Perpustakaan Digital ITB

Government together with the Special Task Force Implementation of Upstream Oil Business Activities and Natural Gas (SKK Migas) continues to strive increasing oil production with targeting national oil production by one million barrels per day (bopd) by 2022 future. When a reservoir field has passed its primary limit. Petroluem engineers do secondary recovery to increase oil production, one of common methods, waterflood, a mechanism that water injected to formation to drive oil towards production well. Once a barrels of water injected to formation, there is no way to know where it will go. Therefore, we need a tracking method, current methods for tracking are expensive, time consuming and required complex data. Hence in order to improve reservoir management decision and optimization in waterflooding, usually it needs reservoir characterization and reservoir performance prediction as a decision-making process to increase reservoir production economically. In this paper is discussed a method that capable to give a rapid evaluation of waterflood performance using historical injection and production data since waterflood applied in a field without complex and time-consuming reservoir simulations called Capacitance Resistance Model (CRM). Firstly, the total production model fit is needed to manipulates injector-producer connectivities and producer time constants to obtain the best possible match between the total production predicted and the total production measured over time for each well. The outputs of this module are the injector-producer connectivities and the producer time constants. This, the inferred geology of the reservoir, can be used to optimize the injection distribution into the future. The oil production model fits each producer’s oil production over time using two empirical constants that are used in the optimizer/solver along with the connectivities and time constants to predict future production (forecasting). Once the best fits are obtained, we do sensitivity analysis to predict the optimum injection rate for each injector for the future economically.