13 results about "Sedimentology" patented technology

The application discloses a kind of based on sequence stratigraphy and seismic sedimentology's braided river channel reservoir fine characterization method, comprising the following steps: obtaining target area core, well logging and high-resolution three-dimensional seismic data;By analyzing the sedimentology mark and logging facies mark in the target area, to determine the sedimentary facies type and sedimentary microfacies division;Using lithology and well logging curve, using the theory of sedimentology, high-resolution sequence stratigraphy identifies sequence interface type and feature, and carries out high-resolution sequence stratigraphic sequence division;Division reservoir architecture interface;According to the internal structure of sedimentary system, sedimentary facies distribution, focus on high-frequency sequence and sedimentary body scale, generate the braided river channel reservoir fine characterization result of target area architecture unit.The present application effectively solves the deficiencies of prior art in reservoir fine description, boundary identification and parameter inversion, improves the efficiency and success rate of oil and gas reservoir development.

The invention relates to the technical field of geology and sedimentary data analysis, in particular to a sedimentary rock particle analysis method and system based on an opencv visual library. The method comprises the following steps: firstly, acquiring a high-resolution digital image of a sedimentary rock sample, and preprocessing to enhance the characteristics of clastic particles; processing the image by using an opencv library, automatically identifying and segmenting a single debris particle, and calculating the equivalent diameter of the single debris particle; finally, an analysis report containing particle distribution and particle size statistical information is automatically generated. According to the method, image acquisition, processing, analysis and report generation are integrated into a continuous automatic process, a traditional manual microscope observation and manual measurement mode is replaced, the analysis efficiency is remarkably improved, and the method is suitable for large-scale sample processing. Recognition and measurement are executed through a standardized algorithm, subjective errors are effectively reduced, objectivity and consistency of analysis results are guaranteed, and an efficient and reliable technical means is provided for sedimentary rock granularity analysis.

The application discloses a kind of based on genesis method's thin layer stratum thickness prediction method, system and medium, it is related to stratum thickness prediction technical field, the method includes: S10, stratum distribution main control factor analysis;S20, structural boundary delineation;S30, in combination with stratum distribution law and seismic delineation structural boundary, qualitative recovery is carried out to stratum geological model, obtains stratum thickness trend model;S40, in combination with stratum thickness data of drilled well and stratum thickness trend model, establishes stratum thickness prediction data model, and iteration is carried out to it;S50, according to well deviation of actual drilling, calculates the well bottom coordinate of the top of target layer;S60, calculates the key parameter of well bottom and coordinate boundary, then it is input into stratum thickness prediction data model, and stratum thickness is predicted.The present application introduces the principle of sedimentology, genesis method predicts stratum thickness, and is strong in logic, and the method is more reasonable;Meanwhile, the present application reduces the quality requirement of seismic data, and is strong in compatibility, avoids excessive processing of seismic data.

The invention relates to the technical field of geophysical logging and sedimentology intelligent interpretation, and particularly discloses a method for intelligently segmenting and identifying sedimentary microfacies based on a logging curve. The method comprises the steps that a gamma ray curve and cleaning rule configuration are acquired, and a coarse segmentation segment set is generated through data cleaning, standardization and filtering processing; a section sample set is generated through interface alignment, boundary fine adjustment and section judgment in combination with a logging interpretation conclusion; feature extraction is carried out based on operation period dependence, and a segment classification result is generated through rule classification and model inference fusion processing; and finally, outputting a sedimentary microfacies type result and forming closed-loop feedback through sequence splicing, morphological rule mapping and configuration parameter self-adaptive updating. According to the method, automation and adaptive optimization of the sedimentary microfacies identification process are realized, and the identification accuracy and the engineering application efficiency are effectively improved.

The application discloses a tight sandstone dessert reservoir prediction method based on seismic sedimentology, and relates to the technical field of reservoir prediction in oil exploration. The tight sandstone dessert reservoir prediction method based on seismic sedimentology comprises the following steps: pre-processing well logging data; drawing a seismic-geological interpretation profile graph; obtaining a structure graph; obtaining a fine layer velocity model; performing well logging curve standardization processing; performing forward simulation; performing reservoir inversion; extracting attributes; and comprehensively performing reservoir prediction according to the attributes and the inversion. The method improves the accuracy and precision of reservoir prediction, and improves the efficiency and economic benefits of data processing and exploration and development.

The invention relates to the field of sedimentology research, in particular to a fine material source analysis method for a mountain-building basin, which is realized by adopting a Monte-Carlo simulation method, and the Monte-Carlo simulation method realizes the analysis process of a plurality of sub-source areas on sedimentary basin material sources by utilizing highly decomposed age spectrum new subclasses. Height decomposition of the method is completed by clustering and heat map analysis of age spectrum data of debris zircon in a sedimentary basin and a source region, and height decomposition of complex age spectrum data in a source-sink process is realized by decomposing complex age spectrum clusters of the sedimentary basin and the source region into different age spectrum new subclasses. The problem that hybrid data of the sedimentary basin is analyzed by using hybrid data of a source region traditionally is avoided, age spectrums of the sedimentary basin and the source region are clear at a glance, and potential uniformity or diversity characteristics of the sedimentary basin and the source region are easy to identify.

The invention discloses a seismic lithogenous phase prediction method based on semi-supervised learning, and belongs to the technical field of seismic sedimentology. Analyzing main diagenesis types of compact sandstone at a target layer by comprehensively using analysis test data, rock physical experiment data, logging data and seismic data, establishing a diagenesis evolution sequence and a diagenesis phase division scheme, and determining rock core diagenesis phases; a logging curve sensitive to the lithogenous phase is screened out, and vertical distribution of the lithogenous phase on a single well is evaluated through logging; determining diagenetic phase sensitive seismic elastic parameters by means of rock physical analysis, correlation analysis and analysis of relation among diagenetic characteristics, mineral components and seismic elastic parameters; a semi-supervised learning neural network model based on an attention mechanism is created, a non-linear mapping relation between the rock core lithogenous phase and the sensitive seismic elastic parameters is established through semi-supervised learning, and a lithogenous phase comprehensive index data body is obtained; and carrying out phase and slice processing on the diagenesis phase comprehensive index data body, screening typical stratigraphic slices, and explaining seismic diagenesis phase space distribution.

The invention discloses a deposition path process fingerprint decoding method and system based on a complex source-sink system, and relates to the technical field of tectonic sedimentology and data modeling crossing. Target strata geochemical characteristic data of a research area are collected and arranged, and a large deposition geochemical data set of the research area is established; and establishing standard stratum characteristics and sedimentary geochemical characteristics thereof in combination with a typical stratum profile of the basin. According to the method, the multi-source supply and re-cycle contribution proportion on the geologic source-sink system deposition path is quantitatively recovered through establishment of target layer series multi-dimensional scaling analysis, homogenization degree analysis, fingerprint decoding parameter PCA data statistics and the like, the defects that a traditional source-sink analysis method depends on prior end member selection and is easily influenced by personal errors are overcome, and the method is suitable for large-scale analysis of the geologic source-sink system deposition path. The inverse Monte Carlo model is utilized to carry out iterative simulation for multiple times, the simulation effect is gradually optimized, the accuracy and reliability of the deposition path and process description result are ensured, and a more scientific and accurate technical means is provided for geological research and resource exploration.

The invention discloses a comparative sedimentology-based material source discrimination method, and relates to the technical field of petroleum and natural gas exploration and development. According to the method, the advantage of full coverage of three-dimensional seismic data on an underground sand body is fully utilized, a sedimentary facies type is determined by depicting a sand body plane distribution form and combining a logging facies mark, comparison is carried out by taking a corresponding modern sedimentary environment as a reference, and the source of the river-delta sedimentary system is comprehensively judged by adopting a comparative sedimentology method. According to the method, the source of the sand body can be identified more quickly and accurately, and geological researchers can be helped to more intuitively understand the superposition relationship of the sand bodies in different underground material source directions. The method is particularly suitable for continental basins which are covered by three-dimensional seismic data and are in the atrophy stage, and is expected to be applied to paleogeography reconstruction of shallow water and complex materials and oil-gas exploration and development.

The present application belongs to the technical field of the cross of sedimentology and artificial intelligence, and particularly relates to a sediment source tracking method based on multi-dimensional morphological characteristics of heavy minerals. The present application establishes a "high roundness-fresh fracture" combined discrimination mechanism, accurately captures the key geological evidence of "highly round particle surface superimposed fresh fracture surface" through a double-head neural network, establishes a standard geological fingerprint logic library, and combines neural network training standardization "multi-cycle" heavy mineral characteristics, so as to improve the extraction depth of mineral morphological characteristics without relying on expensive geochemical tests, effectively distinguish the old sedimentary rock re-circulation components and the far-source direct transport components, realize the quantitative source tracking of sediment dynamics based on the population statistical law, and provide more objective, macroscopic and repeatable quantitative data support for basin analysis, paleogeographic reconstruction and oil and gas reservoir prediction.

The invention discloses a quantitative seismic sedimentology method, which relates to the technical field of oil-gas exploration, and comprises the following steps of: establishing a nonlinear learning model of logging curves (Vp, Vs and RHOB) and a gamma curve (GR) by adopting a random forest learning method, and then applying the model to a three-dimensional elastic parameter body (Vp, Vs and RHOB) to obtain a three-dimensional gamma (GR) body; a three-dimensional gamma (GR) body with clear geological significance is obtained through a data driving mode, and the problem of obtaining a three-dimensional geological parameter body (GR) through three-dimensional seismic data is solved; secondly, replacing a three-dimensional seismic data volume adopted by the existing method with a three-dimensional gamma (GR) data volume in the process of seismic sedimentology analysis and stratigraphic slice analysis, and realizing quantitative seismic sedimentology interpretation under the constraint of a lithology quantitative interpretation standard; and finally, since the random forest algorithm carries out sampling every time to train the model, the generalization ability is very strong, and the method plays a role in reducing the variance of the model.

The invention relates to the cross technical field of geochronology and sedimentology, and discloses a laser in-situ isotope measurement method for limiting the deposition age of sandstone containing carbonate cement, which comprises the following steps: S1, sample collection and preparation: carrying out sample collection and sample separation on a sandstone sample containing carbonate cement and chipping zircon; s2, selecting particles in a to-be-detected area, performing period analysis on the carbonate cement, selecting the to-be-detected area, and selecting particles meeting conditions from the chippings of zircon; step S3; u-Pb isotope analysis, wherein an LA-ICP-MS device is adopted for conducting single-point laser denudation on the to-be-detected area and the particles, and isotope analysis is conducted; s4, data processing and age explanation are conducted, the age of carbonate cement is obtained to serve as the lower limit of sandstone deposition age, and the age of the young group of chipping zircon is obtained to serve as the upper limit of sandstone deposition age; and S5, comprehensively limiting the deposition age, and constraining the real deposition age of the sandstone in combination with the upper limit and the lower limit.

The application discloses a carbonate reservoir prediction method and system based on seismic sedimentology, and comprises the following steps: collecting data of a research area; identifying and dividing sequence interfaces of a target layer by analyzing seismic data and well logging curves; evaluating seismic amplitude data of the target layer and determining an effective signal range; performing frequency division processing on the seismic data in the effective signal range; performing high-precision sequence interface seismic tracking interpretation; analyzing distribution rules of reservoirs and distribution conditions of special lithology in a sequence framework; establishing a seismic forward geology model; performing seismic forward to confirm seismic response characteristics of the reservoirs and the special lithology; selecting appropriate seismic reservoir prediction methods or technologies for reservoirs at different sequence positions to perform reservoir prediction work; and evaluating reservoir prediction results and removing systematic errors leading to abnormal areas. The application has the advantages of improving the precision and accuracy of reservoir prediction, improving the efficiency and economic benefits of data processing and exploration and development.