A new and fast waterflooding optimization workflow based on INSIM-derived injection efficiency with a field application

Traditionally, production optimization is performed based on repeatedly running a full-scale reservoir simulation model, which is quite time-consuming. Recently, we developed a computationally efficient data-driven model, which is referred to as interwell-numerical-simulation model (INSIM), for history matching, characterizing interwell connectivity, monitoring, and optimization for a waterflood. In this research, we develop a new workflow for fast optimization of waterflooding performance which only requires one single INSIM forward run. Specifically, the optimized well injection rate and production rate are determined with the help of the new INSIM-derived injection efficiency and the existing injector-centered allocation factor. The basic idea of the proposed optimization workflow is to recover more oil by injecting more water to those injector-producer pairs that have more remaining oil left; whereas decrease water injection for those connections without much oil left. The major criterion to tune the injection rate is based on the injection efficiency calculated with INSIM, a value to measure the effectiveness of injected water from an injector. The larger the injection efficiency is, the more oil can be produced by injecting a unit amount of water. The advantage of this method is that the well controls are optimized based on the reservoir-engineering point of view which is easy to understand and visualize. Also, the new workflow is very easy to implement and is much more computationally efficient than the traditional optimization workflow. We test the proposed workflow with two examples including a large-scale field example. The computational results indicate that, by using the proposed workflow, the field oil production is increased with less producing water.