Subsurface appraisal activities are employed to reduce reservoir uncertainties. Field appraisal/delineation is crucial to understand the subsurface complexity and define the extent of reservoir. In such scenarios, the ability to appropriately characterize reservoir is a primary factor that determines economic viability of a development project. The high cost associated with appraisals of petroleum fields requires manageable risk and uncertainty quantification. Often, results from appraisal campaigns are not enough to reasonably justify decision of developing the field.
An efficient methodology for quantification of subsurface uncertainties during the appraisal stage was implemented to frame the objectives for achieving optimum outcomes. The approach is more systematic in comparison to classical methods to gain better understanding of uncertainty parameters, capture level of uncertainty and identify optimal model for the field development. Production forecast using probabilistic approach provides good estimate of cumulative oil or recovery factor considering the impact of uncertainties and risk.
This study employs uncertainty quantification and optimization workflow for assisted history matching and forecast during appraisal stage. Uncertainty parameters with ranges and distribution, response parameters along with criteria set were framed into the workflows of sensitivity, history matching and uncertainty analysis. Experimental design techniques (OVAT and Latin Hypercube) were used for sensitivity analysis and uncertainty parameter reduction. Objectives set for scope of studies were driven with detailed analysis of the simulation runs and successfully culminated the promising results within specified project time duration.
The methodology is applied to onshore field in the Middle East during the appraisal phase with limited wells.