Dr. Miguel Bosch, CEO/Founder of Info Geosciences, presents "Inference problems in complex models and applications to Earth sciences" at the MIT Earth Resources Laboratory.

"The inference of the subsurface earth structure and properties requires the integration of different types of data, information and knowledge, by combined processes of analysis and synthesis. To support the process of integrating information, the common concepts of data inversion and tomography are evolving to expand its application to models with multiple inner components (properties, scales, structural parameters) that explain multiple data (geophysical survey data, well-logs, core data). The probabilistic inference methods provide the natural framework for the formulation of these problems, considering a posterior probability density function (PDF) that combines the information from the prior knowledge and the new sets of observations. To formulate the posterior PDF in the context of multiple datasets and model components it is required to identify and model the causal or statistical dependencies across them. The dependencies can be described appropriately via direct acyclic graphs, conforming an inference network. The posterior PDF of the network formulates by the product of the prior information PDFs of the primary nodes, the conditional PDFs of the inner links and the data likelihood functions of the data nodes. Once the posterior probability has been modeled, realizations can be obtained following a sampling approach or searching for a maximum posterior probability earth medium configuration. Examples of inverse problems in complex models can be shown at various scales. At local scale, for example, the distribution of rock lithology, porosity and fluid saturation is inferred from pre-stack seismic data and a calibrated rock-physics model. At regional scale, joint inversion of gravity and magnetic data is applied for the estimation of the lithological structure of the crust, with the lithotype body regions conditioning the mass density and magnetic susceptibility fields. At planetary scale, the Earth mantle temperature and element composition is inferred from seismic travel-time and geodetic data. Challenging problems in inner Earth and fluid reservoir dynamics could be solved with these methods."