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The Early Warning Project: Prewarning and avoiding problems and costly down time in complex industrial processes

The goal and focus of the Early Warning Project has been to find early indicators of potential trouble or suboptimal performance of a complex industrial process. If such indicators are found, there may still be time to perform the appropriate actions in order to stabilise the process and avoid the problem. An alert service should pick up on a signal of upcoming trouble as early as possible, and maintain an “alert degree” which varies according to new evidence coming in. Such functionality will be more potent ‐ and complex ‐ than fixed value-based alert generation that are in abundance today. One test case will be presented, namely the performance of the low-pressure separator on ConocoPhillips’ Ekofisk 2/4 J (EKOJ) platform in the North Sea. This is a highly complex process and there are a lot of influences that are not fully understood. The EKOJ receives streams also from other platforms, meaning that performance issues on these, “up-stream” flows may influence the performance on EKOJ or, more specifically, the separator that we focus on. A method has been designed that, given a set of sensory data (time series showing temperatures, pressures, flows etc.) around the industrial process (on EKOJ itself as well as upstream to EKOJ), extracts knowledge in the form of sets of simple rules. Such rules are intuitively understandable to the experts, but may also be used for real-time monitoring of the working system. Each rule provides diagnostic capability but may also be combined with others to yield combined evidence and an overall probability of imminent problem or failure. Rules may also be used to directly diagnose the situation at hand.