Abstract:

With the advances in subsurface characterization and imaging, petroleum reservoir models now-a-days routinely consist of multimillion cells representing geologic heterogeneity. Reconciling such high resolution geologic models to flow and transport data leads to a non-linear and ill-posed inverse problem. In this talk I will briefly touch upon three aspects of such inverse modeling: (1) recasting flow and transport equations as tomographic equations using a high frequency asymptotic approach and solution of the forward problem (2) parsimonious representation of geologic models via re-parameterization using basis functions and (3) solution of the inverse problem via multi-scale multi-objective optimization. Several field applications will be presented to examine the power and limitations of the approach.

Bio:

Dr. Akhil Datta-Gupta is Regents Professor, University Distinguished Professor and holder of the L.F. Peterson ’36 Endowed Chair in the Harold Vance Department of Petroleum Engineering at Texas A&M University. Dr. Datta-Gupta’s research interests include high resolution flow simulation, petroleum reservoir management/optimization, large-scale parameter estimation via inverse methods and uncertainty quantification. He is a Society of Petroleum Engineers (SPE) Honorary Member (the highest honor bestowed by the society) and received two of the top three technical awards (Carll Award, 2009; Uren Award, 2003) given by the society for his contributions related to petroleum reservoir characterization and 3-D streamline simulation. In addition to his SPE awards, he is recipient of the SURA (Southeastern Universities Research Association) Distinguished Scientist Award (2019) and the U.S. Department of Energy Award for Outstanding Contributions to Basic Research in Geosciences (2008). Dr. Datta-Gupta has published over 100 peer reviewed articles and 4 books. His research program is funded by NSF, DOE and oil companies world-wide. Dr. Datta-Gupta was elected to the U.S. National Academy of Engineering and The Academy of Medicine, Engineering and Science of Texas in 2012.

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