Data science applications in oil and gas exploration: an in-depth perspective

Author:

Nikhalat Jahromi Hamed1,Jorge Alípio Mário2

Affiliation:

1. Postdoctoral Research Fellow, LIAAD, INESC TEC, Rua Dr. Roberto Frias, Porto, Portugal (corresponding author: )

2. Associate Professor, LIAAD, INESC TEC, Rua Dr. Roberto Frias, Porto, Portugal; Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, Porto, Portugal

Abstract

Low oil and gas prices have motivated petroleum executives to look into cost reduction in their supply chains more seriously. To this end, a technology considered in hydrocarbon exploration is data science. There are three exploration-related geoscientific domains in which data science is applied: surface geology, structural geology and reservoir property issues. This research provides an in-depth perspective on data science applications in these domains by considering a variety of work in each of them. The result is an understanding of the specific geoscientific problems studied in the literature along with the relative data science models. This way, this work tries to lay the ground for a mutual understanding on oil and gas exploration between the data scientists and geoscientists.

Publisher

Thomas Telford Ltd.

Subject

General Energy

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Dynamic risk analysis for oil and gas exploration operations based on HFACS model and Bayesian network;Petroleum Science and Technology;2024-01-31

2. A combination model of wavelet analysis and neural network for predicting oil and gas exploration accidents;Petroleum Science and Technology;2022-01-27

3. Editorial;Proceedings of the Institution of Civil Engineers - Energy;2019-08

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