190 results about "Reservoir evaluation" patented technology

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 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 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 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 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 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 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.

This invention provides a fluid identification method, device, processor, and machine-readable storage medium, relating to the field of oil and gas reservoir evaluation. The method includes: determining the porosity correction coefficient for escaping fluids in multiple full-diameter core sections; determining the apparent total porosity, two-dimensional nuclear magnetic resonance T1-T2 spectra, and porosity of each fluid component in the full-diameter core; determining the porosity of the fluid distribution range, the porosity of the bound fluid distribution range, the porosity of the movable fluid in vacuum-saturated water, and the total porosity; determining the escaping fluid porosity correction coefficient based on the total porosity, apparent total porosity, and bound water porosity of the full-diameter core, and establishing a porosity correction coefficient model based on the correction coefficients of multiple core sections, and determining the total porosity based on the model; and determining the oil and gas saturation and water cut of the entire well section core using the apparent total porosity, total porosity, water saturation, and porosity of each fluid component. Through this invention, the porosity of gas reservoir cores can be accurately measured, fluid properties can be accurately identified, and quantitative evaluation can be performed.

The invention discloses a closed coring saturation correction system, which relates to the technical field of oil and gas reservoir evaluation and comprises a movable water degassing correction model based on a nuclear magnetic simulation experiment and a bound water volatilization correction model based on a volatilization experiment. The method comprises the following steps: determining movable water loss through a nuclear magnetic simulation experiment, and establishing a movable water degassing correction model with permeability, movable water saturation and time; determining irreducible water loss through a volatilization experiment, and establishing an irreducible water volatilization correction model with permeability, irreducible water saturation and time; through combination of the movable water degassing correction model and the irreducible water volatilization correction model, more accurate correction of the closed coring water saturation is realized.

The invention belongs to the technical field of oil and gas field exploration, and provides a target reservoir evaluation method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a plurality of control factors affecting the reservoir development of a target reservoir, and generating a plurality of geological information planar graphs related to the plurality of control factors; performing gridding processing on any one geological information plane graph in the plurality of geological information plane graphs to obtain a plurality of geological information standardized plane graphs; performing data fusion processing on various geological data acquired from the geological information standardized planar graphs to generate a probability graph of target reservoir development; and generating a corresponding evaluation graph based on the probability graph, and evaluating the target reservoir based on the evaluation graph. Through the evaluation method, objective and accurate evaluation can be performed on the target reservoir based on the evaluation graph finally generated based on the probability graph.

The invention provides an intelligent sandstone slice identification system and an intelligent sandstone slice identification method, and belongs to the technical field of geological exploration. In the system, a data analysis module integrates three core algorithms: a data enhancement module adopts an improved conditional cycle consistency generative adversarial network to solve the problem of scarcity of rock samples; the multi-modal feature understanding module fuses image visual features and petrology text features by using a cross-modal attention mechanism; and the intelligent identification module completes recognition and classification of mineral composition, structure construction and diagenesis in parallel based on a multi-task learning architecture. The method comprises a system training stage and a sample identification stage. According to the method, the model generalization ability is improved by generating a large number of synthetic samples, the geological rationality of the identification result is enhanced through multi-modal semantic fusion, efficient, accurate and objective automatic intelligent identification of the sandstone slice is realized, and a key technical support is provided for reservoir evaluation in the field of petroleum geology.

The application discloses a kind of shallow shale gas preservation condition microcosmic evaluation method, the method obtains blocky rock sample from study target layer, and carries out equal division, and is prepared into the sample of different water saturation;Through the results of several groups of different temperature and saturation conditions under the methane high-pressure adsorption experiment, and interpolation, the methane theoretical maximum adsorption amount under the condition of any formation temperature, water saturation and pressure can be obtained.Then compare with the gas content of present target layer, finally evaluate the preservation condition of the target reservoir on site.The application has a positive effect on shale gas production planning and reservoir evaluation.

The present application relates to the technical field of testing or analyzing materials by means of determining chemical or physical properties of materials, in particular to an in-situ characterization method and system for shale reservoir micro-nanopore gas adsorption behavior, the method comprising using non-destructive shale samples, introducing gas in a high-pressure high-temperature reaction kettle simulating formation environment, synchronously collecting Raman spectrum and small-angle / ultra-small-angle X-ray scattering data, and realizing in-situ characterization through multi-scale data fusion analysis.The present application realizes in-situ, non-destructive, high-resolution and multi-component dynamic characterization of shale micro-nanopore gas adsorption behavior under real formation conditions, improves the accuracy of reservoir evaluation, and constructs a more accurate physical and chemical model.

The invention discloses a well logging lithology identification method, device and equipment and a storage medium, and relates to the technical field of geological exploration, and the method comprises the steps: obtaining well logging parameters related to lithology changes to obtain initial well logging curves, and determining a target well logging curve from the initial well logging curves based on a target window length; performing fast Fourier transform on the target logging curve to obtain a frequency domain feature vector corresponding to the target logging curve, and performing depth feature extraction on the target logging curve by using a deep learning encoder to obtain a depth attention feature vector corresponding to the target logging curve; and performing feature fusion on the frequency domain feature vector and the depth attention feature vector to obtain a target feature, and performing classification identification on the target feature by using a preset lithology category classifier to obtain a lithology identification result. Therefore, lithology prediction can be refined, and a reliable basis is provided for geological interpretation, reservoir evaluation and oil and gas development.

This application relates to the field of drilling technology, and particularly to a flexible coring device, a flexible coring system, and a method for coring in wells. An embodiment of this application provides a flexible coring device, which includes a flexible coring cylinder, a flexible frame, and multiple articulated members. Each articulated member has a cavity, and the multiple articulated members are sequentially arranged along a first direction. Adjacent articulated members are movably connected, and the cavities of each articulated member are interconnected to form a coring channel for core movement. By using multiple articulated members, this application enables the flexible coring cylinder to bend, adapting to complex conditions such as short-radius wells, small curvature radii, and small wellbore diameters. This improves the flexibility of the flexible coring device in short-radius wells, allowing for efficient and stable coring operations. Furthermore, it can reveal detailed information such as near-wellbore sand body connectivity, residual oil distribution, and contamination zone characteristics, improving the accuracy of reservoir assessment.

The application discloses a kind of based on multi-scale attention prototype network small sample core image classification method.For the classification dilemma caused by few core samples and difficult to label, the application proposes a prototype measurement scheme that fuses multi-scale features and attention enhancement.The method uses a differentiated enhancement strategy, uses pre-trained ResNet-18 as the backbone network, extracts shallow and middle layer features, and embeds CBAM modules in the deep layer to calibrate spatial and channel weights and strengthen key texture focusing.The three layers of features are cascaded and fused to construct an AttnMS-ProtoNet model.During classification, the N-way K-shot sampling is used to simulate the small sample scenario, the class prototype is generated by calculating the mean of the support set, and the learnable temperature coefficient is introduced to dynamically scale the normalized cosine similarity and adaptively expand the class boundary.Model training is completed through label smoothing and stepwise learning rate.This method effectively alleviates overfitting and significantly improves the accuracy of core image classification, providing technical support for oil exploration and reservoir evaluation.

The invention relates to the technical field of reservoir evaluation, in particular to a method, a system and a terminal for predicting the productivity of a low-resistivity oil layer with a deep complex pore structure, and the method comprises the steps: determining the lower limit value of the productivity of a reservoir; obtaining the yield per meter of the reservoir according to the reservoir productivity lower limit value; dividing reservoir intervals, and establishing a productivity strength calculation model according to the divided intervals; the yield per meter and the productivity strength calculation model are intersected to establish a yield per meter calculation model; and accumulating the single-meter yields in the single-meter yield calculation model to obtain a reservoir productivity prediction model, and predicting the productivity of the low-resistivity oil layer with the deep complex pore structure through the reservoir productivity prediction model. According to the method, conventional nuclear magnetic resonance logging information and formation testing information are utilized, on the basis of reservoir productivity sensitive factor analysis, the productivity prediction model is constructed through statistical analysis, the yield of the low-resistivity oil layer of the deep complex pore structure is predicted, and the prediction precision of the yield of the oil layer is effectively improved.

This invention discloses a method, apparatus, electronic device, and storage medium for standardizing well logging curves. The method includes: acquiring well logging curves and data from wells drilling in the target formation of the study area; identifying and determining the tight carbonate layers in the target formation based on the data and well logging curves; using multiple sets of tight layers from a single well as standard layers, determining the frequency distribution histogram of the standard layers, and determining the curve characteristic values ​​of the standard layers based on the frequency distribution histogram; calculating the average of the curve characteristic values ​​to obtain the standard value of the standard layer; and standardizing the well logging curves of all wells using a translation method based on the standard value to obtain the target well logging curve. This technical solution can perform fine standardization processing on formations with strong heterogeneity and no stable, continuous distribution of standard layers, obtaining high-quality well logging curves that meet the requirements of reservoir inversion, improving the accuracy of reservoir prediction using multi-well well logging curves, and is of great significance for reservoir evaluation of heterogeneous formations.