Statistical Learning for Improved Reservoir Characterization
A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Sedimentology, Stratigraphy and Palaeontology".
Deadline for manuscript submissions: closed (15 July 2020) | Viewed by 236
Special Issue Editors
2. Basrah Oil Company, Basrah, Iraq
Interests: reservoir characterization; data analytics; geostatistics; reservoir simulation; statistical reservoir modeling; optimization
Special Issue Information
Dear Colleagues,
It’s my pleasure to submit your work for possible publication at the Geosciences Journal (Switzerland) under a special issue called “Statistical Learning for Improved Reservoir Characterization”. In this issue, we welcome variety of research paper related to adopting various advanced statistical learning algorithms for improved reservoir characterization. The papers may be about facies classification, modeling and prediction. In addition, the papers about permeability estimation as a function of well logging data, core measurements, and facies are also preferred. Moreover, some other papers that are related to the data integration and correlation of various data sources and scales, such as core data, well logging, and seismic are also welcomed. Papers about using the learning algorithms of missing data imputation of petrophysical parameters may be included in this special issue.
Dr. Watheq Al-Mudhafar
Dr. Christine Noshi
Guest Editors
Manuscript Submission Information
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Keywords
- Reservoir Characterization
- Machine Learning
- Statistical Modeling
- Facies Modelling
- Permeability Correlation
- Petrophysical Data Analytics
