Simulation of Stratigraphic Architecture from Statistical and Geometrical Characterizations1

Stratigraphic modeling based on physical and geologic principles has been improved by more sophisticated process models and increased computer power. However, such efforts may reach a limit in their predictive power because of the stochastic, multiscaled nature of the physical processes involved. Building on techniques from the geostatistical literature, a conditional simulation method, dubbed “SimStrat,” has been developed to improve predictions of stratigraphic architecture from limited data. No physical processes are invoked. Rather, the prediction is based solely on geometric and statistical principals. The method takes as input sonar bathymetry, seismically defined stratigraphic horizons, and core-defined horizons. Each stratigraphic horizon is characterized using spectral modeling and coherence modeling for adjacent horizons. Predictions of subsurface horizons are improved where seafloor bathymetry conforms with the underlying strata. Conditional simulations can then be generated that conform to available data constraints and statistical characterization. Tests with synthetic data in one and two dimensions for differing spectral models confirm the reliability of the method.