Summary In this consistently low–oil–price environment, where infill drilling and new field developments struggle to meet economic metrics, production optimization continues to be a focus and driver for the industry. Currently, waterflooding contributes significantly to global oil production and is one of the main nonthermal techniques that can be applied to increase pool recovery. Although proper reservoir management of assets under waterflood (WF) is critical to reaching the highest recovery factor (RF) possible, it is difficult to achieve and maintain given the inherently dynamic nature of the production mechanism. Further, to achieve optimal reservoir management while providing the opportunity to leverage alternative enhanced–oil–recovery (EOR) technology, the existing subsurface and surface infrastructure should be fully optimized. Optimizing the subsurface and surface infrastructure in parallel with achieving optimal reservoir management will result in higher capital efficiency while improving key economic metrics such as operating costs (Opcost); reserves–replacement ratio; depreciation, depletion, and amortization; and overall earnings. Given the existing challenges that include reservoir–conformance problems, lack of reservoir energy, excess fluid production, wellbore/pipeline–integrity issues, and infrastructure constraints, how to fully optimize the current infrastructure while achieving optimal reservoir management in parallel is the main question and challenge. Husky Energy's medium–oil–reservoir–management strategy has been highly successful in reinforcing WF as a sustainable long–term recovery method. In this paper we will present a practical workflow to tackle the challenges highlighted by using a systematic reservoir/production–engineering approach with minimum additional capital expenditure (Capex). First, a robust framework was developed to answer three main questions: What is happening?, Why is it happening?, and How can it be improved? Then, a comprehensive dynamic surveillance methodology, consisting of both numerical and analytical techniques and a 10–step workflow for optimizing a WF project, is discussed. This is followed by the results achieved by using this strategy in three WF fields: the Wainwright Sparky, Wildmere Lloydminster, and Marsden–Manitou Sparky pools in the Lloydminster oil block. The positive effect that this reservoir–management process has had on all key financial metrics will be discussed. As an example, since the beginning of the optimization initiative, the Wainwright and Wildmere pool production has increased 21 and 23%, respectively, and the Opcost has decreased by 33 and 42%, respectively. Further, since implementing a similar strategy in 2016 at the Marsden–Manitou WF, its production has increased by 30% and its Opcost has decreased by more than 18%. Finally, we will present a WF–protocol checklist that has been developed as a guideline for engineers who need to optimize pool performance even in a capital–constrained environment.