Landmark Graphics Corporation

University of Houston System

Halliburton

Frontender Corporation

Cesar Bravo

Andrey V Filippov

Luigi Saputelli

Michael Nikolaou

Supriya Gupta

Sergio Henrique Guerra De Sousa

A self-adapting digital twin of a wellbore environment can be created. The self-adapting digital twin incorporates a standalone Ensemble Kalman Filter (EnKF) module with a constant parameter digital twin developed for a fixed environment. The standalone EnKF module receives streaming measurement data from multiple sensors and prediction data from the digital twin and executes the standalone EnKF module using the streaming measurement data and the prediction data from the digital twin. The results of executing the standalone EnKF module are input parameter corrections for the digital twin that are communicated to the digital twin. Output predictions of the digital twin are used to modify operational parameters of an oil or gas recovery process.

Constructing digital twins for oil and gas recovery using Ensemble Kalman Filter

The electrical submersible pump (ESP) is currently the fastest growing artificial-lift pumping technology. Deployed across 15 to 20 percent of oil-wells worldwide, ESPs are an efficient and reliable option at high production volumes and greater depths. However, ESP performance is often observed to decline gradually and reach the point of service interruption due to factors like high gas volumes, high temperature, and corrosion. The financial impact of ESP failure is substantial, from both lost production and replacement costs. Therefore, ESP performance in extensively monitored, and numerous workflows exist to suggest actions in case of break-downs. However, such workflows are reactive in nature, i.e., action is taken after tripping or failure. Therefore, a data-driven analytical framework is proposed to advance towards a proactive approach to ESP health monitoring based on predictive analytics to detect impending problems, diagnose their cause, and prescribe preventive action.

System and method for detecting, diagnosing, and correcting trips or failures of electrical submersible pumps

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Richmond, TX, United States of America

Cesar Bravo