RobelloSamuel ,Chief Technical Advisor and Halliburton Fellow (WellEngg.), Halliburton
The digital transformation is providing impetus in the advancements in the oil and gas industry. Figure1 shows technological advancements through time. The bifurcation points provide the fusion of new technologies during the industry contraction mode, which translates the environment similar to the industrial revolution. As the industry moves toward automated drilling systems, not only comprehensive 3600 engineering optimization has become very critical, but also the fusion of data analytics at the edge into the system has become increasingly essential. Even though it may sound like a futurist’s pipe dream, the exponential technologies in other industries will provide impetus in accelerating the realization of such a system. With so many technologies advancing at the same time around us, it is up to us to create the layered evolution of an advisory system to rig controls and position ourselves for the cyber remote operation centers. We have to rethink the status quo and provide new options for real-time monitoring space due to increased pressure to reduce operating costs. With enhanced cloud solutions and digital framework with sensor fusion, physical location- based remote center models with multiple screens and video walls are getting outdated to make complex decisions. Fast underpinning engineering analysis and optimization techniques with an enhanced layer of AI and AEI can be run to take instantaneous decisions at the edge leading to depth to depth and slip to slip user experience. We need more of a virtual and modular Unified Command and Operation Cyber Center (UCOC) in the third dimension for end- to- end visibility with interconnected disciplines through a single glass pane window— – an integrated but dynamic and distributed control shared across the enterprise and accessed by anyone at anytime, anywhere.
The other technologies that are handholding are cyber-physical systems, real-time embedded systems, deep Neural Networks and Reinforcement learning, distributed public ledger (blockchain technologies), IOT, IIOT, sensors, cloud computing, digital twins, edge computing and cloud communication, timed models and stream analytics, and hybrid systems – AI/ML/Physics.
Cyber-physical systems (CPSs) integrate cyber capabilities (computation, communication, and control) with physical capabilities (systems governed by the laws of physics and operating in continuous time and other physical processes). Both are tightly coupled and engineered to enhance performance at all disciplines of petroleum engineering. Even though the technologies
behind 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 failover
2 DecisionSpace® integration enables:
• Multi-domain data integration
• Workflow orchestration
• Multi-well/job real- time analytics
• On-demand simulation
3 Plans for engineered, private-cloud solution
4 Post job available for big data analytics
Since 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. Underthese 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.
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