of identifying the target sand body; and obtaining three-dimensional matching factor data according to the wavelet dominant frequency and completing data frequency expansion processing with the constructed broadband wavelet. The spatial matching factor library can be obtained by fully utilizing broadband information of well data in an actual work area and existing mature geological knowledge, wavelet side lobes are further suppressed through amplitude envelope, broadband wavelets are constructed, dominant frequency improvement and frequency band expansion of seismic data are achieved, and the requirements of seismic fine interpretation are met.

The invention belongs to the technical field of geophysical logging data processing, and particularly relates to a multi-scale double-branch neural network logging curve reconstruction method based on seismic constraints. Comprising the steps of reading in well seismic and interpreting horizon data, performing target layer section layering and phase belt division based on three-dimensional seismic interpretation, fusing multiple curves and well-side seismic channel information to construct a pyramid multi-scale training set sample, establishing a residual-Transformer double-branch neural network training model by taking a composite loss function as a core, and constructing a multi-scale training set sample based on the residual-Transformer double-branch neural network training model. And a three-stage progressive training strategy is adopted, and target well missing section reconstruction and result evaluation are carried out. According to the method, high stability and robustness are still kept under the condition of a complex heterogeneous reservoir; interpretation information such as geological layering and phase belt division is fused on the basis of seismic data constraints, so that a reconstruction result better conforms to geological laws; and the obtained reconstruction curve provides reliable support for re-explanation of old data and full utilization of incomplete logging data.

The invention provides a seismic data bidirectional frequency band expansion method based on carrier modulation, which relates to the field of seismic exploration, and comprises the following steps: processing original seismic data through time window segmentation, calculating an autocorrelation function and carrying out time domain continuation; solving a prediction coefficient based on entropy maximization constraint to generate an amplitude spectrum; calculating a boundary attenuation rate through boundary frequency point positioning; constructing an attenuation compensation function to generate a frequency domain carrier function; applying sparse constraint to solve a weighting factor and iteratively calculating a modulation amplitude spectrum; and finally, carrying out combined inverse transformation with an original phase spectrum to obtain expanded data. According to the method, the resolution and the signal-to-noise ratio of the seismic data are effectively improved, and the seismic interpretation precision is improved.

The invention belongs to the technical field of geologic structure interpretation and modeling, and particularly relates to a multi-data fusion seismic interpretation and geologic modeling method for a complex structural zone. The invention discloses a multi-data fusion seismic interpretation and geologic modeling method for a complex tectonic zone. The method comprises the following steps: observing and judging formation and fault development characteristics in a work area through an earth surface outcrop fault; interpreting a stratigraphic dip angle by adopting imaging logging to identify a fault; using 3D-VSP data to enhance seismic imaging and identify faults; a low-angle fault is recognized through conventional logging interpretation; identifying a velocity abrupt change interface by adopting a seismic velocity spectrum to determine a fault; through fault comprehensive judgment identified by different data and methods, the fault position is determined, and a geological structure mode of a research work area is constructed. According to the method, through fusion interpretation, fault position identification, seismic interpretation and geologic structure modeling of various data such as outcrop, logging data, seismic data and velocity field, the accuracy of geologic structure modeling can be improved, the success rate of oil-gas exploration is improved, and meanwhile, the cost is saved.

A system and method in accordance with the present disclosure include a workflow applied to identify areas of confidence in seismic interpretations that meets a pre-selected threshold by utilizing machine-learning (ML) techniques. The ML techniques enable one or more filters to be applied, based on a range of confidence values, to areas of seismic interpretation both in the vicinity of the faults but also away from fault locations. The contribution of the various inputs is evaluated and weighted by the ML model, which reduces the time to prepare input seismic interpretation data and to obtain results from executing the model.

The present application relates to the technical field of rock lithology exploration, and more particularly to a dolomite lithology prediction method, system and device; comprising the following steps: S1, obtaining drilled well data and seismic data of a region to be identified; S2, performing standardization processing; S3, performing well control feature frequency extraction; S4, performing fine production of a synthetic record for the region to be identified; S5, determining a seismic interpretation mode scheme for the region to be identified; S6, determining dolomite attributes; S7, obtaining a first content of dolomite in the region to be identified; S8, determining a second content of dolomite in the region to be identified; S9, determining whether the dolomite attributes determined in the step S7 are qualified according to the first content of dolomite and the second content of dolomite; and quantitatively predicting the content of dolomite in a carbonate rock formation.

This invention relates to a method, apparatus, migration method, device, and medium for establishing an anisotropic parameter field. The method includes: obtaining the thickness of the target logging layer at each well point based on well logging layer information; obtaining the thickness of the target seismic interpretation layer corresponding to the well point based on seismic interpretation layer information; calculating the thickness factor of the well point at the target logging layer based on the thickness of the target seismic interpretation layer and the thickness of the target logging layer; and correcting the target logging layer based on the thickness factor of each well point and the thickness of the target seismic interpretation layer to obtain the corrected target logging layer, thereby establishing an anisotropic parameter field. In this embodiment, by constraining the logging layers between well points under the lateral trend of the seismic interpretation layer, the difference between the established anisotropic parameter field and the anisotropic parameter field of the actual subsurface medium is reduced.

The application discloses a multi-azimuth post-stack seismic attribute interpretation method, device, medium and equipment, and the method comprises the following steps: acquiring a target layer seismic interpretation horizon and a plurality of azimuth seismic attribute data bodies; setting a window used for calculating eigenvalues; selecting an eigenvalue; for the selected eigenvalue, in the window, based on the plurality of azimuth seismic attribute data bodies, attribute optimal eigenvalues of each position point in the plurality of azimuth seismic attribute data body spaces are obtained; based on the attribute optimal eigenvalues of each position point, an eigenvalue data body is obtained; and an attribute plan view is extracted in the eigenvalue data body along the target layer seismic interpretation horizon. The application acquires the most representative attribute advantage eigenvalues in different azimuths, and constructs a new data body from the eigenvalues, so that the purpose of highlighting the geological abnormal response characteristics and reducing the dimension interpretation is achieved, and the efficiency and precision of the post-stack multi-azimuth seismic interpretation are effectively improved.

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.

Systems and methods include a computer-implemented method for presenting an interpretation result of synchronized seismic data and fracturing treatment time. A standard format seismic data set of sensor readings obtained from three-component sensors is generated. Coordinates and recording times corresponding to the sensor readings are added to the standard format seismic data set. Synchronized seismic data is generated from the standard format seismic data set by synchronizing the seismic recording times with the fracturing treatment time. Quality-controlled synchronized seismic data is generated by removing dead traces and abnormal data samples from the synchronized seismic data. A time-frequency analysis is performed on the quality-controlled synchronized seismic data, including performing a short-time Fourier transform to analyze changes in Fourier spectra over time. Based on the time-frequency analysis, a resonance frequency is extracted from each spectrum at different time samples. An interpretation result based on the resonance frequency is presented to a user.

The invention provides a fracture prediction method and device for a shale reservoir. The method comprises the following steps: acquiring a seismic interpretation result of a target shale reservoir; applying a geochemical test analysis method and the seismic interpretation result to determine a key fracture forming period corresponding to the target shale reservoir, and tectonic deformation historical information and rock mechanical parameters of the key fracture forming period; according to the geologic model and rock mechanical parameters of the target shale reservoir in the key fracture forming period, constructing a geomechanical model of the key fracture forming period; and according to the geomechanical model of the key fracture forming period, tectonic deformation historical information and a preset superposition calculation model, fracture parameters of the target shale reservoir in the key fracture forming period are obtained through prediction. According to the invention, the accuracy of crack prediction of the shale reservoir can be improved.

This invention relates to a method for constructing a three-dimensional formation velocity model, belonging to the field of three-dimensional seismic interpretation technology. First, this invention utilizes seismic data from the target area and the time-depth relationship of the pilot sections of vertical and horizontal wells to establish a well-seismic fusion three-dimensional velocity model. Then, based on the lithology encountered in the horizontal section, sonic logging curves, and the fitting relationship between sonic logging and lithology, the layer velocity at the horizontal section of the target layer in the target area is determined. This layer velocity is then interpolated and smoothed to obtain a horizontal section layer velocity model. Finally, this horizontal section layer velocity model is used to constrain the well-seismic fusion three-dimensional velocity model, resulting in the corresponding three-dimensional formation velocity model of this invention. This invention utilizes well logging information from the horizontal sections of horizontal wells to constrain and correct the three-dimensional velocity model, which not only improves the accuracy and stability of the lateral variations in the three-dimensional velocity model but also enhances the accuracy of low-amplitude structural interpretation.

The present application relates to the technical field of oilfield exploration and development, and particularly relates to a method for predicting the distribution range of deep-water turbidite sand bodies. The method comprises the following steps: using three-dimensional seismic data, actual drilling well data and velocity data to calculate the maximum thickness of the sedimentary sand body of the upthrown wall of the fault which provides the source for the turbidite sand body; calculating the fault throw according to the development form of the three-dimensional seismic interpretation fault in the work area, and comprehensively considering the seismic, velocity and well data; determining the dip angle of the downthrown wall stratum through the two-dimensional seismic profile perpendicular to the fault strike; based on the drilling and logging data, according to the thickness of the deep-water turbidite sand body in the higher exploration degree area of the research area and the critical value of the deep-water turbidite sand body, drawing the sand body thickness contour map of the research area, so as to determine the distribution range of the deep-water turbidite sand body in the higher exploration degree area. The method is suitable for accurately predicting the distribution range of the deep-water turbidite sand body in the faulted basin.

The application discloses a method and device for identifying a seismic horizon and a storage medium, and belongs to the technical field of seismic interpretation. The method comprises the following steps: acquiring a seismic data body and a multi-target horizon identification sample set seismic data body, and using the multi-target horizon identification sample set seismic data body to generate a sample seismic profile W r The multi-target horizon identification sample set comprises artificial interpretation seismic horizons obtained after marking and processing the sample seismic profile W r , and at least four auxiliary seismic horizons related to the artificial interpretation seismic horizons; a convolutional neural network is trained according to the sample seismic profile W r and the multi-target horizon identification sample set, and a multi-target horizon identification network Net L is obtained; a to-be-identified seismic profile is substituted into the multi-target horizon identification network Net L , and a transition seismic horizon and at least four auxiliary seismic horizons related to the transition seismic horizon are obtained, and then a target seismic horizon is determined through fusion processing. The method can accurately identify the seismic horizon and improve the accuracy of seismic interpretation.

The present application relates to a kind of low-order fault seismic interpretation method.Seismic interpretation method includes: obtaining the time-depth conversion relationship of target area;According to the time-depth conversion relationship, the seismic profile of target area is converted;According to more than three small breakpoint information or two more fault trace lines on the seismic profile not on a straight line, low-order fault is constrained seismic interpretation;The mode of small breakpoint information or fault trace line of target area is B mode or A+B mode, A mode is: if there is well drilling small breakpoint in target area, well drilling small breakpoint is corresponded with seismic phase one by one;B mode is: in seismic interpretation software, change the polarity of sandstone to corresponding negative polarity, and reduce the intensity of seismic polarity, obtain small breakpoint information or fault trace line.The present application only needs to find out small breakpoint or fault trace line by changing software setting in interpretation process, and low-order fault can be accurately interpreted, which is simple and reliable.

The invention discloses a depth domain seismic three-dimensional sedimentary evolution horizontal well steering while drilling method, and belongs to the technical field of petroleum and natural gas exploration and development. A time domain seismic data body and various inversion data bodies of a certain stratum section are converted into a depth domain data body, reservoir three-dimensional space sedimentary evolution is carried out by utilizing the depth domain seismic data and the inversion data bodies, and the depth domain seismic data and the inversion data bodies are analyzed according to the structural form of a depth domain target layer and the reservoir plane evolution law. And horizontal well multi-target true depth and true dip angle design and while-drilling tracking guiding are directly carried out on a depth domain plane and a section. According to the method, the multi-target true depth and true dip angle design is directly carried out on the seismic plane section in the same depth domain of seismic guidance and while drilling; well drilling information is seamlessly connected with an earthquake, and three-dimensional while-drilling tracking and guiding are carried out on the earthquake in real time. And the drilling rate of the horizontal well reaches more than 80%.

The invention belongs to the technical field of reservoir geological modeling, and provides a clastic rock oil and gas reservoir key interface characterization modeling method, device, equipment and medium, and the method comprises the steps: constructing a geological modeling basic database; key interface identification and representation are carried out based on the constructed geological modeling basic database; constructing a construction model based on the recognition and representation results of the key interface, the seismic data volume and the well data; checking whether a geological interface in the tectonic model is consistent with well data and seismic interpretation, and if not, optimizing the tectonic model; based on the sedimentary microfacies data, a deterministic assignment method is adopted to construct a sedimentary microfacies model; based on the sedimentary microfacies model, a sequential indication method is adopted for simulation, and a lithologic model is constructed; constructing an attribute model based on the lithologic model; according to the method, the structure model is optimized, so that the structure model restores the structure characteristics as much as possible, and reliable spatial constraints are provided for coarsening and modeling of attributes such as lithology, porosity, permeability and saturation.

The application discloses a new high-precision three-dimensional velocity field establishment method for horizontal well deployment area, which comprises the following steps: firstly, determining two or more oil layer group level seismic standard layers near a target layer; secondly, establishing a reasonable constraint framework model in the vertical direction; thirdly, calibrating a velocity spectrum by using a fitting relationship; fourthly, establishing an initial three-dimensional velocity model; fifthly, performing filtering processing on the velocity curve of each well by using a geological mode constraint, so as to obtain a smoothed velocity curve capable of reflecting reservoir changes; sixthly, training the model by using a multi-layer feedforward neural network intelligent algorithm; seventhly, applying the training result of the model to the initial three-dimensional velocity model; and eighthly, obtaining a high-precision three-dimensional velocity field. The method fully applies various information such as well time-depth relationship, three-dimensional velocity spectrum, seismic interpretation results and the like, reduces the error between the depth domain result and the well by means of pseudo well velocity analysis, velocity curve filtering and artificial intelligence algorithm fusion, and thus the accuracy of velocity establishment for the horizontal well area is improved.

The invention relates to a karst ancient landform detail drawing compilation method and device, equipment, a storage medium and a computer program. The method comprises the following steps: determining ancient landform categories contained in a region according to a geological background; according to the unconformity development characteristics, the upper stratum thickness and the lower stratum thickness of the karst unconformity surface are determined, and the thickness ratio of the upper stratum to the lower stratum at all drilling positions in the area and the ancient landform type at each drilling position are determined; determining a thickness ratio interval corresponding to each ancient landform type according to a thickness ratio between the upper stratum and the lower stratum at all drilling positions; performing tracking interpretation on the karst unconformity surface according to the seismic data so as to determine a weathering crust of a seismic interpretation layer and a ratio distribution diagram between the upper stratum thickness and the lower stratum thickness of the weathering crust; and determining a karst ancient landform detail drawing according to the ratio distribution diagram of the calibrated drilling position and the thickness ratio interval. The ancient landform is finely depicted in a well-seismic combination mode, operation is convenient, and efficiency is high.

The present specification relates to the field of oil and gas field exploration and development, and particularly relates to a structure modeling method and device based on horizontal well layering. The method comprises: determining logging characteristics and logging identification marks of a straight well section according to logging data of the straight well section in a study area; determining layer-penetrating point information of a horizontal well according to logging curves of the horizontal well and comparing with the logging characteristics; constructing a well trajectory one section of the horizontal well according to seismic interpretation data and the logging identification marks; extracting corresponding isostatic elevation data of the layer-penetrating point on the well trajectory one section according to the logging identification marks; determining a correction amount according to the elevation of the layer-penetrating point and the isostatic elevation data; and correcting structure surfaces of each small layer according to the correction amount to obtain a structure model. The present scheme solves the problem that it is difficult to establish an accurate, reliable and fine structure model due to the small amount of small layer interface data in structure modeling of an oil and gas reservoir developed mainly by horizontal wells.

The present application relates to the field of seismic interpretation, in particular to a deep seismic reflection structure feature analysis method, device and medium, the method comprises selecting seismic data and determining effective bandwidth data of effective frequency band; different narrow band pass filters are constructed, and structure feature information is scanned to determine the frequency parameters of the structure features; based on the frequency parameters of the structure features and the effective bandwidth data, double constraint calculation is performed on the actual seismic data to obtain a comprehensive structure feature image; noise suppression is performed and seismic reflection structure geological interpretation is performed based on the comprehensive structure feature image. Based on the partial feature frequency scanning technology, combined with the constraint of the double band pass filter, important low frequency information can be retained while fully considering high frequency information, so that the details of the deep seismic reflection structure are more comprehensively reflected. This method can effectively reduce noise interference by accurately selecting the frequency range, and improve the accuracy and reliability of the analysis results.

The application provides a HTI medium elastic parameter and fracture weakness seismic inversion method and system, and comprises the following steps: establishing a seismic forward model based on a longitudinal wave reflection coefficient equation of the HTI medium and a convolution model of a seismic wavelet; according to the fact that a prior distribution of model parameters of the seismic forward model conforms to a Gaussian distribution, analyzing a prior probability distribution function and the seismic forward model by using a Bayesian theory, and then obtaining a posterior probability distribution function of the model parameters; and inversely solving the posterior probability distribution function of the model parameters to obtain the HTI medium elastic parameter and the fracture weakness. In combination with prior information of the model parameters, the uncertainty of an inversion result can be analyzed through the posterior probability distribution, and useful reference information is provided for subsequent seismic interpretation work.

This invention belongs to the field of research on the landward distribution boundaries of natural gas hydrates. It discloses a method and system for studying the fate of methane at the landward distribution boundaries of marine natural gas hydrates, including: seismic interpretation and attribute analysis of present-day BSRs; seismic interpretation and attribute extraction of ancient BSRs to calculate their development depths; calculation of the hydrostatic pressure at the time of the ancient BSRs; simulation and prediction of the ancient BSR positions to determine the location of the landward distribution boundaries of the ancient hydrates; demarcation of the main areas of the study area; identification of whether submarine seepage features are present near the landward distribution boundaries of the hydrates, and interpretation of possible vertical and lateral fluid migration pathways and free gas accumulation; determination of the fate of methane at the boundaries and analysis of the main controlling factors; and calculation of the hydrate decomposition zone volume at the landward distribution boundaries of the hydrates based on the positions of the ancient and present BSRs. This invention identifies multiple types of methane fates at the landward distribution boundaries of marine natural gas hydrates, enabling a correct understanding of the environmental impacts of different methane fates and their effects on hydrate reservoirs.

The application discloses a method for intelligently modeling rock mechanics properties of a tight sandstone reservoir, comprising the following steps: obtaining three-dimensional seismic interpretation data, well logging data and rock mechanics experiment data; establishing a three-dimensional geological structure model of the tight sandstone reservoir which fuses a fault structure; calculating a quantitative fitting relationship between static rock mechanics parameters and a sand ratio; extracting a lithology factor data body from the three-dimensional seismic interpretation data, discriminating the lithology factor data body, generating a three-dimensional spatial distribution of sandstone and mudstone, and thus obtaining a three-dimensional sand ratio distribution model; and based on the three-dimensional sand ratio distribution model and the quantitative fitting relationship, calculating initial values of rock mechanics parameters of each grid unit, and assigning values to the three-dimensional geological structure model and correcting the fault, so as to obtain a final three-dimensional rock mechanics property model. The application realizes multi-source data fusion and quantitative modeling of fault disturbance, and solves the problems of insufficient description of reservoir heterogeneity, lack of physical basis of the model and low reliability of modeling of a fracture zone in the prior art.

The invention discloses a deep coal bed gas containing heterogeneity detection method, a storage medium and equipment. The method comprises the following steps: 1, acquiring post-stack seismic data of a corresponding coal bed gas work area; 2, according to the post-stack seismic data, obtaining a seismic interpretation horizon of a coal seam, and marking the seismic interpretation horizon as T; 3, extracting a plurality of position pairs of post-stack seismic data to obtain a plurality of seismic traces; 4, performing time-frequency analysis on the extracted seismic traces by adopting synchronous extrusion S transformation to obtain a time-frequency distribution diagram; according to the method, the coal seam seismic data is analyzed through synchronous extrusion S transformation, compared with a traditional time-frequency analysis method, the obtained time-frequency analysis result has higher time-frequency resolution and better time-frequency energy focusing performance, in the application of actual seismic data, instantaneous spectrum anomaly characteristics such as high-frequency attenuation related to deep coal reservoirs can be effectively detected, and the method has the advantages of being high in accuracy and high in reliability. The prediction precision of the deep coal reservoir is improved, and the gas-bearing heterogeneity of the deep coal reservoir can be accurately described.

The invention relates to a well-seismic combination recognition method for a mudstone thin interlayer, which comprises the following steps of: establishing an initial model for reflecting structural and sedimentary characteristics by taking a seismic interpretation result as a constraint and combining logging information, and on the basis of the model, indicating a basic process of inversion and a parameter optimization result according to a waveform characteristic; calculating to obtain a target inversion body capable of clearly reflecting the spatial distribution of the reservoir sand shale; after the inversion body is generated, the waveform indication microelectrode inversion body is used as an effective basis for distinguishing sandstone and mudstone, a mudstone interlayer distribution diagram is drawn by combining the known mudstone condition encountered by well drilling, and identification of the mudstone thin interlayer is completed; according to the mudstone thin interlayer recognition method, the mudstone thin interlayer can be qualitatively and quantitatively recognized, and accurate recognition of interlayer type shale oil is achieved.