White Paper: Data Quality Fuels the Artificial Intelligence Race

White Paper: Data Quality Fuels the Artificial Intelligence Race

Authors:
Ron Frohock, Kenneth Collins

Abstract:
This paper reviews different forms and sources of data, dimensions for evaluating the quality of data, and examples of how data quality impacts the success of an Artificial Intelligence project. The emphasis and examples we utilize are focused on how this impacts an organization’s efforts in deploying Artificial Lift production and optimization solutions.

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White Paper: A Machine Learning Approach to Automate Gas Lift Optimization

White Paper: A Machine Learning Approach to Automate Gas Lift Optimization

Authors:
Venkat Putcha, PhD, Nhan C. Le and Mike Pennell

Abstract:
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. 

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By submitting this form, you are consenting to receive marketing emails from: OspreyData Inc, 32234 Paseo Adelanto, Suite A, San Juan Capistrano, CA, 92675, https://www.ospreydata.com. You can revoke your consent to receive emails at any time by using the SafeUnsubscribe® link, found at the bottom of every email. Emails are serviced by Constant Contact

Copyright © 2019 OspreyData Inc. All rights reserved.