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|Title:||Stochastic simulation of the morphology of fluvial sand channels reservoirs|
|Orientador:||Almeida, José António de|
|Publisher:||Faculdade de Ciências e Tecnologia|
|Abstract:||The characterization of fluvial-type oil reservoirs using stochastic simulation algorithms is a complex problem because the morphology of the channels are complex and are not fully characterized by the two-point statistics of the geostatistical models (variograms and/or spatial covariances). Among these features, for example, are delta morphologies and meander-form floodplain where the channels form a complex pattern of the resulting 3D sediment accumulation by the former waterway system. This work presents an innovative methodology designed to simulate 3D stochastic images of the morphology of fluvial sand channels reservoirs. It is based on the following steps: (a) preparation of histograms of length, width and height of sand channels and a 2D image of local orientations; (2) simulate widths and heights of the hypothetical sand channels along their paths; (3) generate randomly skeletons of hypothetical channels and associate the width and height dimensions generated in the previous step (Boolean vector model); (4) convert the Boolean vector model into a raster model and link regions of uncertainty according distances to the skeleton; (5) finally, using the method of Probability Field Simulation (PFS) condition the Boolean model with a model of variogram and resolve the regions of uncertainty. The outputs are sets of binary images (channel – sand / not channel – shale) that can be filled by values of porosity and permeability. This methodology was successfully tested for modeling channel sand reservoir of a river of the Middle East. Specifically, results are discussed in connection with the image of local orientations together with an analysis of the local and global uncertainties of the model.|
|Description:||Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)|
|Appears in Collections:||FCT: DCT - Dissertações de Mestrado|
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