One of the most critical aspects related to the economics of production from a field is the maximization of oil production. For wells that have high CAPEX and OPEX costs associated with them, such as those containing electrical submersible pumps (ESPs), optimization becomes even more important. The objective of this paper is to describe the simulation workflow used to potentially maximize the total oil production for a field by optimizing the distribution of the available power to the ESP wells.

In the study, the development workflow is based on real cases over a field consisting of 28 producers with different characteristics. However, to implement the study correctly, it was necessary to theoretically reconstruct the area with the aim of highlighting the optimizer. Given that the perforation depth, pressure depletion, and relatively low API gravity, the majority of these wells cannot flow naturally. Because of this, ESPs were installed in 34 of the wells. The daily production rate from the field is currently just above 22,000 B/D. To simulate them, both ESP design software and a steady-state multiphase flow simulator were used.

The ESP design software was used to determine the surface power requirements and to generate the pump performance curves for each ESP. The steady-state multiphase flow simulator was used to build both a well simulation model and create a network design on a field-level basis. After the well designs had been uploaded into the network model, the well production optimizer in the flow simulator was run.

The objective function for the optimization was the maximization of the oil field production, while the control variables were the operating frequency of each ESP, which implies the power distribution between the ESPs. Constraints on the total power available for distribution to all EPS's in the field, the total allowable gas production, and the total allowable water production were also taken into account. The optimizer also had an option to shut-in wells to improve the objective function further while honoring the constraints. Five scenarios are discussed in the present paper, showing that an incremental oil production of up to 27.9% could be obtained depending upon the operational constraints.

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