Modern Reservoir Characterization : Integrating Artificial Intelligence (AI) with Traditional Methods
During this workshop, participants will develop a more comprehensive grasp of the geophysical theory of seismic inversion and explore advanced seismic reservoir characterization techniques. Discover the essential steps in the seismic reservoir characterization workflow using machine learning, covering data processing to inversion analysis. Acquire valuable knowledge applicable to your everyday projects.
In classical reservoir characterization, it is commonly assumed that the reservoir exhibits both elastic and hydraulic isotropy. However, real reservoirs often exhibit anisotropic characteristics and spatial heterogeneity on multiple scales. Relying solely on core and log data may not accurately represent the larger reservoir volume. Therefore, the most effective way to accurately analyze the physical properties of most actual reservoirs, across their entire volume, involves utilizing advanced machine learning methods for acquired and interpreted seismic data.
Workshop Objectives
This workshop aims to offer Exploration & Development professionals the chance to gain practical experience in a range of Seismic Reservoir Characterization techniques. This comprehensive workshop will provide a complete overview of seismic approaches, including the underlying theoretical principles and practical techniques used in real-world scenarios.
About the Presenter
Dr. Yasir Bashir
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Reservoir simulation & prediction
This workshop explores reservoir simulation techniques used to model underground oil and gas reservoirs and predict their future performance. Participants will learn how to build geological and reservoir models, run numerical simulations, and interpret results to optimize recovery strategies. The course covers history matching, sensitivity analysis, and forecasting under uncertainty to support efficient reservoir development planning.