Fast prediction of reservoir permeability based on embedded feature selection and LightGBM using direct logging data

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成果类型：

期刊论文

作者：

Zhou, Kaibo;Hu, Yangxiang;Pan, Hao;Kong, Li;Liu, Jie*;...

通讯作者：

Liu, Jie

作者机构：

[Zhou, Kaibo; Hu, Yangxiang; Pan, Hao; Kong, Li] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Key Lab Image Informat Proc & Intelligent Control, Educ Minist China, Wuhan 430074, Peoples R China.

[Liu, Jie] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China.

[Liu, Jie] Minist Ind & Informat Technol, Key Lab, Nondestruct Detect & Monitoring Technol High Spee, Nanjing 210016, Peoples R China.

[Huang, Zhen] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.

[Chen, Tao] China Petr Logging Co Ltd, Xian 710077, Peoples R China.

通讯机构：

[Liu, Jie] H

[Liu, Jie] M

Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China.

Minist Ind & Informat Technol, Key Lab, Nondestruct Detect & Monitoring Technol High Spee, Nanjing 210016, Peoples R China.

语种：

英文

关键词：

direct logging data;embedded feature selection;light gradient boosting machine;machine learning;permeability prediction

期刊：

Measurement Science And Technology

ISSN：

0957-0233

年：

2020

卷：

期：

页码：

045101

DOI：

10.1088/1361-6501/ab4a45

基金类别：

National Natural Science Foundation of ChinaNational Natural Science Foundation of China [61873101]; National Science and Technology Major Project [2017ZX05019-001]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [2019kfyXJJS137]; Changzhou Key Laboratory of high technology [CM20183004]

机构署名：

本校为其他机构

院系归属：

电气与电子工程学院

摘要：

Permeability estimation plays an important role in reservoir evaluation and hydrocarbon development, etc. Traditional physical model-based methods have problems with being time consuming and high cost. The applications of machine learning are currently becoming more and more extensive, however, there are still several limitations to previous machine learning-based permeability estimation methods, such as a limited number of samples, a requirement of prior knowledge, and some parameters needing to be calculated indirectly. In this paper, a hybrid reservoir permeability prediction approach, whic...

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Fast prediction of reservoir permeability based on embedded feature selection and LightGBM using direct logging data

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