21 results about "Facies" patented technology

The application discloses a fine-grained sedimentary rock facies identification method based on deep learning, relates to the technical field of deep learning and sedimentary rock facies identification, and comprises the following steps: collecting facies curve data and microstructure image data and screening characteristic parameters, generating a standardized multi-modal feature set through a special analysis engine; calling a specific model to perform hierarchical feature extraction on the microstructure image to obtain a deep microstructure feature vector; inputting the two types of features into a special network to output a preliminary identification result through cross-modal attention weight distribution; and adopting a specific algorithm to perform inversion correction and dynamic adjustment on the preliminary result, combining feedback information to construct a facies classification system to complete accurate division. Through multi-source feature deep fusion, cross-modal correlation enhancement and multi-link collaborative optimization, the application realizes efficient and accurate identification of fine-grained sedimentary rock facies, adapts to complex lithological characteristics, and provides support for technical application in related fields.

This application discloses a lithofacies analysis system and method based on a shale geological-mechanical coupled lithofacies classification system, relating to the field of shale lithofacies analysis. The system construction module determines the geological-mechanical coupled lithofacies classification system based on information data from the data acquisition module; the prediction module determines single-well lithofacies prediction information; the feedback adjustment module adjusts the single-well lithofacies prediction information based on set rock mechanics and geostress parameter ranges to obtain adjusted information; the three-dimensional model construction module uses a genetic algorithm to perform seismic attribute embedding and integrated inversion based on seismic attribute data and adjusted information, and uses a co-kriging method to construct a three-dimensional model of well-seismic co-modeling of geological-mechanical coupled lithofacies; the parameter model determination module uses a layer-control-facies dual-control method to control constraints and determine the heterogeneity of the geological-mechanical characteristics of shale layers in three-dimensional space, providing a basis for establishing production areas for the exploration and development of artificial oil and gas reservoirs.

A method may include obtaining well data regarding a geological region of interest. The method may further include obtaining a geological process model for the geological region of interest. The method may further include determining a simulation region of the geological process model based on a template size and a simulation grid. The method may further include determining a simulation path through the simulation region. The method may further include determining a geological event associated with a predetermined geological facies based on the well data. The method may further include determining a replicate event based on the geological event, a similarity analysis, and using the simulation path. The method may further include assigning the predetermined geological facies to a cell location of the replicate event in the simulation region. The method may further include updating the geological process model to produce an updated geological process model.

The invention discloses a trend probability constrained hierarchical phase control modeling method and a three-dimensional geologic model, and belongs to the field of oilfield development, and the method comprises the steps: determining small-layer structure features in a target region, and solving a small-layer stratum thickness map in a given target region boundary range through a Kriging difference method; analyzing the characteristics of different small-layer sand bodies under the guidance of the sedimentary mode to obtain a small-layer sand body thickness map; establishing a trend probability body model; and establishing a three-dimensional geologic model. According to the method, the three-dimensional geologic model is guaranteed to be completely loyalty to well point data, meanwhile, geologists can integrate underground reservoir cognition of different levels into the three-dimensional geologic model, and the established three-dimensional geologic model better conforms to the underground real situation. According to the three-dimensional geologic model established by the method, the geometrical morphology and the contact relation of the target geologic body are represented, and the accuracy of reservoir inter-well prediction is improved. The established three-dimensional geologic model provides favorable guarantee for more accurate reserve calculation and more sufficient well location deployment basis.

Example methods and systems for subsurface reservoir characterization are disclosed. One example method includes obtaining facies data of rock formations of a subsurface reservoir, where the facies data is from a forward stratigraphic modeling (FSM) process applied to the subsurface reservoir. A compaction-porosity model and an acoustic impedance-porosity model are selected from a library of rock physics models based on the facies data. An acoustic impedance model of the rock formations of the subsurface reservoir is determined based on the compaction-porosity model and the acoustic impedance-porosity model. The acoustic impedance model is provided for hydrocarbon exploration of the subsurface reservoir.

This invention provides a method for predicting source rocks in deep, well-free areas, comprising: constructing a stratigraphic velocity model; obtaining a three-dimensional stratigraphic structure image based on the stratigraphic velocity model and seismic data from the deep, well-free area, and performing seismic interpretation to determine the potential distribution range of source rocks; constructing a paleogeographic model based on the sedimentary facies and paleogeographic conditions of the deep, well-free area; constructing a tectonic model based on tectonic feature data; constructing a three-dimensional geological model based on the paleogeographic model, the tectonic model, and the stratigraphic data of the deep, well-free area; determining the distribution range of source rocks in the three-dimensional geological model; and overlaying the potential distribution area of ​​source rocks obtained from seismic analysis with the distribution range of source rocks obtained from the three-dimensional geological model to determine areas favorable for source rock distribution. By comprehensively utilizing seismic imaging and geological modeling methods, the accuracy of predicting the distribution of source rocks in deep, well-free areas is improved.

A method for characterizing the architecture of a carbonate reservoir. The method comprises: on the basis of the genetic type of a carbonate reservoir, determining factors controlling the heterogeneity of the carbonate reservoir (101); characterizing the depositional architecture of carbonate rocks on the basis of drilling data, seismic data and the factors controlling heterogeneity (102); characterizing the diagenetic architecture of the carbonate rocks under the constraint of the characterization of the depositional architecture of the carbonate rocks and on the basis of the drilling data, the seismic data and the factors controlling heterogeneity (103); and characterizing the architecture of the carbonate reservoir on the basis of the geological facies of the carbonate reservoir in combination with the characterization results of the depositional architecture and the diagenetic architecture of the carbonate rocks, so as to obtain a characterization result of the architecture of the carbonate reservoir (104). The present invention further relates to an apparatus, a device, a readable storage medium and a program product for the characterization of the architecture of a carbonate reservoir.

This invention discloses a method and system for quantitatively evaluating the present-day in-situ stress field disturbance in fluvial facies tight reservoirs, belonging to the field of oil and gas extraction technology. The method includes the following steps: S1: Determining the direction and magnitude of in-situ stress in each well in the target area; S2: Constructing a three-dimensional geological model that reflects the mud-encased sand structure; S3: Performing a simulation inversion of present-day in-situ stress to obtain the present-day in-situ stress distribution within the channel sand body and surrounding rock; S4: Calculating the stress transfer coefficient and differential stress accumulation factor, and using them to quantitatively evaluate the magnitude disturbance of in-situ stress; S5: Obtaining the strike of the channel sand body, the direction of the regional principal stress, and the direction of the principal stress after disturbance at the channel where the well is located, and using this to calculate the angle between the strike of the channel sand body and the direction of the regional principal stress, and the principal stress deflection angle transmitted from the regional principal stress to the well location, and using these to quantitatively evaluate the disturbance of the in-situ stress direction. This invention can quantitatively evaluate the present-day in-situ stress field disturbance in fluvial facies tight reservoirs.

This invention discloses a method and medium for quantitatively predicting the thickness of source rocks, comprising: establishing a multidimensional source rock identification index system based on multidimensional research data; defining favorable development facies zones of source rocks according to the source rock identification index system; within the defined favorable development facies zones, calibrating the seismic response of source rocks according to the determined source rock identification index system; combining the seismic response calibration with the source rock thickness to establish a quantitative prediction model for source rock thickness; and calculating the predicted source rock thickness using the quantitative prediction model. This invention integrates multidimensional research data into the establishment of the multidimensional source rock identification index system and the quantitative prediction model for source rock thickness, forming a complete technical closed loop. This effectively avoids the limitations of a single data source and, through the constraint of favorable development facies zones, ensures a high degree of consistency between the prediction results and geological laws, avoids purely mathematical prediction errors, and improves the accuracy and reliability of source rock thickness prediction.

This invention provides a method for fine stratigraphic correlation between outcrop profiles and well logging, belonging to the field of stratigraphic correlation technology. It solves the problems in existing technologies for stratigraphic correlation studies in inter-basin regions, where the fine stratigraphic divisions obtained from well logging within the basin cannot be accurately compared with the outcrop strata, leading to difficulties in large-area fine stratigraphic distribution, sedimentary facies research, and prediction of hydrocarbon source rocks and reservoirs. The method includes collecting fine stratigraphic division schemes from well logging within the basin and comparing them with standard outcrop profile divisions to identify differences; collecting full-core wells with conventional logging in the outcrop area to establish a correspondence between well logging stratigraphic divisions and core lithology and rock assemblages, and establishing rock-electrical response indicators; using gamma-ray measurement to construct virtual well logging curves for the outcrop profile and combining this with comprehensive information from full-core wells at the basin margin, outcrop profile rock assemblages, sequence cycles, and paleontology to establish basin-mountain stratigraphic correlation relationships, thus achieving a method for fine regional stratigraphic correlation.

The application discloses a method for updating porosity and permeability of a sub-facies reservoir based on a displacement experiment, and comprises the following steps: step 101, calculating a quantitative relationship between a displacement multiple of the sub-facies and a change of core porosity; step 102, calculating a correlation between the core porosity and the permeability; step 103, obtaining correction amounts of corresponding porosity fields and permeability fields in different displacement multiples; and step 104, correcting to obtain a more accurate geological model of the porosity field and the permeability field. The application is suitable for the technical field of oil reservoir development, can provide a more accurate geological model for numerical simulation calculation of an oil reservoir, and greatly improves the efficiency of a mine development scheme and the accuracy of effect evaluation.

The application discloses a shale facies combination non-homogeneity strength quantitative characterization method, comprising the following steps: step 1, carrying out gray scale pretreatment on a core image to obtain a core gray scale photo; step 2, extracting a lamination thickness characteristic number series from the core gray scale photo; step 3, observing a micro photo of a rock sample, determining lamination composition and type, and defining a shale facies type; step 4, using the shale facies type and corresponding lamination thickness, fitting to obtain a characteristic curve D representing the lamination thickness; step 5, respectively calculating fractal dimensions delta D and delta GR number series of a logging curve GR representing the characteristic curve D and representing the lithology; step 6, carrying out normalization processing on the fractal dimension delta D and delta GR number series to obtain a processing analysis result; and step 7, quantitatively characterizing non-homogeneity strength of the shale facies combination according to the processing analysis result. The method is applied to exploration and development of a shale reservoir, and realizes quantitative characterization of a non-homogeneity degree of the shale reservoir.

The application provides a reservoir physical property parameter prediction uncertainty evaluation method, comprising the following steps: step 1, establishing a statistical rock physics model of a target area, thereby deriving a conditional probability of seismic attributes; step 2, performing statistical analysis on existing physical property parameter data, and establishing a corresponding physical property parameter prior distribution; step 3, based on the statistical rock physics model and the prior probability distribution obtained in steps 1 and 2, using a physical property parameter simulation sampling algorithm of facies variation, performing facies prediction and generating a physical property parameter sample set of the target area; and step 4, according to the physical property parameter sample set obtained in step 3, estimating the expectation, variance and confidence interval of the physical property parameter. The reservoir physical property parameter prediction uncertainty evaluation method realizes the statistical expectation, variance and confidence interval estimation of the shale content, porosity and saturation in the facies variation reservoir, further evaluates the potential risk of the target reservoir development, and provides technical support for the risk analysis of oil and gas exploration and development.

This invention provides a method for igneous rock facies classification and prediction based on multi-physics discriminant factors, relating to the field of oil and gas field exploration and development technology. The method includes: S1: Constructing a multi-dimensional facies classification model based on diagenesis, integrating lithology index and structural maturity index to quantitatively classify geological facies; S2: Performing principal component analysis on well logging curves to select sensitive well logging curves and construct a sensitive well logging dataset; S3: Constructing rock physical facies factors through Fisher discriminant analysis; S4: Projecting known facies samples onto the rock physical facies factor space, training a classification model using a support vector machine algorithm, and generating a facies identification map; S5: Substituting target well data into the model to complete single-well facies identification; S6: Establishing the correlation between rock physical facies factors and seismic elastic parameters, inverting the seismic data volume into a three-dimensional attribute volume of rock physical facies factors based on a Bayesian inversion framework, fusing them to generate a three-dimensional facies model, thus realizing facies prediction from well point to three-dimensional space.

The application discloses a volcanic facies belt distribution method and device, and belongs to the technical field of oil and gas seismic exploration. The method comprises the following steps: establishing a volcanic rock lithology identification chart according to drilling data and logging data of a region to be measured; determining volcanic mechanism macro features according to seismic data of the region to be measured, and obtaining a first seismic attribute data body; determining a plurality of volcanic facies belts according to the volcanic rock lithology identification chart and the volcanic mechanism macro features; performing well-seismic fine calibration on the first seismic attribute data body according to the drilling data and the logging data of the region to be measured, and determining a one-to-one corresponding relationship between the seismic data and the volcanic facies belts; and performing fusion processing on the first seismic attribute data body according to a plurality of target seismic attributes, and obtaining a second seismic attribute data body. The method improves the prediction accuracy of high-quality volcanic reservoirs, reduces drilling risks, and provides reliable data for efficient exploration and development of oil and gas reservoirs.

The application provides a sedimentary microfacies type identification method, system, storage medium and device, relates to the field of geological feature identification, and comprises the following steps: acquiring facies sequence characteristics, logging curve shape and numerical characteristics and vertical probability distribution characteristics of each microfacies type in a specific sedimentary environment; performing correlation analysis on the normalized logging curve numerical characteristics, and screening out preferred logging curves; training the vertical probability distribution characteristics of the microfacies, obtaining an optimal microfacies distribution sequence and a transition probability matrix; respectively constructing a first microfacies label library and a second microfacies label library; respectively establishing a first identification model and a second identification model based on the two label libraries to form a joint model; and finally inputting non-coring well data to be predicted into the joint model, and determining the corresponding sedimentary microfacies type by weighting the highest probability output. The application can intelligently identify complex microfacies, and realizes fine interpretation of sedimentary microfacies in a research area.

The application discloses a river sand facies controlled high-resolution inversion method of structural class attribute constraint, and the inversion method comprises the following steps: step S1, river facies facies belt division based on structural class attribute; step S2, well logging data preprocessing, and calculating a matching factor at a well site; step S3, calculating an inversion wavelet according to the matching factor, and performing space variation processing on the matching factor; step S4, establishing an initial impedance model based on the characteristics of a work area and structural class attribute; and step S5, performing facies controlled high-resolution inversion according to the initial impedance model. For the river sand target, the identification capability of a seismic trace beside a well is improved through well-to-seismic correlation and matching, and then high-resolution wave impedance data volume is obtained through the constraint high-resolution inversion, and a horizon slice exhibits good river sand delineation capability.

This invention discloses a method and apparatus for characterizing carbonate reservoir configurations. The method includes: determining the heterogeneity control factors of the carbonate reservoir based on its genetic type; characterizing the sedimentary configuration of the carbonate rocks based on drilling data, seismic data, and the heterogeneity control factors; characterizing the diagenetic configuration of the carbonate rocks based on drilling data, seismic data, and the heterogeneity control factors, under the constraints of the sedimentary configuration characterization; and characterizing the carbonate reservoir configuration based on the geological facies of the carbonate reservoir, combined with the sedimentary configuration characterization results and the diagenetic configuration characterization results, to obtain the carbonate reservoir configuration characterization results. This invention can achieve the coupling of carbonate sedimentary configuration and diagenetic configuration, laying the foundation for the rational formulation of reservoir development plans.

This invention provides a method for determining the lithofacies classification scheme of continental mixed sedimentary mudstone and shale, comprising: 1) Core observation: Observing the cores according to the sedimentary principles of the strata, following a depth-to-shallow sequence; 2) Stratigraphic division: Using the results of core observations and combining them with well logging curve characteristics, stratigraphic division is performed; 3) Sub-layer evaluation: Sampling is conducted on each sub-layer, and pyrolysis and irregular sample property analysis are performed. Sub-layer evaluation is then performed based on the analysis results; 4) Composition determination: X-ray diffraction whole-rock analysis is performed on the cores corresponding to each sub-layer to analyze the rock mineral composition; 5) Scheme determination: Based on the above analysis results, the target classification scheme is determined. This invention improves the accuracy and effectiveness of lithofacies classification schemes, accurately and efficiently classifying lithofacies types, laying the foundation for further evaluation of favorable lithofacies, and providing a basis for selecting "sweet spot" layers and target windows.

The present invention relates to a computing script designed to extract contour contrasts from images to facilitate methods for lithofacies image determination. The present invention presents a tool for highlighting the heterogeneity of rocks to identify textural patterns and typical structures related to sedimentary facies. The "Canny edge detection" algorithm and settings in the Python computer language environment are used to extract the contour contrasts observed in the cross-sections of the captured rock images. Other results achieved by the present invention include the removal of artifacts, the superposition of images, and the quantification of edge contrasts. These results have been incorporated into the methods for lithofacies image determination. In addition, the use of the resulting products in well-logging facies prediction models, deliverability, and interwell correlations has a wide range of prospects. Thus, the script developed provides important information for the oil industry.

The application provides a tidal flat facies dolostone reservoir logging while drilling evaluation method, the method comprises the following steps: determining the marker layer on the upper part of the high-quality reservoir by using Ca, Mg and other elements according to element logging analysis, qualitatively identifying the reservoir by engineering logging parameters, obtaining the dissolution pore characteristics by scanning the rock debris backscattering imaging, calculating the elastic modulus of the rock by elements, finally forming the tidal flat facies dolostone logging while drilling evaluation method, which can provide the basis for trajectory optimization in the drilling construction process of the tidal flat facies dolostone formation, guide the drilling construction and improve the drilling rate of the high-quality reservoir.