Overproduction of water is an inevitable risk in most mature oil fields. Operators have a high expenditure in both opex and capex to delay the influx of water production, which is reducing both field life and economic value. With the advent of reservoir control technologies, oil production wells are now fitted with downhole pressure and temperature gauges and downhole flow control valves (FCV). These intelligent wells provide valuable data for reservoir surveillance, and operators can control drawdown pressure to reduce water influx from high water production reservoirs.

However, further analysis is required to identify zonal productivity index (PI) and water cut (WC) of each reservoir layer, before engineers can decide and manipulate the FCV flow area configuration of each reservoir flowing in a commingled setting. The current process of allocation using production logging is less efficient while layer-by- layer testing will cause deferments to a well's production. In offshore fields, the delay to production in order to make way for data acquisition is undesirable due to logistical difficulties.

This project aims to build an optimizer to allocate reservoir parameters; PI and WC in commingled intelligent wells; and determine the most optimal setting for the FCV flow areas which will maximize oil production. This is built using data from downhole gauges, well modelling software and a multisoftware platform simulator (MSPS). The inbuilt algorithm in MSPS will allocate PI and WC to match simulated data calculated by a well model, to actual data from the field instruments with the lowest error possible. Once the PI and WC of each layer are known, FCV flow area settings can be configured to yield the optimal oil production.

From the pilot on one well, the optimizer successfully helped engineers to increase oil production from 300 to 430 bbl/d in two months, while maintaining a steady yet maintainable WC increase of 11%, without any intervention costs or deferment. The allocated reservoir PI and WC allow engineers to strategize reservoir management plans specific to each producing reservoir layers, thus, improving the mechanism for reservoir surveillance.