As the crude price still struggles to maintain a profitable balance, we see the industry trying to explore opportunities to become efficient, and ultimately change its course of executing business. The question that has everyone interested in is, “How can one increase the productivity and hence, a profitable revenue?” One of the key factors in this scenario is to focus on the most ignored problem in the past – unplanned downtime.
One such powerful tool insight seems to be “Digitization”, which can help achieve the changing demands. It has been estimated that over 65% of the oil and gas industry may expect great impacts from this digital interruption. The importance of Analytics and Internet of Things (IoT) will likely to increase in next few years. However, a very small expanse of the industry seems to be prepared for it.
Uncertainty in the oil prices tends to make every production moment crucial, and well downtime riskier than ever. Downtime is typically categorized as Planned and Unplanned. Planned downtime deals with scheduled maintained and workover activities, however the unplanned ones are the pain areas. Unplanned downtime usually is a result of equipment failure, downhole problem, etc. To avoid unplanned downtime, the aim here should be to be Proactive than to be Reactive.
During an unplanned downtime in a well, the equipment and a crew awaits draining money to replace a critical component, or to rectify an unplanned event. Studies suggest that with availability of more advanced digital, predictive technique for maintenance will help in reducing unplanned downtime, and the system will be ready for equipment failure or other cases as such, and will result in better operational efficiency.
Less than 25% of operators label their maintenance practice, as a predictive one based on data and analytics; remaining either take a reactive or time-based approach. It has also been observed that operators using predictive approach have experience 30-35% less unplanned downtime than others, resulting in a profitable outcome.
Predictive analytics leverage various systems to examine through large amount of data to identify and understand behaviors and trends to foresee the future. This includes variety of techniques ranging from statistic, modelling and data mining, which analyzes the current and historic information, and help in identifying problematic cases for the future. This preventive measure can be used to reduce the frequency of the unplanned downtime events.
Unplanned Downtime: Impact & Digital Solution
As noted by Frost and Sullivan (Oil & gas market research and consulting firm), in a world of low oil prices, organization should shift from chasing barrels to chasing efficiency. Hence, reducing downtime plays a key role in enhancing the operational efficiency. With the industry measuring the cost of unplanned downtime, the Identifying more predictive measures for maintained practices mostly driven by data and digitization, can enable the production facilities to reduce their unplanned downtime. This includes efficient and effective collection, management and visualization of data related to equipment performance and current condition. In addition to this, utilizing existing industry knowledge and applying advances analytics can help develop predictive techniques. Also, with the availability of humongous data, comes the responsibility to make use of that data in most effective way.
Some of the key points include:
- The ability to identify data-based patterns
- Cognitive learning capabilities
- Opportunities to leverage data in the Cloud for cross organization/industry comparison
- The ability to share data with trusted service providers for additional analysis and insights
Implementing the advanced techniques will enable the capability to transform information, which drives efficient approach towards decision making. Improvement in operational efficiencies will result in better revenue generation, and help in optimizing assets.
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