Seminar by Prof Tapan Mukerjee, 5 July 2018 at ARRC

June 29th, 2018

Prof Tapan Mukerji of Stanford University will visit Deep Earth Imaging at ARRC on Wednesday, 4 July and will present a seminar entitled Bayesian Evidential Learning and Value of Information for decision-focused uncertainty quantification and geomodeling in subsurface systems, at 11.00 in the ARRC Auditorium. Tapan is visiting Perth to lead the Rock Physics for Quantitative Seismic Reservoir Characterization EAGE Short Course on 5 July.

All are welcome to attend. Please pass this note to your colleagues who might be interested. Please contact Bianca Moiler at DEI if you would like to meet separately with Tapan.

Tapan Mukerji is an Associate Professor (Research) in the Department of Energy Resources Engineering and the Department of Geophysics at Stanford University. He co-directs the Stanford Center for Earth Resources Forecasting (SCERF), and is associated with the Stanford Rock Physics and Borehole Geophysics (SRB) and Stanford Basin and Petroleum System Modeling (BPSM) research groups.

Tapan obtained his PhD in Geophysics from Stanford University, in 1995, and MS (Geophysics) and B.S. (Physics) degrees from Banaras Hindu University, India. His research interests include rock physics, geostatistics, wave propagation, stochastic methods for quantitative reservoir characterization, time-lapse reservoir monitoring, and geomodeling applications.

He was awarded the Karcher Award in 2000 by the Society of Exploration Geophysicists. He is a co-author of The Rock Physics Handbook, Quantitative Seismic Interpretation, and The Value of Information in the Earth Sciences, all published by Cambridge University Press. In 2014 Tapan (together with Gary Mavko, Jack Dvorkin and Dario Grana) was awarded the ENI award – the so called “Energy Nobel Prize” – for pioneering innovations in theoretical and practical rock physics for seismic reservoir characterization.

In 2017, Tapan’s book The Value of Information in the Earth Sciences received the finalist publication competition award from the Decision Analysis Society of the Institute for Operations Research and Management Sciences.