#TITLE_ALTERNATIVE#

• Main Author: CHANDRA (NIM: 22216302), STEVEN
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/31100
• Institution: Institut Teknologi Bandung

As major Indonesian gas fields are nearing their mature life cycle, the presence of gas condensate and or water could be a troublesome problem since low reservoir pressure is not sufficient to produce the liquid phase to the surface making liquid loading phenomenon will happen in no time. Liquid loaded wells tend to produce below its supposed economic value, or at worst cases, shutting the wells at once. <br /> <br /> In field X, retrofit gas lift is deemed as a viable solution in order to overcome liquid loading on several of its gas condensate field. It is defined as an act of injecting gas in valves below the perforated zone in order to lift lighter multiphase fluid. However, it is not easy to properly model integrated field development optimization due to its highly uncertain field data. The analytical approach employed by previous publishers is only valid for deterministic datasets or synthetic field data. In contrast, complexities in field operation implied that optimization cannot be performed accurately if datasets supplied are obtained from a set of measurements where errors can possibly occur, making it risky to perform analytical calculations. This research considers an optimization problem that is based on gas allocation for retrofit gas lift application in separated offshore platforms where the given constraint is compressor capacity and gas injection quota. <br /> <br /> This publication employs state of the art genetic algorithm construction to address uncertainties in gas optimization allocation based on two available scenarios offered by the contractors and the results are analyzed in terms of simple economic parameters to determine the effectiveness of the aforementioned genetic algorithm in handling uncertainties in integrated field optimization. <br />