| | Sept - Oct 20209behind cloud computing existed before the present computing power, communication with the sensors, cost per computation, fault-tolerant computation in real time, and web services provide elastic support and scalability to visualize and take actions in near real time.There are several digital levers that can be used to make the virtiual real-time centers more efficient:1 Real- time data historian through cloud-based services· Off-the- shelf technology· Flexible (logs, reports, unstructured context info)· Scalable nodes, replicas, active DC failover2 DecisionSpace® integration enables:· Multi-domain data integration· Workflow orchestration· Multi-well/job real- time analytics· On-demand simulation3 Plans for engineered, private-cloud solution4 Post job available for big data analyticsSince there are several uncertainties, a downhole hybrid approach is used, i.e., physics-informed or guided data analytics have to be done in the cloud to better describe the process. The problem encountered is the penalty of computational time when these engineering models are coupled. Surrogates and proxies have to be created instead of calling the engineering calculations every time to prescribe and predict what is going to happen for the automated system. Under these conditions, the hybrid model provides better solutions. This creates the information fusion with different levels of uncertainty. This way, paradoxes are suppressed, uncertainties are neutralized, and the engineering principles are not violated. The stream-processing frameworks on the cloud provide the capability to process, analyze, and provide solutions at a much faster rate to office and other control centers. Additionally, the resource elasticity is provided by the use of various transient engineering calculations such as fluid mechanics, solid mechanics, and solvers in the form of ultrafast micro-services. Based on this approach, the proxy engineering models are created, and further, they are used with the information from the data using machine learning. This helps to not only interpolate but also extrapolate as the data are processed. Based on thisapproach, Tthe events are also predicted, and the digital programs are updated with the engineering models and data at rest but in motion. This allows checking the change in the status by running engineering calculations in real time based on the real-time status change. Figure 2 shows the workflow using cloud computing, and it results in an intelligent command center paired with Richer Well Construction 4.0 (With Data & Digital Twin). The new open artchitecture stack also provides the option to plug play by any user. It allows us to consume, integrate, connect, and collect data from different sources and move the UCOC to the cloud while enablingand access and control anywhere and at anytime. Dr.Robello Samuel
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