As oil and gas exploration and production occur in deeper basins and more complex geologic settings, accurate characterization and modeling of reservoirs become paramount. Existing technologies for reservoir characterization and modeling have proven inadequate for delivering detailed 3D predictions of reservoir architecture, connectivity and rock quality at scales that impact subsurface flow patterns and reservoir performance. Because of the gap between the geophysical and geologic data available constraints from external analog systems are needed.
Enabled by the rapid advancement in digital and computational technology, computational stratigraphy is a physics-based forward modeling system that simulates the Earth’s surface processes through computation of fluid flow and sediment transport to generate high resolution, geologically realistic models. Computational stratigraphy models can overcome the data sparsity and resolution gap and quantitatively predict reservoir heterogeneity in 3D, across all scales and for any depositional environment.
Integrating computational stratigraphy with existing reservoir characterization and modeling workflows, significantly improves reservoir performance forecasts and development uncertainty assessments. Integrated computational stratigraphy workflow combines characterization and interpretation of field data with sedimentologic and stratigraphic concepts to develop geologic scenarios for forward computational stratigraphy modeling.
Computational stratigraphy reservoir forecast variations emerge from fundamental geologic uncertainties rather than products of ad hoc rock property ranges and spatial correlation structures. Computational stratigraphy models with the greatest differences can be compared more directly with field data and the range of predictions can be more confidently related to physical reality.