Synthesis of geological, technical, economic and other information related to the geological system under study for the creation of a unified numerical model. Basic principles of stochastic simulation. Correlation and consolidation of heterogeneous data: covariogram and the linear model of coregionalization for several random variables. Use of categorical variables for the description of lithofacies: indicators and categorical variables, kriging and cokriging with indicators. Development of lithofacies models using Plurigaussian simulation, incorporation of geological rules for simulation variables. Introduction to the inverse problem. Methods for solving linear inverse problems in the geosciences. Nonlinear inverse problems and solving methods (McMC, Iterative Algorithms). The inverse problem as an optimization problem. Likelihood function of the parameters of the geological model, spatiotemporal configuration (history matching). Case studies: Use of acoustic resistance seismic measurements as additional information to improve the knowledge of porosity from borehole sampling. Reservoir volumetrics using data from boreholes related to the depth of the roof and its thickness, assisted by seismic measurements after velocity processing. Determination of the spatial distribution of lithofacies of a simulated aquifer based on its response to pumping conditions.
ECTS : 4
Language : el, en
Learning Outcomes : • Has become familiar with the use of categorical variables for describing geological phases. • Has understood the concept and use of Geological Rules for 3D visualization of geological phases. • Uses specialized software for developing numerical geological models using the multigussian simulation technique. • Knows the possibility of further improving the accuracy of the model by incorporating information related to the system s response to external tests such as pumping tests, water injection tests, etc.