Reservoir Engineering and Carbon Sequestration
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Chemical Engineering and Technology".
Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 3084
Special Issue Editor
Interests: data analytics; deep learning; computational modeling; reservoir engineering; reservoir simulation; subsurface flow modeling; CO2 geological sequestration; petroleum geoscience
Special Issue Information
Dear Colleagues,
For sustainable and environment-unharmful energy development, the reliable analyses of subsurface fluid flow are essential since most energy resources are obtained from the underground space. However, the subsurface domain is uncertain and thereby the robust and reliable computer-assisted tools for interpreting complex geo-data that are related to a broad range of disciplines, such as geology, petrophysics, reservoir engineering, and CO2 storage. Uncertainty quantification needs computational efforts to understand the earth system and to optimize the production operations for sustainable energy-resources development. This special issue pursues sustainability managing different-scale data to solve complex geoscience problems related to reservoir engineering and carbon sequestration. The topic of interest is the cutting-edge computer-assisted technologies to solve geoscience problems and to optimize the complex multidisciplinary problems. Related topics include but are not limted to the following subjects:
(1) Reservoir engineering
(2) Compuational modeling
(3) Optimization
(4) Data science (deep learning, machine learning, data assimilation)
(5) CO2 geological storage
(7) Uncertainty quantification
(8) Multiphase flow associated with earth system
(9) Geothermal energy
Prof. Dr. Changhyup Park
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- data science
- deep learning
- computational modelling
- reservoir engineering
- CO2 storage
