Semantic Scholar Open Access 2021 429 sitasi

Application of machine learning and artificial intelligence in oil and gas industry

A. Sircar K. Yadav Kamakshi Rayavarapu N. Bist Hemangi Oza

Abstrak

Abstract Oil and gas industries are facing several challenges and issues in data processing and handling. Large amount of data bank is generated with various techniques and processes. The proper technical analysis of this database is to be carried out to improve performance of oil and gas industries. This paper provides a comprehensive state-of-art review in the field of machine learning and artificial intelligence to solve oil and gas industry problems. It also narrates the various types of machine learning and artificial intelligence techniques which can be used for data processing and interpretation in different sectors of upstream oil and gas industries. The achievements and developments promise the benefits of machine learning and artificial intelligence techniques towards large data storage capabilities and high efficiency of numerical calculations. In this paper a summary of various researchers work on machine learning and artificial intelligence applications and limitations is showcased for upstream and sectors of oil and gas industry. The existence of this extensive intelligent system could really eliminate the risk factor and cost of maintenance. The development and progress using this emerging technologies have become smart and makes the judgement procedure easy and straightforward. The study is useful to access intelligence of different machine learning methods to declare its application for distinct task in oil and gas sector.

Topik & Kata Kunci

Penulis (5)

A

A. Sircar

K

K. Yadav

K

Kamakshi Rayavarapu

N

N. Bist

H

Hemangi Oza

Format Sitasi

Sircar, A., Yadav, K., Rayavarapu, K., Bist, N., Oza, H. (2021). Application of machine learning and artificial intelligence in oil and gas industry. https://doi.org/10.1016/J.PTLRS.2021.05.009

Akses Cepat

Lihat di Sumber doi.org/10.1016/J.PTLRS.2021.05.009
Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
429×
Sumber Database
Semantic Scholar
DOI
10.1016/J.PTLRS.2021.05.009
Akses
Open Access ✓