Abstract
Stratigraphic forward modeling (SFM) is an innovative approach to subsurface facies prediction at the basin scale that augments and overcomes some of the limitations of conventional seismic, well, and analog data. As a multidisciplinary approach to play characterization, SFM improves the efficiency of current workflows, which is important given the current downward pressure on capex in oil and gas companies.
A 2D SFM study on data from Browse basin, NW Australia, was conducted to enhance the prediction of facies distribution and improve play characterization by integrating SFM with other disciplines. The work started with seismic interpretation and depth conversion. Then, a third to fourth-order sequence stratigraphy interpretation was performed to determine the main sequence boundaries, maximum flooding surfaces, and a relative sea-level curve. The sequence stratigraphy results were later used to infer some of the inputs and parameters of the SFM model. The model simulates the deposition of clastic and carbonates from the Turonian (Late Cretaceous) to the present day.
The results from the model were used to validate some of the geological concepts and the seismic interpretation. In addition, the approach enabled the prediction of reservoir quality, reservoir distribution, the presence of the seal, and the quantification of erosion. A 2D petroleum system model (PSM) covering the area from the Yampi shelf to the Seringapatam sub-basin was built using seismic interpretation, regional tectonic information, source rock geochemistry, and paleo heat flow. The results from SFM were integrated into a 2D PSM by resampling facies and erosion properties for each of the finely subdivided layers. The high-resolution 2D PSM with refined facies was simulated in geological time to model the basin evolution and its impact on all elements and processes of the petroleum system of Browse basin, which have been validated with nearby fields.
As a result of this integrated approach, the risk of charge and entrapment in prospective stratigraphic traps was better understood and quantified. In addition, this approach helped to increase yet-to-find (YTF) hydrocarbon resources by accurately predicting reservoir distribution and extent. The generation of a 2D SFM and its integration within a multidisciplinary approach to predict facies represents a novel addition to exploration workflows. Adopting such an approach can improve significantly on the understanding of hydrocarbon entrapment and further reduce exploration risks.
