Representing shoreface reservoirs with a rule-based facies model: The GEOPARD algorithm
Abstract
We introduce a new rule-based algorithm called GEOPARD, which models shoreface deposits by following geological principles. In this algorithm, the outcomes of geological processes are represented as rules that are integrated into the core of a standard geostatistical modeling framework. The GEOPARD builds on the stochastic object-based facies modeling technique and incorporates a Bayesian framework for conditioning to data and reducing uncertainty. This paper outlines the geological prior model of the GEOPARD algorithm, which generates facies geometries and controls object placement using geological rules. Specifically, the algorithm builds up a parasequence by stacking a succession of prograding shoreface bedsets, bounded by small-scale hiatus, until a final point of maximum shoreline advance. Model parametrization closely follows the geological conceptual model. The rules are implemented as a series of fully automated modeling steps, mapping the wide variety of facies geometries typically associated with shallow-marine deposits. The functionality of GEOPARD is demonstrated through a series of scenarios, including the reproduction of features observed in an outcrop analogue and benchmarking against the truncated Gaussian simulation method. Key modeled features include sand-body thickness, lateral extent of facies, overall parasequence geometry, and the spacing and dip of bedset bounding surfaces.