According to ARC Advisory Group, companies could lose up to 5% of production due to unplanned downtime. The average impact of unscheduled downtime has caused process companies to lose more than $20 billion in production annually.
As production assets in the oil fields -whether offshore or onshore- are always exposed to harsh environments, maintaining equipment to keep up with production is often challenging. Furthermore, maintaining uptime of these assets can get harder over time due to changes in loading profiles when oil and gas production rates decline.
Oil and gas companies have been generating huge amounts of operational data for several decades, long before the term IIoT was coined. However, the recent improvement in cloud technology, analytics and computing power has enabled the transformation of data into insights that can provide meaningful decision support to both the operational teams and processes, helping enterprises to gain the next level of operational efficiencies.
Due to the clarity on the use cases and proven high ROI, predictive analytics has been getting a lot of attention in the oil and gas industry. Predictive Analytics crunches past performance data of an asset using algorithms and creates a digital replica of the operating model to predict its performance behaviours.
Oil majors have already been reaping significant benefits using predictive Analytics to catch failures before they happen. This technology has transformed their maintenance strategies from reactive to proactive, effectively reducing unplanned downtime and improved asset utilization.
Source: World Oil