The Society of Petroleum Engineers, SPE Juba Section is happy to presents and invites you for our monthly virtual technical lecture series from O&G professionals.
Don’t miss this opportunity to attend this Free event, involving presentation session live interactions and asking questions for the guest lecturer.
Topic : Physics-Based Data Driven Reservoir Characterization and Production Prediction
Time: Monday, Apr 26, 2021 02:30 PM in Khartoum/Juba Time local time
Guest Presenter: Prof. Oyinkepreye D. Orodu
Abstract:
The Capacitance-Resistance Model (CRM) is a semi-analytical modelling approach utilising non-linear multivariate regression. Using historical production and injection rates and historical bottom-hole pressure data if available, CRM quantifies the connectivity and degree of fluid storage between injectors and producers in a reservoir. The CRM has typically been applied to waterflood management and performance prediction, and improved reservoir characterisation. The presentation focuses on using CRM for fault characterisation, flow barrier detection, and combination with deep learning (Artificial Neural Network – ANN) for production prediction. Historical and geological data of a far-east oilfield and syn-reservoir provided data for the study. Results show faults with varying degrees of communication, flow barriers detection, and commendable production forecast by CRM and CRM-ANN. Capacitance-Resistance Modelling can be used to corroborate the results of Interference Testing, Tracer Test and 4D Seismic in detecting and characterising faults and as a cost-effective reservoir management tool.