| Abstract |
Performance forecasts can either significantly overestimate or underestimate a subsurface resource capacity due to uncertainties associated with the collected data and the evaluation process. We applied a process developed around the Experiment Design methodology to capture relevant uncertainties existing in the Darajat's field static model construction, the dynamic simulation model building, calibration, and forecasting. This process systematically identifies, ranks, and quantifies key parameters affecting field performance. It generates a full range of probabilistic field generating capacity distributions that can provide a better platform for the economic evaluations, development planning, and decision making than relying on a single deterministic projection. The ranking of the reservoir and geologic parameters' uncertainty and the projected performance distribution provide a framework for the field operator to explore different expansion alternatives as well as to develop an effective risk management plan to mitigate the potential shortfalls. |