Management of Uncertainty in Reservoir Modelling for an Onshore Carbonate Reservoir in the Middle East: A Case Study

As part of a reservoir modelling study for an onshore oil field in the Middle East, our study implemented a workflow with the objective to evaluate the impact of uncertainty on the long-term development scenario. The presence of several geological uncertainties characterized the field: many faults with uncertainty in juxtaposition and conductivity, lateral distribution of permeability in high permeability layers, and uncertainty on the rock typing. A deterministic geological model was available. There were also many dynamic uncertainties. The workflow started with an identification of uncertain variables, both from the static and the dynamic point of view, through an integrated team approach supported by a previous reservoir synthesis (Major Field Review). Subsequently, a screening analysis allowed identifying the relative impact of uncertain variables. After selecting the uncertainties with the largest impact on recovery, use of an experimental design methodology with a space-filling design resulted in alternative history matches. Statistical analysis of forecasts yielded probability density functions and low and high estimates of ultimate recovery. Forty-five uncertain variables, including both static and dynamic uncertainties, characterized the production profiles. Screening allowed reducing these to 11 main uncertain variables. A Wootton, Sergent, Phan-Tan-Luu (WSP) space-filling design yielded 162 simulation runs. Only five out of these corresponded to acceptable history matches. This number being statistically insignificant, a reexamination of the uncertainty ranges followed by a narrowing, allowed obtaining 45 history matches (out of 198 runs). The obtained spread in the cumulative oil production was narrow, with a slightly skewed distribution around the base case (closer to P90 than to P10). The study resulted in an estimation of final uncertainty in reserves that is smaller than the typical uncertainty found in post-mortem analysis of oil field development projects. Other reservoir studies in the company and in literature, employing a similar workflow, yielded outcomes with a similar bias. To tackle this issue, as a way forward we suggest history matching of multiple geological scenarios, either with multiple deterministic cases (min, base, max) or with an ensemble history matching loop including structural model generation, in-filling, and dynamic parameter uncertainty.