An injection optimization decision-making tool using streamline based fuzzy logic workflow

Abstract

AbstractThis paper presents an adaptive approach to optimize field injection strategies using streamline-based well allocations coupled with fuzzy logic. The strength of our approach comes from the fact that streamlines are generated by running a full-physics reservoir simulator. Streamlines provide great insights about well pattern connectivity and good allocation factors allowing the injection efficiency (IE) for each pattern to be determined. Fuzzy logic can simulate human thinking and handle different categories of information including linguistic, imprecise, approximate, and overlapping to name a few. This paper presents a genuine approach for field injection optimization using a streamlined-based fuzzy logic system. In this work, we present an adaptive streamline-based fuzzy logic system that uses three input parameters namely injection efficiency (IE), water cut (WC), and injection loss to aquifer to assign an injector ranking index (IRI) according to injector performances. The workflow then smartly redistributes water injection by accounting for operational constraints and number of connected producers in a pattern in addition to the IRI. The workflow examines the low performers (i.e., low and medium IRI categories) and assigns different injection reduction factors for each injector in these categories. Then, the total amount of reduced injection is assigned to high performers (i.e., high IRI) while ensuring no operational constraint is violated, such as bottom-hole pressure (BHP) and capacity of pumps. This approach has been tested on a dual-porosity dual-permeability (DPDP) conceptual simulation model. The area of interest has two rows of injectors: downdip and updip. The updip injectors are the focus of the study. The results of applying this approach show noticeable improvements in injection efficiency for most wells in the area of interest ensuring better sweep, good pressure support, and improving cumulative oil production. We believe combining both technologies, namely streamlines and fuzzy logic, can provide reservoir engineers with a robust decision-making tool to attain a more successful field-wide water injection strategy.