Special Issue on Machine Learning Applications in Coal, Petroleum and Geothermal Energy Industries
Published 23 February, 2021
The application of machine learning techniques to solve problems in energy industries has aroused great interest in recent years, due to the development of powerful machine learning models and the availability of high-performance computational resources. Examples of machine learning applications in the industries of coal, petroleum and geothermal energy include: forward prediction of energy production; inverse modelling for the estimation of reservoir properties; surrogate modelling and uncertainty quantification; and optimisation tasks related to the efficient recovery of resources. A variety of studies have attempted to enhance these processes and promising results have been reported. However, challenges remain around machine learning model design, feature engineering, training optimisation and efficiency improvement. In this special issue, we call for original research papers and review articles that present and discuss the latest advances and challenges in the use of machine learning in geoscience applications in coal, petroleum and geothermal energy industries.
Topics Covered:
These include, but are not limited to machine learning applications in:
- Petroleum reservoir simulation and history matching
- Contaminant transport and source identification
- Digital rock construction and petrophysical properties estimation
- Classification and regression problems based on well log data
- Fault/fracture detection based on geophysical data
- Coal bed methane recovery
- Geothermal energy recovery
Important Deadlines:
- Submission deadline: 31 December 2021
Submission Instructions:
Please read the Guide for Authors before submitting. All articles should be submitted online, please select VSI: Machine learning applications.
Guest Editors:
- Managing Guest Editor: Dr. Rui Xu, Peng Cheng Laboratory, China. Email: xur@pcl.ac.cn
- Dr. Zhiming Chen, China University of Petroleum-Beijing, China. Email: zhimingchn@cup.edu.cn
- Dr. Wenhui Song, China University of Petroleum (East China), China. Email: song_wen_hui@hotmail.com
- Dr. Javier A. E. Santos, The University of Texas at Austin, USA. Email: jesantos@utexas.edu