--> Data Constrained Stratigraphic Modeling, by D. E. Watts, W. C. Ross, J. A. May, and C. Greenberg; #90986 (1994).

Datapages, Inc.Print this page

Abstract: Data Constrained Stratigraphic Modeling

Dale E. Watts, William C. Ross, Jeff A. May, Cathy Greenberg

A quantitative stratigraphic modeling package has been developed and tested which provides a reservoir-prediction technology appropriate for exploration applications. The computer-based, two-dimensional modeling program accepts geologic input from the basin of interest and utilizes this information to quantitatively project and constrain lithology distribution away from well control along a modeled dip transect.

The majority of currently published two-dimensional models place most of their emphasis on the simulation of basin fill geometries. In contrast, the thrust of our quantitative stratigraphic modeling program has been to address facies modeling for lithologic prediction. The basic conceptual framework utilized in modeling basin fill involves three major parameters: sea level, subsidence, and sediment supply. The interaction of these three parameters combined with conservation laws and the concepts of base level, and grade compose the basic elements of the stratigraphic modeling software. To test and calibrate the model we utilized empirical relationships established between basin fill geometries and deep water sand distributions along a regional stratigraphic cross-section through the M astrichtian-aged FoxHills and Lewis Formations of South-Central Wyoming.

Simulation of the FoxHills-Lewis system was constrained by model parameters derived from analysis of the basinal stratigraphy. Input files for subsidence, sediment supply, initial basin bathymetry, and equilibrium profiles are derived from reconstructed stratigraphic cross-sections. Sand:mud ratios were derived from available log data. The simulation objective was to achieve a close geometric match between the model output and the reconstructed profiles. Once a satisfactory match was achieved the lithology distribution algorithms operated to distribute sands and muds across nonmarine, shallow marine, and deep marine environments. Model runs thus constrained produced variations in the percentage of sand deposited in shallow versus deep water environments over time, which compared favor bly with lithologic data from the basinal dataset.

AAPG Search and Discovery Article #90986©1994 AAPG Annual Convention, Denver, Colorado, June 12-15, 1994