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Inverse problems in reservoir complex models - advances and future

Miguel Bosch

Complex models in Earth Sciences refer to the combination of multiple properties, scales, observations, and physics relating the various model components for the description of geological objects. As natural objects the reservoirs, earth crust or planets require a multidisciplinary description. Formulating such a description into a joint numerical framework is important for modeling and inference. This involves modeling through a network of observations and model components related by the corresponding scientific disciplines: geophysical survey methods, rock-physics, geology, geochemistry, etc. Moreover, geometric advance in computational resources, data availability and algorithms, opens the opportunity for integrative applications to alleviate current long workflows of processes and intervening specialists.  The probabilistic inference method provides the natural mathematical framework for the formulation of these problems, considering the modeling of prior information and data likelihood functions to combine in the posterior probability associated to configurations of the complex model. I briefly review the basic formulation, present examples of applications to reservoir cases, and discuss about the future of reservoir model building technology.

Speaker: Miguel Bosch, Info Geosciences Technology and Services

Monday, 02/03/20


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Green Earth Sciences Building

367 Panama St, Room 104
Stanford University
Stanford, CA 94305

Website: Click to Visit