Managing hidden system threats for higher production regularity using intelligent technological solutions: a case study

Jawad Raza and Jayantha Prasanna Liyanage

European Journal of Industrial Engineering, 2010, vol. 4, issue 2, 249-263

Abstract: The identification and interpretation of hidden system threats on complex Oil and Gas (O&G) production platforms has always been a challenge. These threats may gradually develop into failures/faults resulting in system shutdowns or, eventually, loss/reduction of production. The O&G industry is willing to test new technologies in managing uninterrupted, higher production regularity. In response to these challenges, a research project was initiated involving a leading oil company in Norway. A systematic investigative approach was adopted which incorporates domain experts' opinion and multiple information resources/databases. The paper attempts neural network modelling of a critical production loss-related scenario based on real plant data from an offshore production facility. Analytical results captured symptoms of suboptimal performance from compressors installed in the gas compression system. This methodology could give plant operators an opportunity to identify system's anomalies early. As a result, unwanted shutdowns can be avoided, consequently improving the overall plant's efficiency and productivity. [Received 30 October 2008; Revised 26 January 2009; Revised 21 May 2009; Accepted 13 June 2009]

Keywords: artificial neural networks; ANNs; compressor performance; production regularity; hidden system threats; complex oil and gas industry; production platforms; Norway; offshore production facilities; gas compression; production loss. (search for similar items in EconPapers)
Date: 2010
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