Applications of Machine Learning and Artificial Intelligence in Petroleum Engineering
摘要截稿:
全文截稿: 2019-03-31
影响因子: 3.706
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 2区
• 小类 : 能源与燃料 - 3区
• 小类 : 工程:石油 - 1区
Overview
This special issue focuses on machine learning (ML) experimentation and operationalization. ML experimentation refers to the efforts centered on data preparation, algorithm selection and model validation and verification. ML operationalization refers to the process of deploying models and the subsequent consumption and monitoring of resilient, efficient and measurable services applied to petroleum engineering problems. The issue accepts submissions on the following topics, as applied to petroleum engineering problems:
Data preparation
Descriptive analytics
Predictive analytics
Prescriptive analytics
Hyper-parameter tuning
Automated ML
ML modeling deployment
ML modeling monitoring
ML continuous integration and continuous delivery (CI/CD)