29 results about "Sedimentary structures" patented technology

A three-dimensional heterogeneous aquifer horizontal equivalent permeability coefficient multi-scale prediction method based on a residual network comprises the steps that a foundation pit dewatering two-dimensional pressure-bearing steady flow model is constructed, the influence of the size of a lenticular body on foundation pit dewatering flow field disturbance is evaluated, and the resolution ratio of a parameter prediction model grid is determined; based on actual drilling data and transition probability / Markov chain T-Progs, according to multiple deposition types formed by a binary deposition structure, a multi-layer aquifer structure, a coarse-grained deposition structure and a fine-grained deposition structure, a three-dimensional stratigraphic random structure model set is constructed, and three-dimensional stratigraphic section random slices are established; obtaining horizontal equivalent permeability coefficients corresponding to stratigraphic sections in various stratigraphic structures based on the underground water flow numerical model FloPy, and establishing a stratigraphic structure-equivalent permeability coefficient training set based on a neural network; a deep learning model is constructed based on the residual network ResNet50; and training, verifying and testing the equivalent permeability coefficient of the stratum section formed by the binary sedimentary structure, the multi-layer aquifer structure, the coarse grain sedimentary structure and the fine grain sedimentary structure.

The invention discloses a shale deposition structure automatic identification method and device, and relates to the field of shale oil exploration and development, and the method comprises the steps: obtaining an image of a rock core and an electric imaging logging image corresponding to the rock core; processing and identifying a bedding boundary in the electrical imaging logging image; determining the number of stratification in the core image; determining a corresponding relation between the number of bedding boundaries in the electrical imaging logging image and the number of bedding in the image of the rock core; based on the corresponding relation and the bedding boundary of the electrical imaging logging image of the non-coring stratum, the actual bedding number of the non-coring stratum is determined, and then the sedimentary structure of the non-coring stratum is determined. After the corresponding relation of the bedding boundary between the actual image of the stratum core and the electric imaging logging image corresponding to the rock is determined, the sedimentary structure of the shale stratum can be automatically determined according to the electric imaging logging image, and the actual core does not need to be sampled and manual identification does not need to be carried out. And the automatic identification of the sedimentary structure of the shale stratum can be realized by adopting electric imaging logging.

The invention belongs to the field of geological sedimentology, and particularly relates to a storm cause high-quality lithofacies identification method based on multi-source data comprehensive identification, which comprises the following steps of: A, data acquisition and preprocessing: S1, data acquisition and confirmation: automatically identifying the characteristics similar to a Baomah sequence in a rock core by using a convolutional neural network (CNN) according to the rock core, a field outcrop, a logging curve and logging data; outputting storm deposition sample information; s2, performing automatic lithofacies classification on the rock core image by adopting deep learning (U-Net) in combination with a sedimentary structure; and S3, automatically identifying curve characteristics of a'box-shaped '(storm dam main body) and'bell-shaped and finger-shaped' (storm dam side edge) by adopting time sequence analysis (LSTM or Transformer). According to the method, the high-quality lithofacies recognition model is established by integrating multivariate data, the recognition precision and efficiency are greatly improved, and a scientific basis is provided for oil and gas reservoir evaluation in a storm sedimentary environment.

The invention discloses a rock core description and tight sandstone reservoir sampling method based on a sedimentary structure, and belongs to the technical field of petroleum and natural gas geological exploration. The method comprises the following steps: collecting geological background data including a target stratum and logging data, and establishing a core description chart; according to the sedimentary structure profile, the core sketch and the text description established by the core description chart, the sedimentary cycle change, the sedimentary microfacies type and the lithofacies type of the target stratum coring section are obtained; and according to the sedimentary cycle change, the sedimentary microfacies type and the lithofacies type of the target stratum coring section, determining a sampling point for tight sandstone reservoir sampling. Based on the core description of the sedimentary structure, the sedimentary characteristics of the coring section can be clearly displayed in a map form, so that scientific researchers who do not carry out the work can quickly understand the sedimentary environment of a target layer and the development law of a compact sandstone reservoir, and then sampling design is carried out in a targeted manner; and a geological basis is provided for subsequent sedimentary reservoir research and exploration and development well position deployment.

The invention provides a lithofacies paleogeography mapping method and system based on tectonic-sedimentary differentiation research. The method comprises the following steps: analyzing and determining key tectonic event occurrence and evolution processes of different key times based on a basin to be processed; geologic structure types and spatial distribution rules of different regions are analyzed, and a geologic structure partition map is comprehensively compiled; a stratum and a stratum internal structure are divided by combining logging, rock cores, rock debris and seismic data; further analyzing a structure-deposition differentiation type based on internal characteristics of the stratum, establishing a non-Wartt facies deposition-structure mode, determining a filling sequence interface division scheme, establishing a sequence stratigraphic well-connecting framework, and analyzing a stratum filling rule; main control factors are researched on the basis of the divided sedimentary facies law units, the spatial distribution law of the mapping units is analyzed, and a lithofacies paleogeography map is compiled and formed. By adopting the scheme, the problems of limited mapping mode and insufficient accuracy in the prior art can be solved, the structure development evolution condition of the sedimentary basin is reliably represented, and the map accuracy is improved.

The invention relates to the technical field of deep oil and gas exploration, in particular to a deep reservoir dominant region prediction method and device, and the corresponding method comprises the steps: determining a reservoir sedimentary facies diagram of a deep reservoir through the sedimentary structures and sedimentary facies of a plurality of single-well reservoirs under the constraint of a pre-generated sedimentary-structure pattern diagram of the deep reservoir; wherein the sedimentary facies is a superposed part of an early-stage high-quality facies belt and a diagenetic facies belt in a quasi-synbiotic period of the deep reservoir; determining a reservoir diagenetic phase diagram of the deep reservoir according to a pre-generated diagenetic sequence diagram of the deep reservoir, the corrosion landform partition map and the fluid system plane distribution diagram; and according to the reservoir sedimentary facies map, the reservoir diagenetic facies map, the dominant sedimentary facies and the dominant diagenetic facies, predicting the dominant region of the deep reservoir. According to the method, the viewpoint of controlling the scale high-quality reservoir by the early-stage high-quality facies belt and the quasi-synbiotic lithogenous facies belt is provided, the double-phase superimposed belt control and reservoir model is established, deep reservoir prediction is carried out, and a good effect is achieved.

The application discloses a shale sedimentary structure automatic division method, and comprises the following steps: S1, FMI static image is cropped and subjected to gray scale processing; S2, a gray scale coexistence matrix is used to calculate FMI gray scale image texture parameters; S3, texture parameter sedimentary structure sensitivity analysis is performed; S4, parameter optimization is performed based on a random forest classification model; and S5, shale sedimentary structure automatic division is performed based on the random forest. The FMI image is fully utilized in the aspect of sedimentary structure division, the restriction of conventional logging on shale sedimentary structure division is broken, a more convenient and effective shale sedimentary structure division method is provided, and important technical support is provided for accurate shale facies division.

The invention discloses a method for determining the paleo-flow direction of a river channel sand body by combining a well trajectory and a core deposition structure, which comprises the following steps of: collecting well location argumentation, core, three-dimensional earthquake and logging data, preliminarily determining the occurrence of a target stratum and judging whether an original stratum is horizontal or not; a comprehensive logging map with a track is drawn based on well deviation and azimuth data of the pilot well, and in-situ occurrence of the rock core stratum is recovered by combining the occurrence of the target stratum and the axial angle of the rock core; then selecting a coring well to analyze a rock core, determining a lithofacies type, and preferably selecting a typical lithofacies and a sedimentary structure for paleo-flow direction recovery; the paleo-flow direction is corrected in a grading mode according to the original stratigraphic dip angle, when the dip angle is smaller than 5 degrees, the pilot well orientation is used as stratigraphic tendency correction, and when the dip angle is larger than 5 degrees, vertical well logging and seismic data correction are combined; and finally, verifying a paleo-flow direction in combination with three-dimensional seismic river distribution, and judging whether projection processing is performed according to an included angle between a well trajectory and a main flow line of the paleo-river According to the method, the paleo-flow direction determination precision is improved, and a reliable basis is provided for reservoir distribution prediction in oil-gas exploration.

The invention belongs to the technical field of tectonic deformation simulation experiments, and discloses a co-sedimentary structure simulation experiment device and a co-sedimentary structure simulation experiment method. The co-sedimentary structure simulation experiment device comprises a sand box, a partition plate and a pushing mechanism. The partition plate is detachably arranged in the sand box and divides the sand box into a first box body and a second box body in the gravity direction, the partition plate is provided with a sand passing part, and the first box body and the second box body are communicated through the sand passing part. The pushing mechanism comprises a first pushing part and a second pushing part, the first pushing part is movably arranged in the sand box, and the second pushing part is arranged on the first pushing part in parallel at an interval and can move together with the first pushing part. And the simulated geological layer is driven by the first pushing piece to form a target simulated recess. And the simulated sedimentary sand can fall into the first box body under the driving of the second pushing piece and is deposited into the target simulated recess. The simulation experiment device for the co-sedimentary structure can better fit the actual environment, the physical simulation experiment of the co-sedimentary structure is realized, and the accuracy of the experiment result is improved.

The invention discloses a method and a system for identifying ocean-going deposition and semi-ocean-going deposition by utilizing a sedimentary structure, and relates to the technical field of shale oil and shale gas exploration and development engineering, and the method comprises the following steps: S1, making and imaging a large shale slice; s2, identifying a horizontal stripe layer and a sequential composite gradient stripe layer group according to the shale large slice imaging data; and S3, identifying ocean-going deposition and semi-ocean-going deposition according to the horizontal stripe layer and the sequential composite gradient stripe layer group. According to the method, the sedimentary facies type is clarified by means of shale large slice imaging data bedding research on the basis of the basic knowledge of ocean sedimentary development page type horizontal bedding and semi-ocean sedimentary development sequential type composite gradient bedding under the strong reduction water body condition. The invention provides a new method for quickly and accurately identifying and distinguishing ocean-going deposition and semi-ocean-going deposition, so that a foundation is laid for optimizing favorable zones and targets of shale gas.

The invention relates to the technical field of geological evaluation, in particular to a stratified pulveryte core geology rapid experimental evaluation method which comprises the following steps: establishing a sample lithology characteristic table according to the color, mineral type and sedimentary structure of a stratified pulveryte core; determining a sampling layer section of the lithologic layer section of the lamina type pulveryte rock to be evaluated, and collecting and preparing a rock core sample; testing the collected rock core sample to obtain test data, wherein the test comprises slice identification, total rock X diffraction analysis, porosity determination and pyrolysis analysis experiment; the test data is extracted, homing comparison is carried out according to the test data and the sampling position, and core homing processing of the test data is achieved; and evaluating and analyzing the core potential of the lamina type pulveryte rock based on test data. According to the method, the rapid evaluation of the hydrocarbon source rock and the oiliness is realized, the sampling heterogeneity problem in the evaluation process is solved, and guidance is provided for the fine evaluation of the shale oil reservoir.

The invention discloses a continental lake basin shale bed series lithofacies combination boundary delimiting method, and belongs to the technical field of exploration and evaluation. The delimiting method comprises the following steps: carrying out rock core observation and analysis on a shale bed series rock sample to obtain lithologic characteristics of the sample; and carrying out organic carbon determination and rock pyrolysis analysis experiment on the shale strata rock sample to obtain the total organic carbon content and the free hydrocarbon content, and determining the abundance of organic matters and comprehensively naming. And determining the sedimentary environment of the sample according to the total organic carbon content and the lithologic characteristics of the sample. And obtaining a relational graph of the continuous thickness of the shale and the free hydrocarbon content and a relational graph of the thickness proportion of the land occupation layer of the shale and the free hydrocarbon content. And establishing a lithofacies combination division standard through the indexes, and carrying out longitudinal lithofacies combination division on the shale bed series rock sample. According to the method, lithofacies can be effectively distinguished through comprehensive analysis of lithology, mineral composition, organic carbon content, sedimentary structure and the like.

The present disclosure provides a method and device for identifying gravity flow type of continental rift lake basin, and relates to the technical field of geological exploration. The method for identifying gravity flow type of continental rift lake basin comprises: obtaining three-dimensional seismic data, core data and logging data of a target area; the three-dimensional seismic data comprises seismic reflection structure and seismic slope; the core data comprises lithofacies characteristics, sedimentary structure, sedimentary sequence and particle size distribution characteristics; based on the three-dimensional seismic data, the core data and the logging data, as well as the characteristics of flood-type gravity flow and the characteristics of slumping-type gravity flow, the gravity flow type of the target area is determined; the gravity flow type is verified based on sedimentary process simulation, seismic inversion verification and reservoir microscopic verification; and in response to the verification passing, the gravity flow type is determined as the target gravity flow type of the target area. Thus, the defects of single parameter and insufficient verification in the traditional identification method are overcome, and the identification efficiency and accuracy of the gravity flow type are significantly improved.

The invention provides a step-by-step iteration prediction method for free oil content, which relates to the technical field of oil and gas exploration, and comprises the following steps of: firstly, collecting conventional logging data of a well to be predicted and historical conventional logging data and nuclear magnetic logging data of wells in the same block and the same sedimentary structure background, and calculating elastic parameters such as longitudinal wave speed and longitudinal wave impedance; secondly, constructing a deep learning network model; gradually predicting the total nuclear magnetic porosity, the effective nuclear magnetic porosity and the free oil content by using the model; and finally, selecting a well which does not participate in model training as a verification well to verify a prediction result, and applying the well to actual production. According to the method, related parameters are predicted step by step, so that the prediction precision is remarkably improved, and the convergence speed of a learning process model is effectively increased.

The invention discloses a fine-grained shale deposition structure identification method and device, electronic equipment and a medium. The method comprises the following steps: determining a research target layer, obtaining a continuous rock core column, and analyzing sedimentary structure characteristics of the rock core column in combination with logging curve characteristics; combining a correlation coefficient method to verify that shale deposition in a research area is influenced by an astronomical orbit period; the method comprises the following steps: establishing a scale for researching the absolute geological age of a stratum through petrostratigraphy, magnetic stratum and isotope analysis; carrying out high-resolution astronomical tuning on the slope and the age difference scale to obtain the duration of a deposition sequence, and recovering the deposition rate by establishing an age model; and establishing an evolution energy spectrum of the shale deposition structure and the age difference level deposition rate, and dividing a histogram of the deposition structure of the research target layer. According to the method, the development characteristics of the sedimentary structure of the fine-grained mixed sedimentary rock in the area can be conveniently, accurately and qualitatively researched by qualitatively identifying the sedimentary structure of the multi-element mixed sedimentary rock and quantitatively screening the distribution range of the sedimentary structure of the multi-element mixed sedimentary rock.

The present application is suitable for the technical field of shale gas exploration and development, and provides a shale favorable sedimentary facies belt prediction method, system, medium and processor. The method comprises: performing step-by-step screening on multi-source geological data based on geological classification screening rules through the multi-source geological data to obtain a core evaluation index system; wherein the step-by-step screening comprises first-level screening based on lithological combination, sedimentary structure and paleontological marker to identify sedimentary facies types, second-level screening based on the correlation strength between each initial evaluation index and a shale gas content macroscopic characterization parameter, and third-level screening based on the adaptation degree of each index and key elements of tectonic preservation conditions; a sedimentary facies belt favorable quantitative characterization model is constructed according to the core evaluation index system; finally, the core evaluation index of the region to be measured is input into the model for prediction, and the shale favorable sedimentary facies belt grade and the uncertainty range of the prediction result are output. The accuracy and reliability of shale favorable sedimentary facies belt prediction are effectively improved.

The present application relates to the technical field of geological disaster prediction, in particular to a seabed liquefaction prediction system based on neural network, which comprises a parameter change extraction module, a response model training module, a disturbance feature division module, a liquefaction probability statistics module and a risk prediction output module.In the present application, the change rates of sediment particle density and effective stress in different depth intervals are extracted layer by layer to build a longitudinal response relationship, which can capture the continuous change characteristics of the sediment layer with the increase of depth, and the response differences under different time sequence disturbance conditions are compared in depth by means of residual neural network, so that the coupling relationship between disturbance information and sediment structure can be dynamically described, and the phased change of disturbance behavior can be effectively corresponded.The liquefaction probability of each depth interval is calculated by combining the disturbance feature and the response model, and the interval risk groups are formed under different time periods, and then the risk amplitude change trend and the jump boundary between disturbance stages are compared.

The invention relates to the technical field of bioclastic limestone, and discloses a bioclastic limestone microfacies type determination method and device, and the method comprises the steps: obtaining a five-element factor of a bioclastic limestone microfacies; determining the microfacies type of the bioclastic limestone according to a five-element factor; wherein the five-element factors comprise the particle size, the indication biological species, the sorting property of the particles, the deposition structure and the structure used for distinguishing the deposition condition. According to the method, five key factors are provided, the use conditions and grading standards of various factors are established, and microfacies identification is quantified.

The invention relates to the technical field of geological disaster prediction, in particular to a seabed liquefaction prediction system based on a neural network, which comprises a parameter change extraction module, a response model training module, a disturbance characteristic division module, a liquefaction probability statistics module and a risk prediction output module. According to the method, the change rates of the sediment particle density and the effective stress in different depth intervals are extracted layer by layer, and the longitudinal response relation is constructed, so that the continuous change characteristics of the sediment layer along with the progressive increase of the depth can be captured, and the response difference under different time sequence disturbance conditions is subjected to deep contrastive analysis by virtue of the residual neural network; the coupling relationship between the disturbance information and the sedimentary structure can be dynamically described, and the periodic change of the disturbance behavior can be effectively corresponded. The disturbance characteristics and the response model are combined to calculate the liquefaction probability of each depth interval, interval risk groups are formed in different time periods, and then the risk amplitude change trend and the jump boundary between disturbance stages are compared.

The present application belongs to the technical field of oil exploration, and particularly relates to a method for well-seismic comprehensive fine delineation of sandy conglomerate. The method comprises the following steps: combining with a reservoir configuration division method, fine delineating a vertical sedimentary structure level of the sandy conglomerate; using a seismic sedimentology analysis method, well-seismic comprehensive delineating a spatial distribution of the sandy conglomerate, and clearly defining a spatial feature of a reservoir configuration unit in a target area; establishing a parameter knowledge base of an internal structure unit of the sandy conglomerate, and predicting a favorable reservoir development position in the target area. The method combines geological, logging and seismic fine delineation methods, finds an effective combination point, and applies the combined system method to a sandy conglomerate reservoir for verification, thereby establishing an effective well-seismic comprehensive fine delineation method of the sandy conglomerate. The method effectively overcomes the problems of complex internal structure of the sandy conglomerate and unclear marks.

This application discloses a method, apparatus, equipment, and medium for predicting the evolution trend of continental shale sedimentary structures, relating to the field of geological exploration technology. The method includes: acquiring well logging data and core data of the target well section to identify the sedimentary structure type and establish a vertical sequence of sedimentary structures; performing spectral analysis on the well logging data to extract Milankovitch cycle period signals; performing Gaussian bandpass filtering and astronomical tuning on the Milankovitch cycle period signals to construct an astronomical timescale for the target well section; performing spectral analysis based on the astronomical timescale and the vertical sequence of sedimentary structures to obtain periodic change information and the matching correspondence with corresponding geological time cycle values; using Chimontocarro simulation to simulate sedimentary noise on the astronomically tuned data to obtain paleolake level change results; and establishing an evolution trend prediction model for sedimentary structure evolution combinations to invert the multi-level evolution trend of sedimentary structures in the target well section. This improves reservoir evaluation accuracy and development efficiency.

In one embodiment, a method directed to automatically separating geological markers associated with well log data includes receiving well log data captured by one or more sensors disposed within a wellbore of a well. The method further includes generating clusters of one or more geological markers associated with the well log data. The method further includes executing one or more of: initiating generation of a visualization of the clustered one or more geological markers on a display device such that the visualization indicates space-time structural transitions of a geological formation associated with a well; mapping and correlating facies data that indicate sedimentary structure data, fossil data, or geological associations of the geological formation; determining geological trap data that indicate a sealed geologic container of the geological formation that holds fluid and is associated with the well; or projecting reservoir trends of a reservoir to which the well is connected.

The invention provides a water tank granularity and mineral characterization method based on laser scattering spots and a Raman spectrum, and belongs to the technical field of underwater detection. A seabed fan deposition process is reproduced and a deposition body is generated; a multi-mode optical detection system integrating laser ranging, elastic scattering imaging and Raman spectrum acquisition is adopted, a probe scans along a preset path, and bottom type tracking and maximum signal acquisition are realized in combination with real-time bottom type feedback and a dynamic optical compensation mechanism; performing multi-scale denoising and feature enhancement on the scattering image and the Raman spectrum through discrete wavelet transform; particle size distribution is inversed based on a space contrast method, and a three-dimensional particle size diagram is generated in combination with Kriging interpolation; pure mineral Raman signals are extracted through spectrum baseline correction and water interference deduction, and high-precision recognition of mineral components is achieved through spectrum library matching; and establishing a granularity-mineral correlation model through clustering analysis and partial least squares regression. The invention provides a systematic and reliable method for collaborative analysis of the sedimentary structure and the material composition.

This invention belongs to the field of geological sedimentology, specifically a method for identifying high-quality lithofacies of storm formation based on multi-source data integration. A: Data Acquisition and Preprocessing; S1: Data Acquisition and Confirmation, i.e., using a convolutional neural network (CNN) to automatically identify "Bouma-like sequence" features in the core based on core samples, outcrops, well logging curves, and well logging data, outputting storm depositional sample information; S2: Using deep learning (U-Net) combined with sedimentary structures to automatically classify lithofacies in the core images; S3: Using time series analysis (LSTM or Transformer) to automatically identify "box-shaped" (storm dam body) and "bell-shaped, finger-shaped" (storm dam side edge) curve features. This invention establishes a high-quality lithofacies identification model by integrating multi-source data, greatly improving the accuracy and efficiency of identification, and providing a scientific basis for evaluating oil and gas reservoirs in storm depositional environments.

A novel method for quantitative reconstruction of carbonate rock stratum sequence lithofacies paleogeography belongs to the technical field of petroleum geological exploration, and comprises the following steps: S1, preparing data and standardized programming diagram basic data; s2, comprehensively determining a sedimentary structure pattern through seismic information; s3, determining a sequence framework and a dominant phase through multi-information fusion; s4, determining main single factors through rock type statistical analysis; and S5, performing quantitative interpolation to carry out lithofacies paleogeography mapping. According to the novel quantitative sequence-dominant facies carbonate rock paleogeography research method, the real characteristics of lithofacies paleogeography are recovered from the two aspects of accuracy and isochronism, a field outcrop profile is more applied by predecessors, and as the richness degree of drilling data is increased, the real characteristics of the lithofacies paleogeography can be recovered. According to the method, the advantages of a quantitative lithofacies paleogeography method, a sequence-lithofacies paleogeography method and a structure-lithofacies paleogeography method are fully absorbed, and the respective limitations are overcome.

The invention provides a gravity flow type discrimination method and device for a continental fault lake basin, and relates to the technical field of geological exploration. The gravity flow type discrimination method for the continental fault lake basin comprises the following steps: acquiring three-dimensional seismic data, core data and logging data of a target area; the three-dimensional seismic data comprises a seismic reflection structure and a seismic slope; the core data comprises lithofacies characteristics, sedimentary structures, sedimentary sequences and particle size distribution characteristics; determining the gravity flow type of the target area based on the three-dimensional seismic data, the core data, the logging data, the flood type gravity flow characteristics and the slump type gravity flow characteristics; verifying the gravity flow type based on deposition process simulation, seismic inversion verification and reservoir microscopic verification; and in response to verification passing, determining the gravity flow type as a target gravity flow type of the target area. Therefore, the defects of single parameter and insufficient verification in a traditional discrimination method are overcome, and the discrimination efficiency and accuracy of the gravity flow type are remarkably improved.

The invention provides a method for determining favorable lithofacies combination of continental facies mixed-volume shale. The method comprises the following steps: S1, subdividing small layers according to logging curve characteristics and stratum thickness; s2, dividing lithology types by using X-diffraction total rock test analysis data; s3, utilizing a special sedimentary structure to divide lithofacies combination types; s4, analyzing three-dimensional reservoir features and two-dimensional reservoir features of different lithofacies combinations; and S5, combining the static geological parameters with the dynamic development parameters, and determining favorable lithofacies combination. According to the method, a special sedimentary structure is used as a main division basis, and an X-diffraction total rock experiment is used for testing and analyzing total rock mineral components to divide lithofacies combination; three-dimensional and two-dimensional means are combined to carry out reservoir multi-dimensional full-scale evaluation, and favorable lithofacies combinations of the reservoir are divided; and the favorable lithofacies combination is finally defined by combining the static geological parameters and the dynamic development parameters, so that the accuracy, effectiveness and comprehensiveness of determining the favorable lithofacies combination of the continental facies mixed shale are improved.

The application discloses a method for demarcating lithofacies assemblage limits of shale series in a terrestrial lake basin, and belongs to the technical field of exploration and evaluation. The method comprises the following steps: obtaining the lithological characteristics of samples by core observation and analysis on the shale series rock samples; obtaining the total organic carbon content and free hydrocarbon content by organic carbon determination and rock pyrolysis analysis experiments on the shale series rock samples, and determining the organic matter abundance comprehensive designation; determining the sedimentary environment of the samples according to the total organic carbon content and the lithological characteristics of the samples; obtaining a relationship diagram of the shale continuous thickness and the free hydrocarbon content and a relationship diagram of the shale thickness proportion in the formation thickness and the free hydrocarbon content; and establishing the lithofacies assemblage division standard through the above indexes, and performing longitudinal lithofacies assemblage division on the shale series rock samples. The method can effectively distinguish the lithofacies through comprehensive analysis on the lithology, mineral composition, organic carbon content and sedimentary structure.

The utility model discloses a hydrate reservoir-forming sedimentary structure coupling simulation structure and a reaction experiment module, and the inner cavity of the reaction experiment module is provided with the sedimentary structure coupling simulation structure. The sedimentary structure coupling simulation structure comprises a monoclinic sedimentary stratum simulation structure, a sedimentary structure transition simulation structure, a mesh fault simulation structure, a fault anticline simulation structure and a stability domain simulation structure; the net-shaped fault simulation structure is located at the fracture position of the fracture and anticline simulation structure, and the fracture and anticline simulation structure is connected with the net-shaped fault simulation structure; a low-temperature water bath circulation structure in the stability domain simulation structure is arranged in the monoclinic sedimentary stratum simulation structure; the monoclinic sedimentary stratum simulation structure, the sedimentary structure transition simulation structure, the mesh fault simulation structure and the fault anticline simulation structure are all provided with filling particles. The utility model provides a feasible simulation mode aiming at the coupling effect of construction and sedimentary elements under the mainland edge background, a temperature field and a pressure field, and can be widely applied to the technical field of geological exploration.