Integrating Gas Lift Well Optimization from Well Model to Field-Scale Network To Assess Additional Compressor Impact
Abstract
Discovered in 1974, Handil field had reached its production peak in 1977 at 194,000 Bopd before it continued to decline. Water injection began in 1978 in order to maintain reservoir pressure. Later, gas lift facility to provide artificial lift was installed in 1981. Field water cut is currently close to 90% with production level of 16,000 Bopd and 30 MMscfd of gas. The produced gas is used for commercial export, to run compressor in production facilities, fuel consumption, and flare. Oil production is mainly supported by gas lift compressor running at nearly maximum capacity. Therefore, prioritization strategy of gas lift rate (Qgl) injected into producer becomes crucial. Well by well evaluation practice to implement the strategy is time-consuming with limited operational flexibility to implement due to numerous active wells (more than 110 active wells). This paper provides an approach of integrated
optimization to improve the prioritization strategy and to assess additional gas lift rate impact beyond current gas lift compressor capacity.
An approach to link sub-surface to surface interaction that involves numerous well productivity models and production facility has been developed to construct simulation model in PETEX platform. Validated model can be useful to verify these points: (1) Optimized ∆P choke; (2) Optimized Qgl; and (3) Combination of optimized ∆P choke and Qgl.
From optimized Qgl verification, allocation strategy is evaluated. It shows that Qgl optimization provides significant incremental gain. The optimized Qgl scenario is developed further into sensitivity case to predict the impact of Qgl beyond current maximum capacity (in case of additional compressor). The sensitivity case justified gain estimation on reactivating additional gas lift compressor, from which incremental gain of several hundred barrels of oil per day is observed by production test. As a conclusion, the integrated model is proven useful and efficient for production optimization purpose.
