by Santanu Sur, Consulting Partner, Energy & Resources, TCS
From the drilling site to the refinery—O&G operators deploy pushers such as pumps, compressors, and turbines to transport highly inflammable products across thousands of kilometers through uninhabited spaces and ecologically fragile areas. These pushers are enormous pieces of equipment that can consume as much as 10,000 KWH of power. They are largely located in isolated zones and require specialists to operate, maintain, and repair them.
An unplanned or accidental breakdown can have a catastrophic long term impact on the surrounding environment. Monitoring and keeping pipeline assets under surveillance is however a routine but equally daunting and critical task for any enterprise. Recently, RECOPE lost over USD 2 million in product theft in one month alone. And earlier this year, a third-party excavator caused a pipeline leak that spilled over 45000 gallons of diesel fuel – leading to serious environmental problems for Worth County and massive legal penalties for Magellan Midstream Partners.
In the near future, OEMs will need to introduce services such as compressing or pumping, filtering or fractionating, instead of just selling their equipment. These services could either be billed based on the volume or quantity of product they pump, refine, distill or fractionate, or based on running hours with pre-defined clauses, such as minimum quantity per month, guaranteeing optimized uptime. Long term service contracts can include both penalty and reward clauses. More importantly, such a service model can help respond to and remediate pipeline leaks and similar incidents, ensuring a proactive approach towards risk mitigation.
Transitioning from a CAPEX-intensive to an OPEX-efficient Cloud-based Operating Model
Traditional monitoring methods generally rely on visual inspections of the pipeline corridor or aerial reconnaissance – neither of which can provide real-time field intelligence about the health of an asset. With the Internet of Things (IoT) however, the process of collecting and sending data from across asset networks has become a feasible, if not necessary, option. When enough information is gathered from intelligent devices and systems embedded at various locations, it is pushed to a central cloud platform which provides operational insights by analyzing it using an underlying AI engine.
The cloud itself offers immense scope for managing large scale datasets. Such a platform with embedded algorithms can forecast equipment failure and even schedule downtime automatically. With an in-built iterative software, it can enable machines to take corrective action on their own – learning from historic instances and adverse incidents to adjust operating parameters for ensuring optimal performance. This will help automate a subset of machine and network-level operational functions, relieving human operators to focus on core activities.
Harnessing Core Digital Capabilities
With the advent of edge computing, cloud and AI, O&G operators can collect data from real-time sources, historic records, and embedded systems before pushing it to the cloud. Third party system integrators can facilitate collection, storage, distribution as well as provide analytics services for making sense of raw or tabulated tags and transactional structured or unstructured data from millions of sensors at remote locations. The processed data can be used for both operating and maintaining assets. This as well as reports, analytical insights can be easily accessed through a secured platform by stakeholders across the value chain.
Satellite and drone-based sensors coupled with optical fiber-based light scattering modulation techniques and ultrasound sensor-based sonic scanning are redefining the process of safeguarding pushers against third party damages. These can provide insights from images that accurately capture color, distance, size and shapes and locations of encroachments, excavation, constructions, and so on. It can monitor anomalies over a period of time and extended areas with prescriptive preventive measures. These technologies provide the necessary flexibility for storing, retrieving, analyzing, and interpreting field data anytime, anywhere. Moreover, since maintenance engineers can monitor these assets remotely, it improves safety by minimizing exposure to hazardous material while creating an audit trail for ensuring compliance with regulatory requirements. The data and analytics can be integrated with other enterprise applications for quicker effective response.
Services such as these can facilitate data distribution to equipment manufacturers or third party agencies such as regulatory bodies. Leading OEMs such as GE, Ingersoll Rand, Rolls Royce are already contemplating offering these services instead of selling compressors to pipeline operators. However the underlining criteria is that they should get access to trillions of datasets from sensors embedded in their machines in real time.
Will such service models help O&G companies as well as O&M teams create a truly holistic, digitally transformed asset network? Let us know in the comments section below.