A Detailed Survey on Machine Learning (ML) Techniques in Oil and Gas Industry

Abstract

This survey paper presents the concepts for extending and improving ML algorithms for mining in the field of Oil and Gas (O&G Industry). The concept of this survey is to take ML based energy efficiency analysis from O & G fields and use the concept of big data, which means that ML is a knowledge mining technique, and then analyze how this method is applied in the O & G field. The gas industry has found some difficulties, such as incomplete data, not suitable for large industries or large industries, and some inaccurate results. Therefore, some existing difficulties have arisen, and it will be a higher level. This article aims to analyze the best and accurate results of energy data, and make quick predictions (early predictions) of O & G fields from the analyzed data. This paper analyzes how ML algorithms change a critical piece of the energy area in the oil and gas industry. Basing on the investigation of ML application prospects and the survey of existing applications, we frame the latest patterns in creating ML-based tools and distinguish their consequences for speeding up and de-risking with processes in the industry.