Complex reservoir lithology identification method, apparatus and device, and storage medium
A lithology identification and reservoir technology, applied in character and pattern recognition, earthwork drilling, instruments, etc., can solve the problems of small number of cores, poor generalization, difficult labeling, etc., so as to improve the accuracy and enhance the generalization. sexual effect
Pending Publication Date: 2021-09-07
CHINA UNIV OF PETROLEUM (BEIJING)
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However, the generalization of this method is poor, and it is only applicable to the current well, and no research has shown that this method can be extended to other work areas and other wells, and the number of cores taken in actual production is relatively small, making it difficult to make a large number of labels
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[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0052] The invention provides a complex reservoir lithology identification method, such as figure 1 and figure 2 shown, including the following steps:
[0053]S101, establishing a petrophysical model applicable to the actual work area;
[0054] In practical applications, complex lithology reservoirs are deeply buried and affected by multi-stage tectonic processes, resulting in complex rock structures. The uneven distribution of pores, fractures and fluids ...
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The invention discloses a complex reservoir lithology identification method, apparatus and device, and a storage medium. The method comprises the steps of establishing a rock physical model suitable for an actual work area; generating lithology labels and multivariate attribute parameters through the rock physical model; according to the generated lithology label and the multivariate attribute parameters, screening out sensitive features sensitive to lithology by using a random forest algorithm and a rendezvous analysis method; taking the screened sensitive features and lithology labels as training samples, and generating a lithology recognizer through training by using a random forest algorithm; and carrying out lithology identification by using a lithology identifier. Therefore, multivariate attributes are incorporated into the lithology identification problem through the rock physical model, and the lithology identifier is trained and generated by using the lithology label made by the rock physical model and the random forest algorithm, so that the accuracy of lithology identification in actual production can be improved, and the generalization of a machine learning algorithm can also be enhanced.
Description
technical field [0001] The invention relates to the field of lithology identification, in particular to a complex reservoir lithology identification method, device, equipment and storage medium. Background technique [0002] At present, lithology identification is one of the important tasks of reservoir evaluation, and it is the basis for solving reservoir parameters, which is of great significance to the accurate identification of lithology. Different types of reservoirs have different pore structures, fluids, and physical parameters, resulting in different elastic responses of different reservoirs, which brings great challenges to lithology identification. [0003] There are already many methods for lithology identification in actual production. The traditional method is to use intersection analysis based on well logging data, but this method often has a large workload and low accuracy. With the development of artificial intelligence and the cross-application of multiple ...
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IPC IPC(8): G06K9/62G06N20/00E21B49/00
CPCG06N20/00E21B49/00G06F18/214
Inventor 唐跟阳冯刚王尚旭
Owner CHINA UNIV OF PETROLEUM (BEIJING)