A rapid, user-friendly & easily deployable workflow solution for managing steam flood operations & reservoir management is presented that combines day to day surveillance techniques with performance prediction that uses an analytical model for proactive management of operations.

The proposed workflow has been implemented in multiple projects (using public data and data provided by operators) to answer multiple critical questions like pattern response date, steam breakthrough time, expected peak rate from a pattern, arrival of the peak rate, underperforming or over-performing regions in a field, redistribution of the steam volumes, where to minimize steam oil ratio, classify patterns based on efficiency and so on.

It is built up on two core components. A set of diagnostic plots and data analytics that enable quick historical performance assessment of patterns as well as the surveillance of the current state of operations. Secondly, an analytical performance model by Jeff Jones is applied to model the oil production from the patterns (early time, mid-life and late pattern life) that serves as a fast-computational tool for practising engineers. This paper discusses the results from multiple fields on the application of proposed workflow and how it has assisted in field management and optimization. These methods are efficient and fast and more importantly user friendly for reservoir management of steamfloods.