White Paper: A Machine Learning Approach to Automate Gas Lift Optimization
Venkat Putcha, PhD, Nhan C. Le and Mike Pennell
This paper presents a methodology for providing automated set-point recommendations to optimize gas lift well operation, by establishing a live synergy between physics-based simulation and real-time field data through the employment of machine learning models. The machine learning models serve two distinct purposes in this approach: 1. Accelerate simulation learning to enable real-time solutions 2. Probabilistic estimation of likely downhole and reservoir operating conditions of a well, with live updating of the probability based on the response to set-point changes, thus improving accuracy with each transition.
Enter your information below to receive an
email link with access to this White Paper!
Copyright © 2019 OspreyData Inc. All rights reserved.