Quantifying Polymer Injectivity and Performance in the Milne Point Oil Field

Abstract

Abstract Polymer floods often collect a large amount of injectivity data that is often overlooked or minimally explored for additional value. This paper uses a plethora of existing field data for numerous polymer injectors to improve injectivity prediction, potentially identify problem wells, and perform polymer QA/QC using existing field wellhead pressure, bottom hole pressure, and rate data. Existing injectivity models (Aitkulov, et al. 2021) (Jackson, et al. 2019) (Poulsen, et al. 2018) are used to predict performance and determine difference between prediction and actual injectivity. Step-rate tests (SRT) or cases with multiple rates are also used to quantify well performance, constrain, and quantify rheology parameters in the reservoir, and look for bottom-hole pressures approaching the minimum horizontal stress. Polymer flow in tubing is used to determine friction reduction capabilities and is used to double check that polymer rheology is on specification via calibration with known viscosity using Moody diagrams (Moody 1944). Many wells were found to be below ideal injectivity on both water and polymer, however most of them were easily explained by pattern orientation, e.g., injection well with only one offset producer. The concept of friction factor (fDW) plots vs. Reynolds numbers (Re) are demonstrated for the purpose of performing QA/QC checks on polymer being injected where applicable.