The November issues of SPE Reservoir Evaluation & Engineering and SPE Production & Operations are now available in the OnePetro online library. Each issue presents peer-reviewed papers, and both include spotlight sections on data analytics.
The spotlight section in the newest SPE Reservoir Evaluation & Engineering focuses on machine learning and data analytics in petroleum engineering and presents the following four papers:
- SPE 195690, A Machine-Learning Methodology Using Domain-Knowledge Constraints for Well-Data Integration and Well-Production Prediction
- SPE 187361, An Integrated Machine-Learning Approach to Shale-Gas Supply-Chain Optimization and Refrac Candidate Identification
- SPE 191400, Data-Driven In-Situ Sonic-Log Synthesis in Shale Reservoirs for Geomechanical Characterization
- SPE 197053, Simplified Dynamic Modeling of Faulted Turbidite Reservoirs: A Deep-Learning Approach to Recovery-Factor Forecasting for Exploration
These papers are presented in addition to other peer-reviewed work covering topics such as unconventional reservoirs, petrophysics, hydraulic fracturing, and production processes.
The latest issue of SPE Production & Operations includes a spotlight section on data analytics that presents the following two papers:
SPE 195594, Data-Driven Modeling of Carbon Dioxide Corrosion for Integrity Management Application
SPE 192393, Use of Advanced Process Control for Automating Conventional Oilfield Operations