Perpustakaan Digital ITB

Enhanced Oil Recovery (EOR) applications are highly recommended and required in Yemen country to maintain stable levels of oil production. The field selected for this research is located in Yemen, where relatively-thin sandstone reservoirs are dominant at moderate depths. The reservoir is highly undersaturated with an API gravity of 14.2 and a very low solution gas-oil ratio (GOR), initial oil viscosity (?o) of 420 cP. The reservoir is naturally producing with the support of a strong water drive at the bottom, however, the increase in water cut poses a disadvantage for this reservoir. Over time, the oil production will decline and development plans will be required to improve the oil recovery. This research aims to optimize the oil recovery factor and the interest in the overall project economy by evaluating the optimization of the steam flood process based on the Stochastic analysis with the highest Recovery Factor (RF) and the highest Net Present Value (NPV) objective functions. Two optimization techniques have been used to perform the data analysis, namely the Deterministic and Stochastic Approaches. The Deterministic approach is carried out by direct analysis of the results of the technical optimization method using the CMG simulator, while the Stochastic approach uses the simulation results from the Deterministic approach to determine the most influencing parameter in the steam flood process as well as to optimize the infill and injection wells location, number of steam injection wells and the steam injection rate with the highest oil Recovery Factor (RF) and highest Net Present Value (NPV) objective functions in CMOST. In this field development using a Deterministic approach, 2 producer wells were converted into injector wells with a total steam injection rate of 3774 Bbl/D, the injection pressure of 1740 psi, steam quality of 75%, and steam temperature of 300 oC. The cumulative oil production (NP) for this scenario is 15,70 MMSTB, RF is 52,34%, and the NPV is 33.10 MM$/STB. For the Stochastic approach, CMOST optimization using the maximum Recovery Factor (RF) objective function resulted in an Np of 18.40 MMSTB, an RF of 61.33%, and NPV of 43.00 MM$/STB. CMOST optimization with the maximum Net Present Value (NPV) objective function resulted in an Np of 17.19 MMSTB, an RF of 57.29%, and an NPV of 53.86 MM$/STB. The Stochastic approach with maximum Net Present Value (NPV) objective function provided the most favorable scenario to be used in the development of Field “X”. And the optimization using the Stochastic approach also produces faster, optimum, and more accurate results than the Deterministic approach.