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Performance Monitoring of an Offshore Gas Compressor

Multivariate statistical process control (MSPC) methods can be used to monitor offshore equipment onshore. Models of a compressor’s operation can be created using the MSPC techniques of Partial Least Squares (PLS) and Principal Component Analysis (PCA) to prevent downtime from occurring or, at the very least, keep it as minimal as possible. The models use historical data and can help to predict compressor problems before they become critical and allow essential maintenance to take place before downtime becomes unavoidable. The models can also be used to detect when a component in the compressor process has changed.

As published in:

Matrikon in Energize Energize
August 2007

The independent power and energy journal of Southern Africa







Matrikon in Upstream TechnologyUpstream Technology
February 2007

Upstream Technology is the first publication to explore the impact of information technology (IT) on the upstream sector of the energy industry. Readers will learn about the impact of mergers on major oil companies’ IT departments, gain insight into how e-business technology is expanding for E&P applications, how technologies are improving operations, financial performance, and ultimately shareholder value, and much more. As the energy industry and the Internet become more intertwined, Upstream Technology will continue to provide objective, comprehensive information about the upstream sector’s IT developments as a whole.

Matrikon in Oil Information Technology Journal OilIT.com
March 2007

Oil IT Journal’s coverage spans upstream geology and geophysics through drilling, production and distribution to plant data management, finance and e-business. Oil IT Journal has a track record of providing clear and impartial analysis of the technical and commercial issues important to oil and gas CIOs, decision makers and end users.


Get the full Technical Paper Now!

Details:
Technical Paper
(353 KB , PDF)
Author: Lauren Neal, MEng. Matrikon

Description:
In a world where success and profit go hand-in-hand, oil and gas companies are pressured to meet production targets on a daily basis. Oil and gas production generates money and any downtime caused by equipment failure has the possibility of crippling a business. Any downtime is an issue in this industry but if underlying causes could be predicted and prevented before a system reached an unrecoverable stage, companies could save millions that would otherwise be lost revenue.






           

 
 

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