This practical and highly-interactive course includes real-life case studies and exercises where participants will be engaged in a series of interactive small groups and class workshops. 

 

This course is designed to provide participants with a detailed and an up-to-date overview of the Reservoir Characterization: A Multi-Disciplinary Team Approach. It covers the importance of a multi-disciplinary team approach in reservoir characterization; integrating geology, geophysics and engineering; the technology in reservoir characterization; the data types and quality control; the static models and the geostatistical methods in static modeling; the rock typing and petrophysical analysis; the structural modeling and fault representation; the 3D geological model building; and the integration of core and log data in static models. 

 

Further, the course will also discuss the dynamic models and reservoir simulation grids; the fluid properties and PVT (Pressure-Volume-Temperature) analysis; the history matching and calibration and production forecasting using dynamic models; the sensitivity analysis in dynamic models and reserve estimation methods; identifying and evaluating by-passed pay zones; and the strategies for reducing development time and costs. 

During this interactive course, participants will learn the production enhancement techniques; the rejuvenation of old fields through integrated approaches; the integration of static and dynamic models for field development planning; the risk assessment and uncertainty analysis in reservoir characterization; the role of emerging technologies (AI, Machine Learning, etc.) in reservoir characterization; the challenges and solutions in a multi-disciplinary team approach; and the best practices and lessons learned in reservoir characterization and future trends.