Validating 3-D structural models with geological knowledge for improved uncertainty evaluations

Several stochastic approaches have recently been developed to evaluate uncertainties in 3-D geological models based on imprecise geological data. Multiple models are generated through random changes of input parameters, according to defined probability distributions. This leads to a new problem: randomly generated realizations might be topologically different or they might be in contrast to expected geological constraints or settings. We present here a method to enable automatic checks of models based on reliability filters encapsulating aspects of geological knowledge. We apply those filters to a model of a graben structure and obtain an ensemble of acceptable realizations, representing the range of uncertainty, but preserving expected geological features. (C) 2014 The Authors. Published by Elsevier Ltd.