QUANTITATIVE STRATIGRAPHIC PREDICTION: TURNING DOODLES INTO DIGITS

Successful hydrocarbon exploration and production depends on the ability to be predictive. Prediction must transcend qualitative description by utilizing quantitative tools, workflows, and approaches that allow us to maximize and apply all available data. This presentation illustrates how process-based modeling tools predict sediment routing systems, the resulting three-dimensional sedimentary architecture, and facies distribution. A process-based, quantitative approach is used for predicting sedimentary environments by integrating data and knowledge pertaining to modern depositional systems, subsurface, outcrops, laboratory experiments, and numerical modeling tools. A more quantitative and rigorous data collection and analytical approach is required to facilitate the building of data-constrained predictive models based on first principles. Appropriate sensitivity and uncertainty analysis that captures the complexity of the predicted systems is crucial. A set of case studies demonstrate workflows that integrate diffusion-based forward stratigraphic prediction with petroleum systems prediction. The case studies are from a deep-water system with a mobile substrate and show the influence of accommodation, basin geometry and topography, sediment supply on the sediment routing, and impact of a high resolution, three-dimensional sedimentary model on petroleum systems prediction.