Machine Learning in the Oil and Gas Industry: Including Geosciences, Reservoir Engineering, and Production Engineering with Python
By 作者:Yogendra Narayan Pandey
Release Finelybook 出版日期:2020
Publisher Finelybook 出版社:Apress
pages 页数: Paperback
The Book Description robot was collected from Amazon and arranged by Finelybook
Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed By 作者:an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.
Throughout the book, the emphasis is on providing a practical approach with step-By 作者:-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry.
What You Will Learn
Understanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industry
Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used
Study interesting industry problems that are good candidates for being solved By 作者:machine and deep learning
Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry