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Artificial Intelligence in Petroleum Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 2358

Special Issue Editor


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Guest Editor
Department of Petroleum and Natural Gas Engineering, West Virginia University, Morgantown, WV 26506, USA
Interests: artificial neural networks; evolutionary computing and fuzzy logic in earth science; reservoir engineering; natural gas engineering; simulation and modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the past 50 years, petroleum scientists and engineers all over the world have generated a large number of technologies (models and solutions) that have introduced impactful enhancements in oil and gas productions. In the last decade, the generation of new technologies and the adaptation of existing petroleum technologies have been employed to enhance carbon sequestration.

While the original application of artificial intelligence in petroleum engineering started in the early 1990s, in the past decade this avenue has been enhanced and has been proven capable of hugely augmenting all the petroleum technologies of the past 50 years. For example, currently, in petroleum reservoir engineering, artificial intelligence has generated new reservoir simulation and modeling that can provide far superior results (history matching, reservoir geological modeling, production forecasting, production optimization, etc.) than the existing grate numerical reservoir simulation technology that currently is used by CMG, Eclipse, Petrel, and tNavigator. This same fundamental principle is applicable to other petroleum engineering technologies.

The fact is that, in a few years from now, artificial intelligence will become the only technology that is used in petroleum engineering. 

Prof. Dr. Shahab D. Mohaghegh
Guest Editor

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Keywords

  • petroleum engineering
  • artificial neural network
  • reservoir engineering
  • drilling
  • surface facility
  • fuzzy logic

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Published Papers (1 paper)

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Research

14 pages, 6085 KiB  
Article
Storage and Processing of Big Data for Geomagnetic Support of Directional Drilling
by Dmitry V. Kudin, Alexei D. Gvishiani, Izabella M. Nikitina, Ivan O. Belov, Boris A. Dzeboev, Andrew A. Grudnev, Boris V. Dzeranov and Roman I. Krasnoperov
Appl. Sci. 2024, 14(21), 9730; https://doi.org/10.3390/app14219730 - 24 Oct 2024
Viewed by 996
Abstract
Modern satellite positioning and navigation technologies are not applicable in specific areas such as the exploration of oil and gas deposits by means of directional drilling techniques. Here, we can rely solely on natural geophysical fields, such as the Earth’s magnetic field. The [...] Read more.
Modern satellite positioning and navigation technologies are not applicable in specific areas such as the exploration of oil and gas deposits by means of directional drilling techniques. Here, we can rely solely on natural geophysical fields, such as the Earth’s magnetic field. The precise underground navigation of borehole drilling instruments requires a seamless, near-real-time access to operational geomagnetic data. This paper describes the MAGNUS BD hardware-software system, deployed at the Geophysical Center of the Russian Academy of Sciences, that provides the efficient accumulation, storage, and processing of geomagnetic data. This system, based on the Big Data (BD) technology, is a modern successor of the MAGNUS processing software complex developed in 2016. MAGNUS BD represents one of the first cases of the BD technology’s application to geomagnetic data. Its implementation provided a significant increase in the speed of information processing and allowed for the use of high-frequency geomagnetic satellite data and expanding the overall functionality of the system. During the MAGNUS BD system’s deployment on a physically separate dedicated cluster, the existing classical database (DB) was migrated to the Arenadata database with full preservation of its functionality. This paper gives a brief analysis of the current problems of directional drilling geomagnetic support and outlines the possible solutions using the MAGNUS BD system. Full article
(This article belongs to the Special Issue Artificial Intelligence in Petroleum Engineering)
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