Abstract
Accurate original oil in place (OOIP) estimation is a serious industry concern, not only due to the economic issues but also the further field life and success of the development. The uncertainty surrounding the EE-Pool resource size is due to the unique values of the reservoir areas and net pay. This uncertainty in the reservoir area and net pay has also affected the estimated reserves, resulting in wrongly predicted reservoir potential. In order to reduce technical and economic risks associated with the uncertainty of EE-Pool, a data analytics approach applying different methods of OOIP determination techniques was used. EE-Pool contains a heavy amount of data: production data, PVT data, pressure data, well testing data, rock properties data, and geological data. The value of OOIP from the Material Balance Equation (Straight-Line method) was estimated at 100-million stock tank barrels of oil (MMSTB) for both areas and has been determined as a reference value. Compared with the reference value of OOIP, the volumetric method demonstrated the worst result with 63-% error and 63 MMSTB. While the Monte Carlo Simulation combined with Crystal Ball provided the most optimistic results with 9.1-% error and 9.1 MMSTB of oil.