#TITLE_ALTERNATIVE#

• Main Author: HIDAYAT (NIM : 12214023), DANNY
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/26378
• Institution: Institut Teknologi Bandung

This study presents an application of integrated surface network model of X Area in South East Sumatera, Indonesia. This area consists of 3 mature producing fields with 10 active offshore platforms, 1 inactive platform, and 88 active ESP wells. These mature fields are now facing high water cut problem and pressure depletion, which are natural condition while the fields has been producing for more than 20 years. Fluid produced in this area needs to be transported using pipelines into main platform processing unit to be treatened after. With these complex production problems, the surface network modeling is needed to model system performance for field optimization decision. Surface network modeling in this X Area consists of 2 main projects, which are well performance modeling and integrated network modeling. <br /> <br /> The well performance modeling is conducted using nodal analysis. The IPR of each well is built using 3-phase liquid-based Wiggins IPR using production test data due to high water cut. Well model(s) must give operating rate and pressure similar with actual condition with maximum error tolerance of 5%. This calibration needs trial and error of Well L-factor as a pressure drop multiplier for vertical lift correlation. The integrated network was constructed using Piping and Instrument Design (P&ID) map and then validated using actual inlet and outlet pressure record of pressure gauge, by adjusting the pipe L-factor and D-factor as a length and diameter-related multiplier factor with maximum error tolerance of 5%. The network solution shows that there are pipelines which have liquid velocity less than optimum liquid velocity in offshore pipelines. Three cases are developed to increase the liquid velocity, which are decrease wellhead pressure by opening the chokes, changing the ESPs to increase the liquid flowrate, and both of them. All cases result higher liquid velocity (and liquid flowrate), even though some pipelines still can’t meet the requirement. Case 3 is selected as best case since almost all pipelines can meet the liquid velocity requirement and gives highest oil recovery.