Quantifying the Risk on Reservoir Quality with Forward Stratigraphic Modelling in Frontier Areas - Orphan Basin, Canada
Forward stratigraphic modeling allows assessing the extension, thickness and quality of reservoir bodies in underexplored areas. However, most of the data used in such basins is subject to uncertainties which become critical in frontier areas where very little information is available for calibration. The potential range of input parameters variation leads to a high variability of the modeling simulation results that should be quantified to reduce the exploration risk.Traditionally, risk assessment is done performing multi-realizations with a Monte-Carlo sampling which requires a lot of time, sometimes months, when hundreds of simulations are required on a high resolution model. To overcome these delays unaligned to the E&P industry constraints, we here present a new workflow linking forward stratigraphic modeling to a dedicated uncertainty analysis tool based on response surfaces.If the later technology is commonly used in reservoir engineering, it is quite unknown in exploration. In this approach, a set of simulations - the experimental design - is used to compute response surfaces that provide very fast estimations of the simulator outputs for any parameter values. The uncertainty study is then conducted from the response surface predictions only. A limited number of simulations is generally enough to obtain reliable estimations. The total time required to estimate the risk associated to the model uncertainties is thus drastically reduced.The Canadian passive margin is used to illustrate this workflow. The focus is made on the turbiditic sandy reservoirs of the Upper Cretaceous formation of the Orphan Basin and the uncertainties linked to its quality in terms of net to gross ratio and thickness. Only one well being available for calibration, the impact of subsidence, sediment sources supply and content, and sediment transport is analyzed to understand the influence of each parameter. A propagation is then realized to quantify the risk on the reservoir quality and the probability of presence of reservoir facies. Applied to the full reservoir unit and not only at a single well location, this approach provides relevant probability maps critical in the decision-making process.
AAPG Datapages/Search and Discovery Article #90350 © 2019 AAPG Annual Convention and Exhibition, San Antonio, Texas, May 19-22, 2019