|Multimodal visualization of giant oil and gas reservoir models.|
Mathematical modeling and numerical simulation play a major role in managing and predicting the behavior of these systems using large supercomputers. With the aid of evolving measurement technologies a vast amount of geoscience, fluid and dynamic data is now being collected.
Consequently, more and more high resolution, high fidelity numerical models are being constructed. However, certain challenges still remain in model construction and simulating the dynamic behavior of these reservoirs.
|The benefits of fine-scale simulation are improved accuracy and a higher rate of oil recovery.|
Computational challenges include effective parallelization of the simulator algorithms, cost-effective large-scale sparse linear solvers, discretization, handling multi-scale physics, complex well shapes, fractures, complaint software engineering with the rapidly evolving super computer architectures, and effective visualization of very large data sets.
This presentation will cover examples for the giant reservoir models using billion plus elements, model calibration to historical data, challenges, current status, and future trends in computational modeling in reservoir modeling.
|Dr. Ali H. Dogru|
His academic experiences include University of Texas at Austin; Norwegian Institute of Technology; California Institute of Technology; University of Texas; and Istanbul Technical University. He is a visiting Scientist at Earth Sciences at MIT. He holds a PhD from The University of Texas.
He has 12 U.S. patents, is the recipient of the SPE’s John Franklin Carl award, SPE's Reservoir Description and Dynamics award, and a recipient of World Oil’s Innovative Thinker award. He has published extensively.