127 results about "Reservoir evaluation" patented technology

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 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 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 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 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.

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.

The invention belongs to the technical field of natural gas exploration and development, and relates to a secondary gas reservoir area selection method, system, equipment and medium. According to the method, the comprehensive evaluation factor data of a plurality of secondary gas reservoirs of the destination stratum of the research block is acquired, so that the favorable target area for exploration and development can be accurately acquired. A corresponding secondary gas reservoir evaluation chart is obtained according to the secondary gas reservoir comprehensive evaluation factor data, and quantitative comparison of the physical properties of the reservoir stratum is facilitated. According to all the secondary gas reservoir evaluation maps, a region with a gas-bearing distribution intersection exceeding a threshold value is selected as a favorable target region for exploration and development, and the favorable target region for exploration and development is comprehensively obtained through various secondary gas reservoir comprehensive evaluation factors, so that the selection precision of the target region is improved; the geological basis is provided for exploration and development block optimal well position deployment and natural gas favorable enrichment area searching, and efficient and high-quality exploration and development of natural gas are boosted.

The invention relates to the technical field of coal rock gas reservoir evaluation, in particular to a coal rock gas reservoir compressibility evaluation method and system, and the method comprises the steps: obtaining and sorting multi-source reservoir comprehensive test data of a research area; constructing a prediction model between rock physical property and mechanical parameters; calculating main rock mechanical parameters of the stratum based on the prediction model; calculating the principal stress distribution of the coal rock reservoir, the top plate and the bottom plate by combining an experiment and a combined spring model; the method comprises the following steps: calculating mechanical and stress differences between a reservoir and a top and bottom plate stratum, revealing geomechanical difference characteristics, and determining main parameters influencing the compressibility of the reservoir by using Pearson correlation analysis and an XGBoost integrated learning algorithm based on gas production data of a coal and rock gas well; according to the method, the geomechanical difference between the coal rock and the top and bottom plates is comprehensively reflected, and the accuracy of the compressibility evaluation of the deep coal rock gas reservoir is improved.

The invention belongs to the technical field of shale oil and gas development, and discloses a shale oil-gas-bearing potential multi-parameter collaborative evaluation method. The method integrates six experimental technologies of nitrogen adsorption, carbon dioxide adsorption, carbon and oxygen isotope, rock pyrolysis and XRD total rock / clay analysis, and comprises the core steps of obtaining multi-dimensional data such as a pore structure, mineral composition, organic matter characteristics, an isotope ratio and the like after standardized pretreatment of a shale sample, and performing parameter correction, weight distribution and collaborative modeling to obtain a shale sample. And quantifying the oil-gas potential index and grading. The method solves the problem that traditional single parameter evaluation is insufficient in accuracy, data are comprehensive and reliable, and key technical support is provided for shale oil and gas exploration and development and reservoir evaluation.

The application discloses a shale gas reservoir characteristic prediction method, and belongs to the technical field of shale gas reservoir characteristic prediction. The method comprises the following steps: collecting and preprocessing multi-source data such as well logging, seismic, core and production dynamic; obtaining a fusion characteristic value based on a weighted fusion model; inputting the fusion characteristic into a gradient boosting decision tree model with a regularization term to predict reservoir characteristics; calculating the contribution degree of each input characteristic by using a Shapley value, and quantifying the prediction uncertainty by using a Monte Carlo method; dynamically updating the data source weight according to the prediction quality evaluation index, and forming a self-adaptive multi-source fusion closed loop. The method can realize efficient fusion and dynamic optimization of multi-source heterogeneous data, has the result explainability, credibility quantification and real-time updating capability, is high in prediction precision and stable, and is suitable for shale gas reservoir evaluation and production optimization.

This invention relates to the field of cuttings acoustic wave measurement technology, specifically an automatic positioning and sampling device and method for measuring transverse and longitudinal waves of cuttings. It includes symmetrically arranged slide rails, a synchronization unit slidably mounted on the slide rails via a sliding adjuster, a B-type acoustic wave sensor mounted on the synchronization unit, and an A-type acoustic wave sensor corresponding to the B-type sensor. A rack is provided on the back plate, and a stepper motor moves up and down along the rack. It also includes a thickness measurement module and a thickness calculation module, with the thickness calculation module connected to the sliding adjuster. The thickness measurement module, thickness calculation module, and stepper motor are all connected to an integrated control unit. Through zero-point calibration, cuttings loading and positioning, automatic sensor adaptation and adjustment, and closed-loop pressure monitoring, precise coincidence of measurement points, sensor coaxiality, and precise pressure control are achieved. This invention reduces manual intervention, improves the accuracy and efficiency of cuttings acoustic wave time difference measurement, and provides reliable data support for drilling engineering guidance and reservoir evaluation in oil exploration.

The application discloses a kind of tensor field direction constraint weighted fitting fracture prediction method and system.It includes: the original seismic data is carried out dip orientation filter processing, obtains filtered seismic data body;The filtered seismic data body is carried out eigenvalue coherence analysis, obtains coherence volume, and the coherence volume is carried out coherence enhancement processing, obtains enhanced coherence volume;Based on enhanced coherence volume, using tensor direction constraint vector ant colony tracking algorithm, automatically track fracture strike, obtain fracture tracking result;Based on fracture tracking result, construct gradient structure tensor field, use the direction information of gradient structure tensor field to carry out anisotropic Gaussian weighted fitting, obtain the quantitative description result of fracture.The application is through with tensor field direction information as unified constraint throughout fracture prediction whole process, realizes the quantitative description of small scale, low density fracture, and the coincidence rate of prediction result and disclosed fracture area reaches more than 80%, provides reliable basis for mine safety exploitation and reservoir evaluation.

The invention discloses a nuclear magnetic resonance rock physical parameter uncertainty intelligent quantification method and device, equipment and a medium, and relates to the technical field of rock physics and geophysical logging, and the method comprises the steps: generating a probability distribution model based on a mapping relation between echo data of a reservoir and a spectrum; performing random disturbance on the spectrum to obtain a candidate spectrum, calculating a candidate spectrum matching degree and a spectrum matching degree, and calculating a replacement probability based on the candidate spectrum matching degree and the spectrum matching degree; judging whether the replacement probability is greater than a preset threshold value, if so, taking the candidate spectrum as a new spectrum, and skipping to a process of executing random disturbance until the replacement probability is not greater than the preset threshold value to obtain a spectrum set; according to the method, a reservoir porosity set, a permeability set and a saturation set are calculated, intelligent quantification of nuclear magnetic resonance rock physical parameter uncertainty is carried out, parameter distribution credible interval and stability evaluation are provided, and the reliability and interpretation value of a reservoir evaluation result are remarkably improved.

This invention discloses a reservoir identification method that integrates seismic attribute inversion and paleokarst morphology modeling, belonging to the field of reservoir identification and modeling technology. The method includes: using an image sensor to perform multimodal fusion processing on a standardized image dataset to obtain multimodal fused image data; performing high-precision texture sampling and spatial alignment processing to generate a cross-modal image fusion matrix; inputting the cross-modal image fusion matrix into an image topology map construction process to establish image block node relationships and spatial connection edge weights, generating a paleokarst topology map; coupling the karst-seismic joint matching map with comprehensive reservoir attribute data to establish an effective reservoir evaluation model; and generating a multi-level reservoir prediction layer set through weighted fusion and multi-parameter spatial analysis. By constructing the paleokarst topology map and the karst-seismic joint matching map, spatial modeling of complex karst structures and cross-modal correlation analysis of seismic anomaly attributes are realized.

The application discloses a method and system for determining a reasonable water drive lower limit of horizontal well development in an ultra-low permeability reservoir, and belongs to the field of oilfield development. By obtaining the throat radius, the direct factor of restricting the fluid flow capacity, the reservoir percolation capacity can be better reflected; the higher the proportion of the number of fractures in the non-safe range, the greater the risk of water breakthrough in the fractured reservoir, and the less favorable the water injection development effect; the proportion of the water breakthrough oil production well can determine the adaptability of water injection development; according to the obtained yield, water injection development can be adopted when the yield is greater than 1; according to the average throat radius membership function, the number of fractures in the non-safe range membership function, the water breakthrough oil production well proportion membership function and the economic benefit membership function, the reservoir evaluation coefficient is obtained; when the reservoir evaluation coefficient is greater than the set value, the reservoir is suitable for horizontal well water injection development; when the reservoir evaluation coefficient is less than the set value, the reservoir is not suitable for horizontal well water injection development, and the horizontal well development mode of the ultra-low permeability reservoir can be determined.

The invention discloses a glutenite physical property evaluation method based on XRF element logging. The glutenite physical property evaluation method comprises the steps of rock debris sampling, cleaning, drying and grinding; measuring rock debris element types and rock debris element contents by XRF (X-Ray Fluorescence) elements; establishing a quartz gravel content index based on the quartz gravel characteristic element Si, and calculating the quartz gravel content index; establishing a granite gravel content index based on the granite gravel characteristic elements Na + K, and calculating the granite gravel content index; establishing an interstitial filler content index based on the interstitial filler characteristic elements Ca + Mg and Al + Fe + Ti, and calculating the interstitial filler content index; establishing a glutenite physical property evaluation standard based on the relationship between the quartz gravel content index, the granite gravel content index and the interstitial substance content index of the drilled well and the glutenite physical property; and performing reservoir evaluation by using the established glutenite physical property evaluation standard, and the like. According to the invention, glutenite stratum physical property evaluation can be carried out in real time while drilling.

The invention relates to the technical field of petroleum and natural gas exploration, in particular to an oil reservoir remaining oil saturation quantitative prediction method and device. The method comprises the following steps: determining an interpretation label in a target oil reservoir based on logging information of the target oil reservoir; on the basis of the interpretation label in the target oil reservoir, multiple oil-bearing schemes are constructed; and analyzing the multiple oil-bearing schemes, and quantitatively predicting the remaining oil saturation of the oil reservoir. The method can effectively, scientifically and accurately characterize the distribution condition of the remaining oil in the oil field under the current condition, and is of great significance to oil field development, oil reservoir evaluation and dynamic analysis.