Feasibility Study and Technical Optimization by Implementing Steam Flooding for the Field Development Plan of A Heavy-Oil Field in Yemen - Mohammed Sheikh Salem Al-Attas; Amega Yasutra (Testing Center for Oil and Gas LEMIGAS, 2021)
Enhanced Oil Recovery (EOR) applications are highly recommended and required in Yemen 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 (uo) 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 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, deterministic and stochastic approaches. The deterministic approach is carried out by direct analysis on the results of the technical optimization method using the CMG reservoir 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 RF and highest NPV. In this field development using deterministic approach, two producer wells are converted into injector wells. The RF for this initial scenario is 52,34%, and the NPV is 33.10 MM/STB. For the second scenario using Stochastic approach, CMOST optimization using the maximum RF objective function resulted in RF of 61.33%, and NPV of 43.00 MMS/STB. Finally for the third scenario using CMOST optimization with the maximum NPV objective function resulted in RF of 57.29%, and an NPV of 53.86 MMS/STB. The Stochastic approach with maximum NPV objective function provides the most favorable scenario to be used in the development of Field