Design and Implementation of a Digital Twin for Live Petroleum Production Optimization
Fig . 1 : Schematic of the closed-loop process providing an overview of the Digital Twin .
THE CURRENT STATE
Before going further into the details of the Digital Twin implementation , it is necessary to understand the scope and potential impact of this paper . In this section , it is attempted to set a baseline by describing the typical current state of operation in the Oil and Gas Industry .
The above described process in Figure 1 is already implemented widely in the oil and gas industry , albeit , every step in the process is performed manually by subject matter experts , and on a well by well basis . The manual process is time-intensive , it takes several hours to implement it on one well at a given point of time for data collection , processing , simulation , inverse modeling and generating a set-point recommendation using a history matched model . Petroleum wells are dynamic entities that change their underlying operating conditions over time .
Further , wells are subjected to discontinuities in behavior due to design changes , workovers , restimulation and impact from nearby operations such as hydraulic fracture hits . Set-point reviews or changes are required as the well behavior changes . If diligently performed , the time investment required to optimize set-points is approximately 7-10 days per well per year . Due to the significant time investment , typically , the simulation based set-point optimization is
- 38 - March 2021