A reservoir identification method, device, equipment and readable storage medium
By using weighted kernel principal component analysis, well logging curves are mapped from a low-dimensional space to a high-dimensional feature space and the data dimensionality is reduced, which solves the problem of lithology identification in mixed sedimentary reservoirs and achieves rapid and accurate lithology identification.
CN117631021BActive Publication Date: 2026-07-03PETROCHINA CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- PETROCHINA CO LTD
- Filing Date
- 2022-08-24
- Publication Date
- 2026-07-03
AI Technical Summary
Technical Problem
Existing technologies struggle to quickly and efficiently identify the lithology of mixed sedimentary reservoirs, particularly in well logging curve intersection methods where information redundancy and difficulties in handling nonlinear relationships exist.
Method used
We use weighted kernel principal component analysis to map well logging curves from a low-dimensional space to a high-dimensional feature space. Through data dimensionality reduction processing and weighting coefficients, we can identify sandstone reservoirs.
Benefits of technology
It enables rapid and accurate identification of lithology in complex areas, boasts fast processing speed, simple operation, and is suitable for large-scale data processing, thus possessing broad application value.
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Figure CN117631021B_ABST
Abstract
The application discloses a reservoir identification method, device and equipment and a readable storage medium. The method comprises the following steps: obtaining a weighting coefficient of a logging curve of different logging sections by using core data; mapping the logging curve of different logging sections from a low-dimensional space to a high-dimensional feature space; performing data dimension reduction processing on the high-dimensional feature space; and identifying a sandstone reservoir according to the dimension reduction processing result and the weighting coefficient. The method can quickly and effectively identify the lithology in a complex area, is simple to operate, fast in operation, can process a large amount of data, and thus has great application potential.
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