Successfully implementing polymer flooding and maximizing benefits requires selecting best options of variables such as polymer concentration and slug, and number and location of new wells. Option-decisions combined generate thousands of scenarios. Therefore, even using smart algorithm optimizers to efficiently find the maximum of a business objective mathematical function can be a very time-consuming process.

The objective of this article is to demonstrate a methodology to improve the chances of finding the maximum net present value (NPV) solution for planning an offshore polymer-flooding; this includes finding, for example, the minimum injection volume to more easily offshore operations.

The reservoir and economy models included here were automatically coupled with software that encloses a smart numerical algorithm for searching complex maximum/minimum functions. The options of the previously mentioned decision variables were selected to maximize the NPV of the inverted five-spot polymer-flooding project under constrained rig availability. The process was conducted in three stages:

Stage 1: potential value estimation

Stage 2: narrowing options through deterministic numerical simulation

Stage 3: A) numerical optimization of all decision variable options except the drilling sequence; B) numerical optimization of the drilling sequence


A total of 379 scenarios were numerically forecasted in just a few months. The best scenario showed three times the NPV of the nonflooding case. Compared to the reference water-flooding scenario (i.e., all the same options but with the fluid injected), the NPV was 1.3 times greater, the water-oil ratio (WOR) was 0.45 times lower, and Np was 1.25 times greater. Unobvious scenarios, such as reducing the yearly drilling rig availability but extending drilling by four years, were revealed. A comparison of the working time for Stage 2 with Stages 3A and 3B showed that the numerical optimization is six times faster per scenario generated.

This study demonstrates that the use of numerical algorithms of polymer flooding yields a significant incremental value over traditional deterministic simulations in a much shorter time frame and with fewer costs compared to previous steps related to building a reservoir model. It is expected to be applicable to all types of enhanced oil recovery (EOR) processes.

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