The New Edge. Building and Deploying a New State of the Art, High Speed Acquisition, Automation and Analytics Platform for Drilling, Completions, Production, and Renewable Energy Applications

2021 ◽  
Author(s):  
Anthony Paul Pink ◽  
Carl Fehres ◽  
Julie Diane Pearce ◽  
Stacy Costa ◽  
Mickey Noworyta

Abstract This paper discusses the architecture, development, and deployment of a new state-of-the-art data acquisition and analytics platform. The system is designed to capture and store data for all phases of well construction and is also suited to aggregating data from renewable energy sources such as offshore wind turbines. In today's well construction world it is vitally important that an edge platform can capture high-quality, high-speed data. It needs to be able to universally translate data from many protocols and provide outbound data streams that are easy to consume and store. The high-quality data streams can then be queried by high-value analytics that ultimately deliver predictive and prescriptive solutions. Our approach was to identify the market pain and develop a system that solved the digital requirements for our customers who needed a field-deployed and field-supported, agnostic digital ecosystem. In the new "Digital Oilfield" the requirements for data capture, aggregation, edge computing, automation, cloud infrastructure and office applications are all expanding rapidly. Most "Edge" solutions are cloud-based and come from purely digital companies who have little or no domain knowledge or field infrastructure with which to deploy and maintain those systems. It was observed that an "Edge" solution was required that remained highly performant even if network connectivity from the cloud to the location was lost. This paper will also discuss the novel approach to the development of this platform with an oil & gas operator's subject matter experts being embedded in the contractor's product development team. The result being an end-to-end solution designed for both the requirements of the field and the office. The customer had previously built its own system internally, but was looking for a partner who could update and maintain an evergreen technology stack, increase speed and capability and be able to maintain and support a scalable product worldwide on all its operational locations. We will explain the development process, early field testing and commercialization of this product and the results that were achieved. This new system will have an open architecture that allows other digital companies to leverage the high-speed data and host their applications on the platform both on the wellsite and in the office. The system also provides interoperability with the machines on location, this interoperability enables a wide range of 3rd parties to be able to deliver automated applications on the well location. This technology will enable significant performance improvements in drilling and completion operations.

Author(s):  
Peter M. Pachlhofer ◽  
Joseph W. Panek ◽  
Dennis J. Dicki ◽  
Barry R. Piendl ◽  
Paul J. Lizanich ◽  
...  

The Propulsion Systems Laboratory at the National Aeronautics and Space Administration (NASA) Glenn Research Center is one of the premier U.S. facilities for research on advanced aeropropulsion systems. The facility can simulate a wide range of altitude and Mach number conditions while supplying the aeropropulsion system with all the support services necessary to operate at those conditions. Test data are recorded on a combination of steady-state and high-speed data-acquisition systems. Recently a number of upgrades were made to the facility to meet demanding new requirements for the latest aeropropulsion concepts and to improve operational efficiency. Improvements were made to data-acquisition systems, facility and engine-control systems, test-condition simulation systems, video capture and display capabilities, and personnel training procedures. This paper discusses the facility’s capabilities, recent upgrades, and planned future improvements.


Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 741-750 ◽  
Author(s):  
José Luis Roca ◽  
German Rodríguez-Bermúdez ◽  
Manuel Fernández-Martínez

AbstractAlong this paper, we shall update the state-of-the-art concerning the application of fractal-based techniques to test for fractal patterns in physiological time series. As such, the first half of the present work deals with some selected approaches to deal with the calculation of the self-similarity exponent of time series. They include broadly-used procedures as well as recent advances improving their accuracy and performance for a wide range of self-similar processes. The second part of this paper consists of a detailed review of high-quality studies carried out in the context of electroencephalogram signals. Both medical and non-medical applications have been deeply reviewed. This work is especially recommended to all those researchers especially interested in fractal pattern recognition for physiological time series.


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