223 results about "Depositional facies" patented technology

The invention relates to the technical field of reservoir numerical simulation, and discloses a polymer flooding reservoir rapid simulation optimization method considering sedimentary facies constraints, which comprises the following steps: identifying sedimentary facies boundaries according to distribution characteristics of sedimentary facies, and establishing a connected network model considering the sedimentary facies constraints on the basis of the sedimentary facies boundaries, well positions and various sedimentary facies attributes; carrying out one-dimensional grid division on the connected network model, converting the connected network model into a grid connection format of a universal simulator, and solving the connected network model by adopting the universal simulator to obtain pressure and saturation solutions; establishing an automatic historical fitting mathematical model based on sedimentary facies and oil reservoir constraint conditions; the economic net present value is used as an index, the water injection rate, the liquid production rate and the polymer injection rate of each well are used as optimization variables, the differential evolution algorithm is used, the total polymer injection amount and the oil reservoir pressure are restrained, and an oil reservoir injection and production optimization mathematical model is established. According to the method, the oil reservoir is optimized by comprehensively considering the characteristics of the oil reservoir after water flooding is converted into polymer flooding, so that rapid decision-making of the oil field and guidance of oil field construction are realized.

The invention discloses a method for predicting a favorable area of a thin-layer stacked sand body, and relates to the technical field of exploration and development of oil and gas reservoirs, and the method comprises the steps: generating a synthetic seismic record through well-seismic combination by using interval transit time and a density curve, aligning the synthetic seismic record with an actual seismic record, and building a three-dimensional frame model of a target layer of a research area; performing abnormal value elimination and standardization processing on the logging curve, making a statistical histogram, comparing peak separation degrees of sandstone and mudstone, and selecting the most sensitive curve to distinguish the sandstone and mudstone; and realizing well-side seismic trace waveform dynamic clustering analysis through singular value decomposition, and determining the number of effective samples. Based on the result of waveform indication simulation, the method is combined with the optimized seismic attribute to predict the thin-layer stacked sand body together, a systematic method is provided, the multiplicity of solutions of predicting the thin-layer stacked favorable sand body through the seismic attribute and the uncertainty of depicting the sand body by the sedimentary facies in the area with few wells can be reduced, and the prediction accuracy of the thin-layer stacked favorable sand body is improved. Therefore, the precision and reliability of thin-layer stacked sand body prediction are improved.

The invention discloses a three-dimensional geologic body model construction method based on sedimentary simulation, and the method comprises the following steps: S1, data collection: collecting various geological data of a target region, including but not limited to drilling data, seismic exploration data, a geological map, paleocurrent direction data and the like; the collected data are preprocessed, the data quality is checked, and wrong or abnormal data are removed; s2, feature parameter extraction: extracting feature parameters related to sedimentary facies from the preprocessed geological exploration data; the parameters can comprise a particle size median Md, a sorting coefficient SO, skewness SK, kurtosis Kg, a logging curve characteristic value, natural gamma GR and resistivity Rt; and S3, parameter mapping of the sedimentary facies. According to the preparation method, through parameter mapping and fine identification of sedimentary facies, the sedimentary characteristics of the geologic body are reflected more accurately, and the calculation amount is reduced and the modeling efficiency is improved while the precision of the model is ensured by the application of a self-adaptive grid division technology and a finite volume method.

The invention discloses a method for depicting the boundary of a sedimentary system through a heavy mineral combination based on an intelligent sensing system, and relates to the technical field of geological exploration, and the method comprises the steps: obtaining the heavy mineral content data of a sedimentary rock sample collected by a target layer section and a peripheral exposed section of the target layer section in a research area through the intelligent sensing system; carrying out statistics on the contents of various heavy minerals in the collected samples, calculating the percentage of each heavy mineral, and carrying out data arrangement to form a data table; and importing the heavy mineral content data into data analysis software, carrying out Q-type clustering analysis, and classifying according to the similarity between samples. According to the method, the heavy mineral content data of the sedimentary rock sample is obtained through the uniformly distributed sampling points, compared with traditional single-point sample analysis, the spatial distribution characteristics of a material source system in a research area can be more comprehensively reflected, the boundary of a sedimentary system can be accurately divided, the recognition precision of sedimentary facies distribution is improved, and the analysis accuracy of the sedimentary facies is improved. And more detailed basic data are provided for geological research and resource exploration.

The invention belongs to the technical field of rare earth mineral exploration, and particularly relates to a rare earth prospecting method based on particle size analysis of ultra-fine particle sediments, which comprises the following steps: sampling a clay rock stratum at the bottom of Xuanwei group, and analyzing the particle size of the sample and the composition of each particle size; and when the proportion of the sample with the particle size of 111.00-654.11 microns is 50%-60%, the proportion of the sample with the particle size of 0.04-0.15 microns is 15%-25%, and the proportion of the sample with the particle size of 2.42-7.64 microns is 20%-30%, judging that the sample is a rare earth enriched dominant phase region. The method disclosed by the invention has a relatively good effect on sedimentary microfacies analysis of sedimentary type rare earth ore-bearing construction which has no obvious sedimentary structure and no obvious sedimentary facies mark and is relatively strongly damaged by later-stage transformation; meanwhile, the sedimentary rare earth prospecting target area can be delineated rapidly and greenly, the cost of the exploration stage is greatly reduced, and the prospecting efficiency is improved.

The invention provides a sandstone-type uranium deposit sedimentary facies identification method, system and device and a medium, and belongs to the technical field of sedimentary facies identification, and the method comprises the steps: obtaining sandstone-type uranium deposit sedimentary facies multi-source data; time-frequency domain feature data, texture feature and waveform feature data and element ratio feature and statistical feature data related to sedimentary facies in the sedimentary facies multi-source data are extracted; time sequence features, three-dimensional structure features and metallogenic environment features are extracted from the feature data and weighted fusion is carried out to obtain the sedimentary facies category recognition probability. Multi-dimensional information complementation is realized by combining logging, earthquake and geochemical data, covering vertical lithology change, three-dimensional sand body distribution and a sedimentary facies state in a redox environment scene, and the focusing capability and the recognition precision of the model are effectively improved.

The invention relates to the field of geological mineral exploration, and discloses a reservoir analysis method for a virtual well, which comprises the following steps: standardizing a historical logging curve set into a standard logging curve set, and carrying out sedimentary subfacies analysis on the historical logging curve set to obtain a single well sedimentary facies result; comparing and analyzing the standard logging curve set to obtain a well-to-seismic calibration result; generating multi-type sedimentary facies seismic response features; clustering and analyzing the multi-type sedimentary facies seismic response features to obtain a plurality of single-type sedimentary facies distribution features, and constructing a plurality of virtual wells; calculating a target layer longitudinal wave impedance logging curve, and determining a reservoir longitudinal wave impedance range; seismic wave impedance inversion is carried out by using the longitudinal wave impedance logging curve of the target layer to obtain a longitudinal wave impedance data body, and the distribution measurement data of the target layer is counted by using the longitudinal wave impedance range of the reservoir and the longitudinal wave impedance data body. The invention further provides a reservoir analysis device and equipment for the virtual well, a medium and a program. According to the method, the reservoir analysis efficiency of the virtual well can be improved.

The invention provides a three-dimensional sedimentary facies modeling method and device based on planar graph constraint, and the method comprises the steps: loading a sedimentary facies graph and a thickness graph to a three-dimensional space, projecting a planar graph to an oil reservoir grid through space coordinate transformation, and coarsening the planar graph into an oil reservoir grid surface attribute; establishing a rapid sedimentary facies model by utilizing the plane sedimentary facies diagram, and establishing lithologic probability volume data by utilizing the plane thickness diagram and through coKriging interpolation; and the logging sedimentary facies data serve as hard data, the rapid sedimentary facies model serves as spatial constraint, the probability body serves as trend constraint, and a sequential indication simulation algorithm is utilized to generate the sedimentary facies model. According to the three-dimensional sedimentary facies modeling scheme based on the planar graph constraint provided by the invention, information such as the logging facies, the planar facies and the thickness graph is comprehensively utilized, the understanding of geologists can be introduced between wells, the problems of mathematics and datamation of a conventional method are solved, and the precision of a sedimentary facies model is improved.

Methods for seismic diagenetic modeling are disclosed. The methods include obtaining a seismic facies map, well data from one or more wells, and a burial map, and determining input parameters, a burial-history curve, and a thermal-history curve based on the well data. The methods may further include determining a sedimentary facies map based on the seismic facies map and the well data, for each of the sedimentary facies, determining a facies-dependent seismic diagenesis model based on the input parameters, the burial-history curve, the thermal-history curve, the sedimentary facies map, and models, determining a seismic diagenetic model based on the facies-dependent seismic diagenesis model for each of the sedimentary facies and the burial map, and determining an output map based on the seismic diagenetic model. The methods may further include identifying a drilling target based on the output map and designing a wellbore drilling plan based on the drilling target. Systems for seismic diagenetic modeling are also disclosed.

The invention provides an abrupt slope glutenite mass scale prediction method and system, and the method comprises the steps: S1, building an isochronous stratigraphic framework based on well drilling and seismic data, and recognizing a basin edge fault and a base; s2, inshore subsea fan gravel rock mass depicting based on a sedimentary facies belt; s3, constructing a relationship between occurrence parameters of the basin edge fault and the basement and geometric morphology parameters of the glutenite body; and S4, constructing a near-shore underwater fan glutenite mass scale prediction mathematical model based on the basin edge fault and the basement occurrence. And establishing a corresponding mathematical model to realize fine prediction of the near-shore underwater fan gravel rock mass scale.

The invention discloses a method for predicting a favorable sand body in a less-well area based on sedimentary numerical simulation and comprehensive well shock, and relates to the technical field of oil-gas exploration and development. Based on logging, shock and core data, a sedimentary facies is depicted, a sedimentary system is defined, and a basic structure-sedimentary environment is constructed; the method comprises the following steps: defining a containing space parameter, a material source supply parameter and a carrying parameter by utilizing a sedimentary ancient landform, lake plane elevation, tectonic settlement and a material source system, and establishing an initial sedimentary forward modeling model; and comparing the simulation result of the initial deposition forward modeling model with the underground actual geological information of the area with less wells point by point and layer by layer, and evaluating the correlation degree of the simulation result and the actual geological condition. According to the method, the theoretical basis of favorable sand body prediction is provided, the uncertainty of single attribute prediction is eliminated, the precision of favorable sand body prediction in the well-deficient area is improved, and a technical method and the theoretical basis can be provided for favorable sand body prediction in numerous sedimentary basin well-deficient areas.

The invention discloses a marine clastic rock reservoir modeling method based on geological cause information, which relates to the technical field of geological modeling, and comprises the steps of collecting and preprocessing modeling data, obtaining preprocessed data, performing geological background research on a target area, performing profile analysis and interface identification on the preprocessed data, and obtaining a marine clastic rock reservoir model. Extracting and converting inclination angle information from the preprocessed data, identifying and quantifying interlayer features, generating a probability distribution constraint body, performing sequential indication modeling, and verifying, optimizing and applying the model; according to the method, multi-source data is integrated to deeply research the sea entering and sea exiting rule, an interface is accurately identified, a sedimentary facies belt is divided, a foundation is laid for reservoir analysis, dip angle information is innovatively utilized, the dip angle information is converted into a probability value and fused into sequential indication modeling, interlayer distribution is accurately simulated in combination with reservoir characteristics and a variation function, and the reservoir analysis result is obtained. And the characterization capability of the model on a complex reservoir structure is obviously improved.

The invention discloses a sedimentary facies model construction method and device, equipment and a storage medium. The method comprises the following steps: acquiring regional geological parameters of a target construction region; and determining structure interpretation data according to the regional geological parameters, and constructing a three-dimensional structure model according to the structure interpretation data. And analyzing distribution information of each lithofacies in the three-dimensional structure model according to regional logging data, and constructing a lithofacies framework model. A target sedimentary facies model corresponding to the target construction area is constructed according to the three-dimensional sedimentary point cloud and the lithofacies framework model based on a multi-point geostatistics algorithm, and the three-dimensional sedimentary point cloud is obtained by performing actual sedimentary simulation on the target sedimentary construction model obtained through pre-training based on the area geological parameters of the target construction area. According to the technical scheme, the three-dimensional sedimentary point cloud of the research area can be accurately extracted, high geological objectivity and physical authenticity are achieved, and therefore the objectivity and geological reliability of the sedimentary facies model are remarkably improved.

The invention discloses a pipeline sediment erosion and deposition numerical simulation method and system based on a cellular automaton, and the method comprises the steps: (1) constructing a one-dimensional cellular erosion and deposition scene of a pipeline, and setting the cellular size, neighborhood relation and state of the pipeline, and the initial conditions of the quality of particulate matters in an aqueous phase and a sedimentary phase; (2) calculating the net settling volume of the cells in the vertical direction, and updating the cellular sedimentary facies particulate matter mass and deposition thickness at the next moment according to a sedimentary facies particulate matter updating rule; (3) calculating the water-phase transport quantity of the cells in the horizontal direction, and updating the mass and concentration of the water-phase particulate matters of the cells at the next moment according to a water-phase particulate matter updating rule; and (4) calculating vertical settlement and horizontal transportation of the circulating pipeline cell in combination with the updated pipeline cell state, so as to obtain the erosion and deposition change process of the sediment in the pipeline. According to the pipeline sediment erosion and deposition change discrete calculation form, the migration and transformation process of the sediment in the pipeline can be accurately simulated, and technical support is provided for pipe network sediment erosion and deposition simulation.

The invention provides a sand body distribution prediction method, equipment and a medium, and relates to the technical field of seismic exploration. The method comprises the following steps: acquiring seismic response waves and logging data beside a hoistway in a target area; based on the seismic response waves beside the hoistway and the logging data, a singular value decomposition algorithm is adopted, and the corresponding relation between the seismic response wave components of the target area and different sedimentary facies is determined; a likelihood function used for describing the sedimentary facies plane distribution probability is constructed by taking the corresponding relation between the seismic response wave component of the target area and different sedimentary facies as prior information; determining plane distribution probabilities of different sedimentary facies based on a likelihood function and the seismic response waves of the target area; based on the plane distribution probabilities of different sedimentary facies, grouping seismic response waves corresponding to different sedimentary facies to obtain a plurality of sample sets; seismic wave inversion is carried out based on each sample set, and the vertical thickness and plane distribution of the sand body in the target area are obtained. According to the sand body distribution prediction method provided by the invention, the transverse resolution of the sand body is improved.

The invention provides a local artificial intelligence earthquake sand liquefaction deformation prediction method and system, and relates to the technical field of geological disaster prediction, and the method comprises the steps: obtaining multi-source geological data; 3-5Hz soil mass frequency domain features are extracted through wavelet packet decomposition, a DEM and a historical liquefaction thermodynamic diagram are fused to divide a sedimentary facies control unit, a three-dimensional voxel model is generated by adopting a Bayesian constrained improved Kriging algorithm, and a four-dimensional space-time tensor is constructed in combination with real-time seismic oscillation dominant frequency offset; inputting the tensor into a local adaptive graph convolutional network, dynamically adjusting the weight of a convolution kernel through a space-time attention mechanism, and synchronously outputting a prediction result; triggering incremental learning based on MEMS acceleration and FBG strain data, correcting a predicted value of an unliquefied region, and feeding back the predicted value to the voxel model; and finally, generating a probabilistic disaster chain scene tree through spatial pattern matching. The technical bottleneck that a traditional model is poor in adaptability in a complex sedimentary environment and cannot be updated in real time is solved, and intelligent early warning support is provided for engineering safety of an earthquake active area.

This invention provides a method for characterizing sedimentary microfacies distribution based on comprehensive geological and seismic analysis. By studying the sedimentary environment and surrounding tectonic background of the entire block, this invention calculates the cumulative percentage of channel and shoal body types based on sedimentary microfacies and grain size analysis. Based on a comprehensive analysis of the lithofacies of drill cores and corresponding well logging curves and seismic response characteristics, it establishes a comprehensive response model of the main sedimentary facies-well logging facies of the target stratigraphic group in the study area. Furthermore, based on the fusion of seismic attributes, it characterizes sand bodies in seismic profiles. By integrating the sand body characterization results, the comprehensive response model of sedimentary facies-well logging facies, and the sedimentary microfacies types, a method for characterizing sedimentary microfacies distribution in tight sandstone reservoirs using comprehensive seismic and geological analysis is established.

The invention provides an identification and prediction method for petroliferous basin mixed rock. The identification and prediction method comprises the following steps: S1, identifying single well lithofacies; s2, the sedimentary facies type and the sedimentary microfacies type of the sand-mud mixed accumulation area are recognized and divided; s3, establishing a lithofacies combination classification scheme, and forming a matching relationship between the lithofacies combination and the sedimentary microfacies; s4, establishing a well logging database of the mixed rock stratum section of the sand-mud mixed zone; s5, establishing rock physical phase classification by using an SOM neural network clustering analysis method; s6, establishing a lithofacies combination type and sedimentary microfacies identification model; and S7, establishing a spatial distribution model of the sedimentary microfacies and lithofacies combination of the mixed rock. And the mixed rock reservoir is classified and predicted, and the prediction result has higher geological causes and rationality.

The application discloses a kind of based on sequence stratigraphy and seismic sedimentology's braided river channel reservoir fine characterization method, comprising the following steps: obtaining target area core, well logging and high-resolution three-dimensional seismic data;By analyzing the sedimentology mark and logging facies mark in the target area, to determine the sedimentary facies type and sedimentary microfacies division;Using lithology and well logging curve, using the theory of sedimentology, high-resolution sequence stratigraphy identifies sequence interface type and feature, and carries out high-resolution sequence stratigraphic sequence division;Division reservoir architecture interface;According to the internal structure of sedimentary system, sedimentary facies distribution, focus on high-frequency sequence and sedimentary body scale, generate the braided river channel reservoir fine characterization result of target area architecture unit.The present application effectively solves the deficiencies of prior art in reservoir fine description, boundary identification and parameter inversion, improves the efficiency and success rate of oil and gas reservoir development.

The invention discloses a hydrocarbon source rock TOC content plane distribution prediction method based on a mud-to-ground ratio, and relates to the technical field of oil-gas exploration and development, and the method comprises the following steps: dividing a single well sequence and a sedimentary facies, and carrying out the statistics of the mud-to-ground ratio of a stratum between interfaces; according to the TOC test result and the logging curve of the hydrocarbon source rock sample, a single well TOC content prediction model is established, and the TOC average content of hydrocarbon source rocks between interfaces is counted; obtaining a mud-to-ground ratio plane contour map; establishing an organic matter sedimentary geologic model, and analyzing the correlation between the TOC average content and the mud-land ratio; establishing a quantitative characterization mathematical model between the mud-land ratio and the TOC average content, and matching the quantitative characterization mathematical model with an analysis result of the organic matter deposition geologic model; drawing a TOC plane contour map according to the mud-to-earth ratio plane contour map and the quantitative characterization mathematical model; according to the method, the distribution of the high-abundance hydrocarbon source rocks can be described more accurately, the reliability is high, and the result accuracy is high.

The invention discloses a paleo-gradient constraint reservoir characterization attribute for deep fan delta sedimentary facies characterization. The paleo-gradient constraint reservoir characterization attribute comprises the following steps: 1) carrying out multiple seismic attributes of a target stratum and carrying out normalization processing; 2) seismic attribute optimization is carried out by using the correlation with the sandstone thickness; 3) fitting a multiple linear regression relationship between the sandstone thickness and the optimized seismic attributes; 4) drawing a whole-area sandstone thickness prediction contour map; 5) solving an ancient slope on the ancient landform map; 6) drawing a whole-region ancient slope contour map; 7) acquiring a relation inflection point between the sandstone thickness and the paleo-slope in the research area; 8) predicting sandstone thickness and paleo-gradient by using seismic attributes to establish paleo-gradient constrained reservoir characterization attributes; and 9) calculating all-region paleo-gradient constraint reservoir representation attributes, and drawing a contour map as a basis for depicting the deep fan delta sedimentary facies. The method solves the problem that seismic attribute representation sedimentary facies lacks environmental information and the problem of multiplicity of solutions of deep fan delta seismic reflection representation sedimentary facies.

The invention provides a sand body reservoir prediction method and device, electronic equipment and a storage medium. The method comprises the steps that well-seismic horizon calibration is conducted according to well drilling data and seismic data; interpreting and tracking a horizon interface and a sand body reservoir interface of the complex salt structure region according to the seismic reflection characteristics; the sedimentary microfacies of the complex salt structure area are recognized, and sedimentary facies plane distribution comprehensive calibration is carried out; according to the time sequence of the salt structure activity and the sand body reservoir section stratum development, the interaction mode of the salt structure and the water channel is analyzed, and sand body reservoir prediction is conducted. According to the method, the interaction mode of the salt structure and the water channel is analyzed according to the time sequence of salt structure activity and sand body reservoir section stratigraphic development, under-salt and inter-salt turbid water channel space distribution is predicted, and prediction of a geophysical imaging fuzzy zone sand body reservoir is achieved. The method is of great significance in reducing deep-sea exploration cost and improving drilling success rate.

The invention belongs to the field of oil and gas field development, and discloses a method and device for researching the uncertainty of oil reservoir geological reserves, and the method comprises the steps: analyzing the uncertainty of a structure, the uncertainty of a sedimentary facies, the uncertainty of porosity, the uncertainty of water saturation, the uncertainty of an oil-water interface and the uncertainty of a volume coefficient; based on the analysis result of each uncertainty, geological reserve sensitivity analysis is carried out; based on the analysis result of each uncertainty, carrying out geological reserve uncertainty analysis; and performing quality control on the uncertainty analysis of the geological reserves. Through uncertainty analysis, the geological reserve distribution condition of the oil reservoir can be backed up, and a good foundation is laid for selection of oil and gas field development modes, compilation of development schemes and the like. And meanwhile, the method comprises quality control on a research result, so that the uncertainty understanding on the geological reserves of the oil reservoir is more reliable.

The invention discloses a carbonate rock and gypsum salt rock combination zone analysis method and device, and the method comprises the steps: dividing a plurality of analysis units according to the similarity of a geological structure unit, a sedimentary facies belt and an oil-gas accumulation combination type in a research zone; the oil-gas reservoir-forming combination in each analysis unit has similar geological structures, sedimentary environments and reservoir-forming characteristics; predicting a space-time factor of hydrocarbon generation capacity in the research zone and a space-time factor of a sub-heterotypic structure zone; comprehensively analyzing and researching space-time factors of the in-zone Tibetan formation area by combining a structure evolution history, a deposition history, a thermal evolution history and a fluid evolution history; and selecting an exploration area according to space-time factors in the research area. According to the method, a region with favorable reservoir forming conditions can be selected as an exploration region, and a new thought and direction are provided for oil-gas exploration.

This invention discloses a method, apparatus, computer equipment, and medium for predicting Paleogene reservoir permeability. The method includes: acquiring seismic and well logging data of a target Paleogene region; determining sedimentary facies data, porosity, amplitude spectral gradient, and velocity dispersion data of the target Paleogene region as input variables based on the seismic data; wherein a quantitative correspondence exists between the sedimentary facies data and permeability; determining the sample permeability of drilled wells in the target Paleogene region as an output variable based on the well logging data; and substituting the input and output variables as the original sample set into a preset random forest model to predict the reservoir permeability of the target Paleogene region. By introducing sedimentary facies into the sample data, a phase control effect can be achieved in the random forest regression sample training and decision-making process, thereby making the prediction results more reliable, more consistent with actual geological sedimentary patterns, and increasing the accuracy of permeability prediction.

The invention discloses a method and device for drawing a carbonatite sedimentary facies diagram based on ternary coupling. The method comprises the following steps: determining a water depth environment based on a regional structure effect, a basin position, a substrate characteristic and a climate condition, and establishing a research region concept deposition mode; selecting a typical well, dividing a three-level sequence in the typical well according to earthquake, logging and core data, and further dividing a mapping unit; for each sequence, establishing a relationship between the ternary coupling of the water depth background, the sea level cycle and the paleo-geographic position and the sedimentary hydrodynamic condition and the stratum thickness, analyzing the thickness change of the single well stratum in the sequence, and reversely deducing the sedimentary hydrodynamic condition based on the relationship in combination with the water depth background, the sea level cycle and the paleo-geographic position; and determining a single-well facies under the guidance of the concept sedimentary mode, fitting, matching and correcting the single-well facies and hydrodynamic conditions, and drawing a sedimentary facies diagram of the drawing unit in combination with the regional structure trend. The method can draw a reasonable and accurate regional sedimentary facies diagram for a complex oil field group.

The invention discloses a Fisher river and lake sedimentary facies distinguishing method and system based on granularity parameters, and belongs to the field of sedimentary facies. The method comprises the following steps: collecting sedimentary granularity data of a river-lacustrine facies stratum; inputting the sedimentary granularity data of the river-lake facies strata into a Fisher discrimination function, and outputting a river-lake sedimentary facies discrimination result; the Fisher discriminant function construction process comprises the steps that sedimentary granularity data of a river-lake facies stratum is obtained, and river-lake sedimentary facies division is conducted through mathematical analysis software; and on the basis of a result obtained by dividing the river-lake sedimentary facies, combining the granularity parameters of the sedimentary granularity data of the river-lake facies stratum, and performing fitting to form a Fisher discriminant function. According to the method, the river-lake sedimentary facies division result is combined with the granularity parameters, the Fisher discrimination function is formed through fitting, the influence of human factors on river-lake facies division is avoided, the river-lake sedimentary facies discrimination result is obtained through calculation by means of the Fisher discrimination function, and analysis of sedimentary environment evolution of a research area can be achieved.

The invention belongs to the technical field of oil and gas exploration and development, and relates to a method and system for quantitatively depicting distribution of different types of hydrocarbon source rocks in a few-well area, and the method comprises the steps: obtaining a seismic body, a sedimentary facies diagram, interval transit time logging data and density logging data after target lamination; hydrocarbon source rock seismic reflection characteristics corresponding to different deposits are obtained through a seismic profile map obtained by intercepting a post-stack seismic body; analyzing the types of the hydrocarbon source rocks by utilizing a sedimentary facies diagram, and depicting plane distribution of different types of hydrocarbon source rocks in a target layer according to different types of hydrocarbon source rock development characteristics and sedimentary facies predicted by utilizing the seismic reflection characteristics of the hydrocarbon source rocks; the residual stratum thickness of the target layer is obtained according to the post-stack seismic body, the stratum sand-to-ground ratio of the target layer is predicted, and hydrocarbon source rock thickness distribution in the target layer is depicted according to the residual stratum thickness and the stratum sand-to-ground ratio; and carrying out coupling analysis on the hydrocarbon source rock plane distribution and the hydrocarbon source rock thickness distribution to obtain hydrocarbon source rock space distribution. According to the method, distribution of different types of hydrocarbon source rocks in the less-well area is quantitatively depicted.

This invention discloses a method for establishing time-spectral sedimentary facies samples based on seismic forward modeling. The method includes: Step S1: Constructing typical sedimentary models and various sedimentary facies property templates for the actual work area based on core sedimentary characteristics; Step S2: Obtaining sedimentary facies geological profiles based on typical sedimentary models and sedimentary facies property templates; Step S3: Extracting actual seismic forward modeling parameters from actual seismic data; Step S4: Conducting forward modeling of the sedimentary facies geological model based on the actual seismic parameters; Step S5: Converting the forward modeled seismic data into time-spectral data through continuous wavelet transform; Step S6: Extracting typical seismic traces from the forward modeled seismic profiles, using the sedimentary facies in the geological model as labels and the time-spectral data as feature values ​​to establish sedimentary facies seismic samples. A large number of high-precision samples are generated under the guidance of typical models, and the sample labels are completely accurate, eliminating errors caused by time-depth calibration, thus meeting the needs of machine learning for sedimentary facies prediction.

The invention provides an oil and gas block well seismic label capacity expansion method, system, device and medium, and belongs to the field of geology, geophysics and machine learning, and the method comprises the steps: dynamically delimiting a core work area based on a real well, and laying candidate points in a gridding manner; pCA dimension reduction and parallel prediction of a plurality of models are adopted to obtain a preliminary screening virtual well point pool; candidate points contradictory to real data are eliminated by setting a real well protection radius and a threshold value, and box separation and capacity limiting are performed according to a sand thickness interval, so that sample space and attribute distribution balance is ensured; and finally, through multi-round iterative extrapolation, sedimentary phased directional attenuation constraint is introduced, double verification is performed on newly added samples, and the coverage range of reliable samples is gradually expanded. According to the method, hundreds of times of expansion of the well seismic label is realized, the generated virtual sample has both geological rationality and statistical diversity, deep learning model training can be effectively supported, the accuracy and generalization ability of reservoir parameter prediction in a less-well area are remarkably improved, and a reliable data basis is provided for oil-gas exploration decision.