Middle East Steamflood Field Optimization Demonstration Project

Abstract

Occidental Mukhaizna completed a steamflood field optimization demonstration project involving about 100 Mukhaizna wells from Mid-December 2018 to Mid-March 2019. The field demonstration involves a data analytics process that provides recommendations on the best steam injection allocation among wells in order to improve overall steamflood performance. The process uses a low fidelity physics-based proxy model and cloud-based parallel processing. A field optimization engineer history matches and anchors a proxy model to current well and field operating constraints. The engineer completes hundreds of forward runs as part of an optimization algorithm to identify scenarios most likely to help increase value (oil production per steam injected) over the short term in the field, while honoring all producing and injection well operating ranges. The reservoir management team vets the rate change ideas generated and provides their recommendations for changes so the likely best and most practical overall scenario is implemented. The process is refreshed monthly so field performance results are included immediately, and the optimization process is kept evergreen. The field results so far have been encouraging, yielding an increase in oil production that has exceeded expectations. This paper will describe the data analytics field optimization process and workflow, present the baseline performance versus field demonstration results, and share lessons learned.