Design and Implementation of a Digital Twin for Live Petroleum Production Optimization
employed semi-annually or annually per well , or when there has been a redesign or a workover . The details of the typical procedure are represented in the Manual Optimization section of Figure 2 .
The automated version of the manual optimization results in dynamic optimization . Such a system can go through the entire process from data collection through to set-point recommendation for all wells on a continuous basis . Changes in well operating states are programmed to be detected , and the underlying models that are used to generate the set-point recommendations get updated with changing well conditions .
The term “ automation ” in this paper refers to the implementation of a system designed to minimize human intervention by identifying , templatizing , storing , scheduling and executing repeatable processes . As described above , it is feasible to generate manual set-point recommendations , however , to manually update and generate simulations every time there is a change in the system for a field consisting a few hundred wells becomes intractable . As a result , thumb-rules or intuition based set-point optimization takes the forefront position when compared to physics-based-modeling .
The scope and intent of this paper is to describe a system capable of automating massive scale simulation and the associated data processing using a cloud based distributed system . Such a system stores , transfers and processes data , and subsequently queues , executes and stores the results from thousands of simulations relevant to several hundreds of wells on an ongoing basis .
The expected impact of the paper is to provide motivation to set up pipelines for automating components or entirety of the data processing , simulation , inverse modeling and set-point recommendation workflow in the Oil and Gas industry and other analogous spaces capable of utilizing an IIOT network for developing a digital twin as defined in the introduction section of this paper .
IIC Journal of Innovation - 39 -