The machine learning is not only an important tool for oil and gas big data analysis

but also a general data-driven analysis method. As an important field with a long history and a large data base

oil and gas exploration and development has a great potential for data mining. The use of big data analysis technology for oil and gas field can help decision makers to conduct investment analysis

risk assessment and production optimization

which brings significant economic benefits. The machine learning method has been tried by the researchers applying to the researches on oil and gas. Nowadays

many application scenarios have been proposed with the development of machine learning algorithms

but general solutions for specific scenario are still divided. So that

we introduces the procedure of a machine learning modeling upon the most basic principles

and summarizes the development history of the main three kinds of machine learning methods that can be applied to oil and gas big data analysis. And then based on the characteristics of oil and gas field big data

the core contents

goals and advantages of oil and gas field big data analysis and utilization are discussed

the main application scenarios of machine learning in oil and gas field are analyzed

and the existing problems and countermeasures in typical oil and gas production prediction are summarized.