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Thursday, February 28 • 1:20pm - 1:45pm
Applications and Programming Models: "Integrated Reservoir Modeling and Simulation Optimization Workflow Based on a High-Performance Parallel Computing Cluster," Guoxiang Liu, Energy & Environmental Research Center, University of North Dakota


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Large model size and multiple predictive simulation scenarios are two of the primary challenges in reservoir modeling and simulation. In trying to capture heterogeneity within a reservoir, the cell count can increase drastically by adding horizontal and vertical resolution. In addition, multiple predictive and optimization scenarios designed to investigate strategies for drilling, optimization of production, and net present value analysis and carbon dioxide injection for enhanced oil recovery (EOR) and storage can take considerable time and computational power. These challenges slow down simulation speed and overall computation time, leading to increased project timelines, and can cause project delays. To solve these issues, an integrated model optimization workflow was proposed, as well as the design and construction of a high-performance parallel computer cluster built at the Energy & Environment Research Center (EERC). To obtain the maximum speed-up for this integrated optimization workflow, a scalability test of the cluster for multiple simulation jobs over various cores was performed. This was followed by a grid sensitivity analysis that aims to find the coarsest grid cell size that will capture the necessary heterogeneity of the reservoir. Then numerical tuning was performed with the objective of reducing processing time while minimizing material balance error and solver failure percent. Finally, a sensitivity analysis was performed to identify properties and parameters that most affect the history match or predictive simulations.


Henri Calandra

Henri Calandra obtained his M.Sc. in mathematics in 1984 and a Ph.D. in mathematics in 1987 from the Universite des Pays de l’Adour in Pau, France. He joined Cray Research France in 1987 and worked on seismic applications. In 1989 he joined the applied mathematics department of the French Atomic Agency. In 1990 he started working for Total SA. After 12 years of work in high performance computing and as project leader for Pre-stack Depth... Read More →

Olav Lindtjorn

HPC and Innovation Manager, Schlumberger
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avatar for Jan Odegard

Jan Odegard

Executive Director, Ken Kennedy Institute for Information Technology, Rice University
Jan E. Odegard joined the Ken Kennedy Institute for Information Technology (formerly Computer and Information Technology Institute) at Rice University as Executive Director in 2002. In this role he led the development and deployment of large scale competing resources in support of research. Today, the computational resources deployed at Rice supports the research of over 100 faculty members and close to 500 users. The majority of users are... Read More →


Guoxiang Liu

Research Manager, Energy & Environmental Research Center, University of North Dakota

Thursday February 28, 2013 1:20pm - 1:45pm
DH 1064 Duncan Hall