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A Novel Method for Matching Reservoir Parameters Based on Particle Swarm Optimization and Support Vector Machine
Joint Authors
Detang, Lu
Yin, Rongwang
Li, Qingyu
Li, Peichao
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-29
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
When the reservoir physical properties are distributed very dispersedly, the matching precision of these reservoir parameters is not good.
We propose a novel method for matching the reservoir physical properties based on particle swarm optimization (PSO) and support vector machine (SVM) algorithm.
First, the data structure characteristics of the reservoir physical properties are analyzed.
Then, the particle swarm differential perturbation evolution algorithm is used to cluster and characterize the reservoir physical properties.
Finally, by using the SVM algorithm for feature reorganization and the least squares matching of the extracted reservoir physical properties, the feature quantity of the reservoir physical properties can be accurately mined and the pressure matching precision is improved.
The experimental results show that employing the proposed method to analyze and sample the data characteristics of the physical properties of the reservoir is better.
The extracted parameters can effectively reflect the physical characteristics of oil reservoirs.
The proposed method has potential applications in guiding the exploration and development of oil reservoirs.
American Psychological Association (APA)
Yin, Rongwang& Li, Qingyu& Li, Peichao& Detang, Lu. 2020. A Novel Method for Matching Reservoir Parameters Based on Particle Swarm Optimization and Support Vector Machine. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1198064
Modern Language Association (MLA)
Yin, Rongwang…[et al.]. A Novel Method for Matching Reservoir Parameters Based on Particle Swarm Optimization and Support Vector Machine. Mathematical Problems in Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1198064
American Medical Association (AMA)
Yin, Rongwang& Li, Qingyu& Li, Peichao& Detang, Lu. A Novel Method for Matching Reservoir Parameters Based on Particle Swarm Optimization and Support Vector Machine. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1198064
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1198064