Petroleum Exploration and Development will publish a special issue on the topic of "Subsurface Analytics; Application of Artificial Intelligence and Machine Learning in Reservoir Engineering, Reservoir Modeling, and Reservoir Management" in February, 2020 (Volume 47, Issue 1).
Positively influencing subsurface related decision making in the oil and gas industry is the most important contribution of any new technology. Subsurface Analytics that is defined as the application of Artificial Intelligence and Machine Learning (AI&ML) in Reservoir Engineering, Reservoir Characterization, Reservoir Modeling, and Reservoir Management, is the manifestation of subsurface Digital Transformation in the upstream Exploration and Production. The focus of this Special Issue is on the realistic and useful application of AI&ML that can make a substantial difference in high-impact decision making and transforming the traditional approaches to reservoir engineering problem solving to the new set of AI-based approaches.
The focus of this special issue will be on conventional and unconventional subsurface related topics including:
- Well logs,
- Rock typing
- Completion optimization
- Hydraulic fracturing
- Reservoir simulation
- Coupled reservoir-wellbore simulation
- History matching
- Production forecasting
- Infill location optimization
- Water flooding optimization
- Water and/or gas injection optimization
- Reduced order modeling of numerical reservoir simulation
- Any other subsurface related activities
Research papers are now being invited. Deadline for manuscript submission is May 31, 2019. All manuscripts for this special issue will be only accepted in English.
Managing Guest Editor
Shahab D. Mohaghegh; Professor, Petroleum & Natural Gas Engineering, West Virginia University
- Fareed Alhashmi; Executive Director of Development, Dragon Oil
- Dr. Rahim Masoudi; Chief Technical Officer, Petronas
- Mr. Keith Holdaway; Advisory Industry Consultant, SAS Institute, Inc.
- Dr. Jalal Jalali; Senior Reservoir Engineer, EQT Production
Manuscripts should be submitted online by registering and logging into ONLINE SUBMISSION (Click Here). Please indicate that your contribution is for this Special Issue in your cover letter.
Submitted manuscripts should not have been published previously nor be under consideration for publication elsewhere.
Online Office Login for Editors and Peer Reviewers
Editors Entrance (Click Here)
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