235 results about "Reservoir evaluation" patented technology

The invention relates to the technical field of reservoir evaluation, in particular to a deep learning-based reservoir evaluation model construction method and system. The method comprises the following steps: acquiring logging data and core analysis data of a target work area, and respectively carrying out abnormal value processing and missing value filling to obtain complete logging data and complete core data; calculating reservoir pore structure parameters based on the complete core data; and inverting the macroscopic porosity of the reservoir based on the complete logging data. According to the method, the accuracy, the stability and the robustness of reservoir evaluation are remarkably improved by fusing the core data and the logging data and combining the pore structure parameters, the macroscopic porosity and the geological attention mechanism, the problems of data missing and small samples are solved, and the interpretability and the geological consistency of the model are enhanced.

The invention discloses a reservoir identification method fusing seismic attribute inversion and ancient karst form modeling, and relates to the technical field of reservoir identification and modeling, and the method comprises the steps: carrying out the multi-modal fusion processing of a standardized image data set through an image sensor, obtaining the multi-modal fusion image data, executing the high-precision texture sampling and space alignment processing, and obtaining a multi-modal image data set; generating a cross-modal image fusion matrix; inputting the cross-modal image fusion matrix into an image topological graph structure construction process, establishing an image block node relationship and a spatial connection edge weight, and generating an ancient karst topological graph; and coupling the karst earthquake joint matching graph with the comprehensive reservoir attribute data, establishing an effective reservoir evaluation model, and generating a multi-stage reservoir prediction layer set through weighted fusion and multi-parameter spatial analysis. By constructing an ancient karst topological graph and a karst earthquake joint matching graph, spatial modeling of a complex karst structure and cross-modal correlation analysis of earthquake abnormal attributes are realized.

The invention relates to a method, a device and equipment for analyzing in-situ formation fracture porosity of mixed rock. Comprising the steps of obtaining original data of a plurality of layers in a target block; taking out a first rock core sample from each layer of the target block, and performing experimental analysis on the first rock core sample of each layer to determine a target layer; taking out a second core sample from the target horizon, and performing a triaxial compression test on the second core sample to obtain a stress index; according to the original data and the stress index, the stratum fracture porosity of the target layer is calculated, the stratum fracture porosity is used for guiding workers to evaluate the real underground in-situ fracture porosity of the reservoir, and therefore an oil and gas reservoir exploitation plan of the target layer is made. The stratum fracture porosity calculated by the method represents the fracture porosity of the target horizon in the target block and represents in-situ characteristics in the stratum, so that the accuracy of reservoir evaluation is improved. A worker can formulate an oil and gas reservoir exploitation plan according to the formation fracture porosity, and the oil and gas reservoir yield is improved.

The invention discloses a rock permeability testing system in a high-temperature and high-pressure environment and a using method thereof, and belongs to the technical field of geothermal development or coal in-situ gasification mining. The test system is composed of a stress loading system, a test kettle assembly and a magnetic particle imaging system. When in use, the stress loading system and the test kettle assembly provide conditions such as high temperature, high pressure, seepage fluid and the like for a test piece; and detecting the spatial distribution state of the nano magnetic induction particles added in the seepage fluid through a magnetic particle imaging system to observe the pore and crack distribution characteristics in the test piece or detecting the nano magnetic induction particles added in the pollutant solution to observe the pollutant migration condition. The test system is scientific in design, simple in structure and easy to operate and maintain, can monitor pore fracture distribution and pollutant migration conditions in the test piece in real time under high-temperature and high-pressure conditions, provides accurate dynamic observation data, and provides important technical support for reservoir assessment and optimization in a complex environment.

The invention discloses a salt lake carbonate rock multi-parameter quantitative classification and reservoir evaluation method, and relates to the technical field of oil-gas exploration. The method comprises the following steps: selecting a key well in an exploration block, collecting a plurality of salt lake carbonate rock samples, preparing an analysis sample under an anhydrous condition, quantitatively measuring a salinity parameter, a mixing index and a diagenesis strength parameter by utilizing the analysis sample, and determining a salinity code, a mixing code and a diagenesis phase code. And naming the salt lake carbonate rock based on the salinity code, the mixed product code and the lithogenous phase code, directly evaluating the salt lake carbonate rock reservoir according to a naming result, and performing single well comprehensive evaluation on the salt lake carbonate rock reservoir. According to the method, the influence of salinity, mixed accumulation and diagenesis strength on formation and evolution of the salt lake carbonate rocks is fully considered, accurate division of the types of the salt lake carbonate rocks is achieved, the reservoir naming result is directly associated with reservoir evaluation, and technical support is provided for standardized evaluation of the salt lake carbonate reservoir.

The invention discloses a tight sandstone reservoir evaluation method and system based on a knowledge graph and a storage medium, relates to the technical field of geological exploration and development, and aims to solve the problems of data splitting and model staticizing existing in an existing evaluation method. Comprising the steps that S100, tight sandstone reservoir evaluation data are collected, an ontology knowledge base is constructed, and a tight sandstone reservoir domain ontology layer is constructed based on knowledge and the incidence relation between the knowledge; step S200, a tight sandstone reservoir evaluation model is constructed, the evaluation model comprises a knowledge extraction module and a knowledge reasoning module, and the knowledge extraction module is used for performing triple extraction on the entity relationship marked by the tight sandstone reservoir sequence, and constructing a tight sandstone reservoir knowledge graph combined with the entity relationship; the knowledge reasoning module is used for sensing a convolutional network based on a structure embedded by a rule, and is used for carrying out collaborative reasoning of multiple tasks; and S300, based on the tight sandstone reservoir evaluation model, performing multi-task collaborative reasoning of the tight sandstone reservoir.

The invention relates to a lithofacies intelligent pattern classification method based on a conditional diffusion probability model, and belongs to the technical field of deep learning, pattern recognition and big data processing. Comprising the following steps: step (1), collecting and preprocessing big data; step (2), constructing a conditional diffusion probability model; step (3), model training and parameter optimization; step (4), generating a category balance sample; (5) enhancing data quality evaluation; and (6) training and verifying the pattern classification model. According to the method, shale lithofacies data enhancement and intelligent mode classification based on the conditional diffusion probability model and the deep learning technology are realized, the lithofacies identification problem under the condition of training set category imbalance is effectively solved, and the minority class lithofacies identification precision and the overall classification performance of the model are remarkably improved; and a reliable technical method is provided for marine shale oil and gas reservoir evaluation and sweet spot prediction.

The invention discloses a logging depth correction method and system and a computer readable storage medium, and the method comprises the following steps: determining a reference well and at least one correction well needing depth correction in a plurality of wells under the same oil field pressure system; establishing a reference well pressure trend model according to the measurement data of the reference well; establishing a corrected well pressure trend model according to the measured data of the corrected well; according to the reference well pressure trend model and the correction well pressure trend model, a depth correction value is obtained through analysis; and correcting the measured depth value of the correction well according to the depth correction value. According to the method, the precision of depth measurement can be improved, the precision of oil and gas reservoir evaluation is further improved, and the method is high in operability.

The invention provides a shale reservoir grading evaluation method. The shale reservoir grading evaluation method comprises the following steps: acquiring petrology, geochemistry and pore structure parameters of different shale reservoirs by utilizing at least two experimental test methods; calculating a multi-scale fractal parameter of the pore structure of the shale reservoir; according to the obtained petrology, geochemistry, pore structure and multi-scale fractal parameters, reservoir evaluation is conducted, and shale reservoir grading is completed. According to the method, shale reservoir petrology, geochemistry and pore structure parameters are obtained by comprehensively utilizing multiple means, pore structure multi-scale fractal parameters are calculated, reservoir characteristics are evaluated by combining multiple types of parameters, and reservoir grading evaluation is completed; the problem that a single test method or a single calculation method cannot systematically analyze the pore structure of the reservoir, divide the type of the reservoir and carry out reservoir evaluation is avoided, and the accuracy, effectiveness and comprehensiveness of grading evaluation of the shale reservoir are improved.

This application relates to the field of data technology and discloses an intelligent processing method for mud logging data. The method includes: collecting data through multi-source mud logging equipment and preprocessing to form a result set; identifying and classifying formation characteristics according to the result set; analyzing oil and gas parameters based on the formation atlas and the result set; establishing an early warning mechanism by identifying risks using the oil and gas evaluation table and the result set; evaluating reservoir physical properties according to the oil and gas evaluation table and the early warning mechanism; integrating the formation atlas, the oil and gas evaluation table and the reservoir report to reconstruct the geological structure and predict the enrichment area. This application realizes the full-process intelligent processing from the acquisition and preprocessing of multi-source heterogeneous mud logging data to formation identification, oil and gas evaluation, drilling risk early warning, reservoir evaluation and oil and gas reservoir description, overcomes problems such as data spatio-temporal mismatch, isolated parameter analysis, strong subjectivity in evaluation, and lagging early warning in traditional methods, and improves the efficiency, accuracy and systematicness of mud logging data processing.

The invention provides a rock sample pore wettability evaluation method, device and system and electronic equipment, relates to the technical field of reservoir evaluation, and aims to solve the problem that the wettability of different pores of rock cannot be represented. The evaluation method comprises the following steps: acquiring a first three-dimensional grayscale image of a rock sample in a normal state, a third three-dimensional grayscale image of a wet-phase fluid filled with a tracer agent in the rock sample, and a fourth three-dimensional grayscale image of the wet-phase fluid and a non-wet-phase fluid filled with the tracer agent in the rock sample; and determining the pore wettability of the rock sample according to the first three-dimensional grayscale image, the third three-dimensional grayscale image and the fourth three-dimensional grayscale image. According to the evaluation method provided by the invention, the high-resolution three-dimensional imaging technology is combined with the distribution of the interface form of multiphase fluid seepage in a stable state, so that the wetting state in each rock sample pore can be quickly evaluated one by one, and the evaluation method has important significance on exploring the influence of different wetting conditions on fluid properties.

The invention relates to the technical field of reservoir assessment, and discloses a gas storage geologic body stability intelligent prediction method considering configuration heterogeneity, and the method comprises the following steps: 1, reservoir configuration unit division and feature extraction; 2, carrying out coupling analysis on geomechanical parameters and a crustal stress field; step 3, carrying out correlation modeling on configuration heterogeneity and mechanical characteristics; and 4, training and optimizing the stability intelligent prediction model. According to the method, deep coupling characterization of geologic configuration heterogeneity and mechanical response is achieved, and the physical basis and precision of stability prediction are remarkably improved.

The invention provides a sandstone reservoir oil-water layer logging identification method and system, and belongs to the field of reservoir evaluation. According to the method, an identification plate is obtained according to oil testing and production testing data and gas logging data, and then the fluid type of a reservoir to be identified is identified through the identification plate. According to the method, a conventional gas logging technology is adopted, new technical means and measurement time do not need to be added, the fluid type of the sandstone reservoir can be simply, conveniently and rapidly recognized based on deep excavation of gas logging data, the recognition coincidence rate is increased, a basis is provided for exploration and development decision and benefit development, and the method has the advantages of being economical, real-time, accurate and the like and has good application prospects. The popularization and application prospects are wide.

The invention relates to the technical field of greenhouse gas emission reduction, and discloses a gas injection method for improving coal seam carbon dioxide sequestration efficiency, which comprises the following steps: S1, reservoir evaluation and well pattern deployment; s2, multi-slug alternate injection is carried out; s3, intermittent injection-production operation is carried out; s4, long-term storage monitoring; and S5, stability maintenance measures are taken. According to the method, through an innovative'carbon dioxide-nitrogen-carbon dioxide 'multi-slug alternate injection process and an optimized well pattern deployment strategy, the problems of gas fingering and fluid channeling caused by strong heterogeneity of the coal seam are effectively solved, and particularly, by means of the low viscosity and weak adsorption characteristics of the nitrogen buffer slug, the coal seam gas density is improved, and the coal seam gas density is improved. The carbon dioxide preferentially enters a high-permeability channel and forms a mobility control barrier, so that the subsequently injected carbon dioxide is forced to turn to a medium-low-permeability area, and the swept volume and the contact area of the carbon dioxide in the coal seam are obviously enlarged.

This invention provides a method, system, and computer equipment for predicting the maturity of shale and mudstone reservoirs through well logging. By analyzing the total porosity and total organic carbon content of shale and mudstone cores from different regions, this invention obtains a mathematical relationship between relative porosity and total organic carbon content. This mathematical relationship reflects the porosity-enhancing efficiency of organic matter and reveals a close relationship between this efficiency and vitrinite reflectivity, which reflects the thermal maturity of organic matter. As maturity increases, the porosity-enhancing efficiency of reservoir organic matter decreases. Therefore, the maturity of shale and mudstone reservoirs can be predicted and evaluated based on the porosity-enhancing efficiency of organic matter. Based on this, this invention establishes a "three-parameter" chart using data on total porosity, total organic carbon content, and vitrinite reflectivity of shale and mudstone from different regions. By processing the data in the area to be tested, the mathematical relationship between relative porosity and total organic carbon content of the shale and mudstone reservoir is obtained. Combined with the "three-parameter" chart, the organic matter maturity can be determined, providing a reference for reservoir evaluation and prediction.

The invention relates to a thin interbed clay mineral content prediction method based on an RBF neural network, and the method mainly improves the longitudinal resolution through the inversion of the RBF neural network on the basis of multiple attributes, and compared with the conventional research, the method directly uses the seismic attributes, such as amplitude, as the input to learn a target curve, and improves the prediction efficiency. According to the method, the seismic frequency division reconstruction data body and the inversion body are selected as input, so that the longitudinal resolution and the well coincidence rate are greatly improved; in addition, the inversion body is used as input, so that the problem that neural network inversion geological laws are poor in previous research is solved, and an important basis can be provided for reservoir assessment and development; examples prove that the method disclosed by the invention is higher in precision of inverting the clay mineral content compared with a simulation method directly using waveform indication, and is suitable for reservoir parameter prediction of a thin interbed.

The invention discloses a thin-layer Jurassic oil reservoir evaluation method based on economic limit oil reservoir thickness. The thin-layer Jurassic oil reservoir evaluation method comprises the steps that S1, a thin-layer Jurassic oil reservoir productivity evaluation model is established according to oil reservoir geological parameters; designing development schemes of two sets of development well patterns; s2, analyzing the productivity influence factors by using the evaluation model, and predicting the accumulated oil production in the next 15 years during development through the two well pattern mining schemes; s3, economic benefit evaluation is carried out, and whether the mining economic value exists or not is judged; and S4, respectively calculating financial net present value rates of the two schemes, comparing the financial net present value rates, and selecting a mining mode with a relatively large value. According to the thin-layer Jurassic oil reservoir evaluation method based on the economic limit oil reservoir thickness, the economic limit oil reservoir thickness under the condition of different productivity influence factors in the thin-layer oil reservoir development process is determined, and formulation of oilfield development technical policies is further guided; the problem that an existing thick oil layer development technology policy is poor in thin layer oil reservoir adaptability is solved.

The invention relates to the technical field of shale oil exploration and development, in particular to a lamellar fracture secondary classification shale reservoir evaluation method. The method comprises the following steps: determining a target research area, respectively identifying brittle minerals and clay minerals of a shale sample in the research area, calibrating a shale deposition scale and a shale diagenesis scale, dividing lamellar fractures in the research area into deposition lamellar fractures and diagenesis lamellar fractures according to the shale deposition scale and the shale diagenesis scale, the method comprises the following steps: combining a sedimentary lamella fracture with a plurality of diagenetic lamella fractures to construct a lamella body, firstly calculating the lamella body thickness, the lamella body spacing, the lamella body penetration ratio and the lamella body curvature, then calculating an imbibition capability index, a seepage capability index and a development capability index, and finally evaluating the lamella development degree of the shale reservoir according to three obtained evaluation indexes. According to the method provided by the invention, the two-level division of the lamellitic seam level is realized, the lamellitic body is also constructed, and clear guidance can be provided for shale oil exploration and development.

The invention belongs to the technical field of geophysical exploration and oil and gas reservoir evaluation, and particularly relates to a heterogeneous dolomite reservoir fractal rock physical modeling method. The method comprises the following steps: data acquisition and processing: acquiring ultrasonic velocity and attenuation data, and acquiring acoustic logging data and post-stack seismic data of a target layer; constructing a fractal rock physical model; generating a multi-band rock physical drawing board; drawing board correction and reservoir parameter quantitative prediction. The fractal dimension serves as a clear and predictable key parameter to be introduced into the dolomite rock physical model for the first time, the limitation that a traditional model can only predict the pore volume (porosity and fracture content) but cannot describe the pore structure form is broken through, the precision and dimension of reservoir physical property prediction are improved, and the reservoir physical property prediction accuracy is improved. By combining an infinite heavy pore medium model with a fractal theory, the established model can simulate propagation of waves in an actual complex porous medium more truly, spanning from two dimensions to three dimensions is realized, and multiplicity of reservoir prediction is greatly reduced.

The application discloses a method for testing lost gas in shale gas content based on a depletion experiment device, and relates to the technical field of oil and gas field development.The depletion experiment device comprises a core holder, a heating jacket, a confining pressure pump, a gas inlet assembly, a gas outlet assembly, a vacuum pumping device, a gas reference container and an arc-shaped radiation slot plate.The application fully utilizes the characteristic that the horizontal permeability of shale is much greater than the vertical permeability, designs a test device fully consistent with the real environment, and can make methane truly saturate the shale core and greatly reduce the time required for saturating the shale core on one hand, and can directly test the lost gas part in the shale gas content on the other hand, thereby improving the test efficiency and the accuracy of the test results, and providing strong evidence support for shale gas reservoir evaluation and reserve calculation.

The invention provides a tight gas reservoir gridding evaluation method, system and device and a storage medium, and the method comprises the steps: obtaining dynamic and static data of a target block, the dynamic and static data comprising geological data and production dynamic data; geological reserve gridding parameters are determined based on the geological data, and the geological reserves are gridded; determining the dynamic reserves of each well in the target block based on the production dynamic data, and meshing the dynamic reserves of each well; calculating the unused reserves and the ratio of the dynamic reserves to the static reserves of the target block grid by grid based on the geological reserve gridding and the dynamic reserve gridding of each well; and obtaining a gas reservoir evaluation result based on the unused reserves and the dynamic and static reserve ratio. According to the method, fine evaluation and infilled well arrangement of the tight gas reservoir are achieved, well pattern infilled evaluation refinement is high, calculation is convenient, and the method has great significance in development evaluation of the tight gas reservoir, development scheme compiling, recovery ratio improving countermeasure making and the like.

The invention discloses a complex structure stratum while-drilling azimuth electromagnetic wave logging parameterization inversion method, and belongs to the field of oil exploration and development. The method comprises the following steps: s1, modeling a complex geologic structure, constructing a 2D complex geologic model, and parameterizing the 2D complex geologic model; s2, analyzing response characteristics of the 2D complex geological model according to the 2D complex geological model established in the s1, and carrying out influence factor and sensitivity analysis; s3, obtaining observation data according to response characteristics of s2, and constructing an objective function; and s4, in combination with s2 and s3, performing inversion on the parameterized 2D complex geological model by using a PT-MCMC inversion method to realize fine reconstruction of the complex stratum. According to the method, fine reconstruction of the complex stratum is achieved, good inversion precision is achieved, and the characterization capacity and the calculation efficiency are both considered. The method provides support for real-time geosteering, reservoir evaluation, layer interface prediction and the like of oil and gas fields.

The invention provides a rock water content obtaining method based on one-dimensional nuclear magnetism, pyrolysis and extraction experiments, and relates to the field of geological prospecting, the method comprises the following steps: extracting hydrocarbon-containing fluid in a rock sample by using an oil-water amphiphilic solvent; carrying out a rock pyrolysis experiment on the sample after extraction to obtain an extraction advance value, an extraction advance value and a post-extraction value, and calculating the hydrocarbon content of the sample; carrying out a one-dimensional nuclear magnetic resonance experiment of the pre-extracted sample to obtain a pre-extracted nuclear magnetic resonance signal; carrying out a one-dimensional nuclear magnetic resonance experiment on the extracted sample to obtain an extracted nuclear magnetic resonance signal; acquiring the fluid content of the sample according to the nuclear magnetic resonance signal before extraction and the nuclear magnetic resonance signal after extraction; and calculating the water content of the sample according to the hydrocarbon content and the fluid content. The technical scheme of the invention is suitable for reservoir evaluation, resource quantity calculation, reservoir fluid monitoring in the development process and other scenes.

The invention relates to the technical field of fault type oil and gas reservoir evaluation, in particular to a fault rock compaction diagenesis burial depth determination method and device based on the shale content of surrounding rock, and the method comprises the steps: obtaining fault rock and surrounding rock of a target layer in a research area and burial depth related parameters; a fault rock compaction diagenesis degree index is determined according to the fault rock and burial depth related parameters, and a surrounding rock compaction diagenesis degree index is determined according to the surrounding rock and burial depth related parameters, or after the surrounding rock shale content in the surrounding rock and burial depth related parameters is replaced with the fault rock shale content, the surrounding rock compaction diagenesis degree index is determined according to the fault rock shale content; and drawing a relational graph of the compaction diagenesis degree index of the surrounding rock and the compaction diagenesis burial depth of the surrounding rock, projecting the compaction diagenesis degree index of the fault rock into the relational graph, and determining the compaction diagenesis burial depth of the fault rock. The method breaks through the limitation of the existing method for determining the fault rock compaction diagenetic burial depth technology, and can provide an effective means for accurate discovery, exploration and deployment of oil and gas in the oil and gas containing basin fault type oil and gas reservoir.

The application discloses a kind of multi-region reservoir potential effective quantification evaluation methods, it includes the following steps: step 1, on the basis of interpretive achievement data, respectively using DSG Seismic Attribute Generation module and OpenGS Openinversion module of module calculation relative amplitude data body and relative wave impedance data body, and carry out construction smoothing;Step 2, in combination with well data, main fracture characteristics and reservoir attribute, in the region of reservoir target obvious and well data, reservoir and T74 layer relative amplitude and relative wave impedance inversion ratio plane calculation and point position statistics are carried out;Step 3, using EXCEL to calculate the ratio between reservoir and T74 layer, and draw the ratio trend chart between the two layers in the study area.The application can intuitively and effectively find out the distribution of the study area reservoir, which solves the problem of previous reservoirs being limited to qualitative analysis and cannot be quantified, breaks the status quo of previous qualitative analysis of reservoir evaluation parameters, and is simple to operate and has strong popularization.

This invention discloses a method, apparatus, equipment, and storage medium for determining the reservoir control limit of strike-slip faults. The method includes: determining oil and gas reservoir evaluation indicators for each well within a target area based on single-well test data; determining matching oil and gas reservoir evaluation indicators for each depth interval based on the oil and gas reservoir evaluation indicators for each well within the target area; wherein the depth intervals are determined based on statistical results of the drilling depths of each well within the target area; determining the correlation between the matching oil and gas reservoir evaluation indicators for each depth interval and the pre-obtained oil and gas supply depths of each well; and determining the reservoir control limit of strike-slip faults within the target area based on the correlation. This technical solution solves the problem of low reliability in determining the reservoir control limit of strike-slip faults, and can improve the accuracy of predicting the reservoir control limit of strike-slip faults while providing corresponding technical support for the selection of potential zones.

The bauxite reservoir identification method, device and computer storage medium relate to the oil and gas exploration and development technical field, and particularly relate to a bauxite reservoir identification method, device and computer storage medium, which realize accurate hierarchical identification of bauxite reservoirs through the collaborative operation of a data preprocessing module, a three-phase relative marker construction module, a feature extraction module, a parameter inversion module and a reservoir identification module in sequence; wherein the data preprocessing module, the three-phase relative marker construction module, the feature extraction module, the parameter inversion module and the reservoir identification module are sequentially connected, each module completes the whole-process bauxite reservoir identification work in the mode of algorithm coupling and data linkage, and finally outputs a visualized comprehensive columnar chart and supporting evaluation results, effectively improving the accuracy and longitudinal continuity of bauxite reservoir identification, and being suitable for the reservoir evaluation and productivity prediction links in bauxite exploration and development.

The application discloses a kind of shale oil reservoir's attenuation-elastic-electricity combined modeling and parameter prediction method, belong to geophysical exploration and oil and gas reservoir evaluation technical field.First, obtain mineral components, pore structure and elastic-attenuation-electricity full-dimensional experimental data through core experiment, determine attenuation and resistivity as high sensitivity parameter after sensitivity analysis;Again, based on Hashin-Shtrikman boundary, differential equivalent medium theory, triple-pore medium wave propagation equation, construct the acoustic and electrical rock physics model of completely consistent micro-pore structure;Finally, establish longitudinal wave impedance-attenuation coefficient-resistivity three-dimensional joint rock physics chart, after multi-band correction, simultaneously quantitative prediction reservoir porosity, shale content and fracture porosity.The application breaks through the limitation of conventional acoustic-electricity combined model, significantly reduces the multi-solution of reservoir parameter prediction, and is suitable for fine evaluation of various shale oil tight reservoirs.

The present invention provides a method for determining shale bedding fracture porosity and an oil and gas reservoir evaluation method. The method comprises: conducting a helium porosity test on a shale sample to obtain a total porosity value; conducting a low-temperature carbon dioxide adsorption experiment on the shale sample that has undergone the helium porosity test to obtain a matrix microporosity value; encapsulating the bedding plane of the shale sample that has undergone the low-temperature carbon dioxide adsorption experiment with epoxy resin, and conducting a directional mercury injection test perpendicular to the bedding plane to obtain a matrix macropore porosity value and a matrix fracture porosity value, where matrix macropores are matrix pores greater than or equal to a preset threshold; and subtracting the matrix micropore porosity value, the matrix macropore porosity value, and the matrix fracture porosity value from the obtained total porosity value to obtain a shale bedding fracture porosity value. The present invention clarifies the shale gas bedding fracture porosity, which helps evaluate shale gas exploration potential and predict favorable areas.

The invention belongs to the technical field of mineral calculation and reservoir evaluation, and particularly discloses an electric imaging logging mineral component quantitative characterization method based on porosity spectrum correction, which comprises the following steps: preprocessing original electric imaging logging data, and generating a high-density pixel image; performing probability density statistical analysis on the pixel value of each depth point in the high-density pixel image to obtain a pixel waveform spectrum; calculating the apparent porosity of each pixel point in the high-density pixel image to generate a pore spectrum; performing pore fluid influence correction on the original electrical imaging data based on the pore spectrum, performing image enhancement to generate a pure mineral pixel waveform spectrum, and performing equalization processing to obtain an imaging mineral probability map; according to mineral content data obtained through core XRD total rock analysis, an imaging mineral spectrum is subjected to quantitative calibration, and distribution cut-off threshold values and pixel point value ranges corresponding to different minerals are recognized and deduced. The method can effectively solve the calculation error caused by the influence of the traditional imaging mineral calculation fluid on mineral calculation.