IoT-Enabled Pumps Could Rejuvenate The Oil & Gas Sector
Oil and gas is somewhat different from other industrial sectors – there are extremely hostile operating conditions, and most equipment has been in the field for decades. Forbes reports how IoT can balance the scales of digitization and enhance processes in O&G while helping the planet at the same time
The oil and gas (O&G) sector still has a long way to go to become as connected as other industrial sectors, despite having some of the tightest operating margins around. Part of the problem with implementing IoT devices in O&G is the fact that extremely hostile operating conditions make access to these sites difficult and expensive, and the majority of the equipment being used has been hard-wired for years or decades.
Pumps, one of the most vital components of any O&G application, are one of these hard-wired pieces of equipment that, crucially, use up 10% of all the world’s electricity across all their numerous applications. Bringing IoT to O&G may not only revolutionize the sector and bring huge cost savings, it might also help to mitigate some of the more harmful effects of climate change that inefficient pumps and other machinery perpetuate.
Fuelled by fossils
The oil and gas sector is certainly due for a digital overhaul. As a Deloitte report from December 2018 points out: ‘the production segment [of O&G] is still grappling with sensorizing its decade-old wells or making sense of the stored production data,’ detailing the sector’s struggle to harness the disruptive potential of new technologies. Apart from the shocking wastage of inefficient pumps (up to 90% are inefficient), legacy equipment is rife in the O&G sector. This is mostly due to extreme operating conditions that mean drills, compressors and pumps must withstand severe abrasion for decades at a time with significant cost to be removed from the field. As it is difficult to replace or access this equipment, the industry relies on machine condition monitoring (MCM) systems and programmable logic controllers (PLCs) that are often literally hard-wired into these apparatuses, and could be as old as the machines themselves.
However, there is not a lack of instrumentation (like the MCMs and PLCs) to measure those operations. ‘The oil and gas sector is actually over-instrumented’ says Tor Jakob Ramsøy of Arundo Analytics, ‘but over 50% of those sensors are not connected to anything.’ Improving day-to-day processes will mitigate the environmental impact of inefficiency in the O&G sector. ‘More efficient equipment means less pollution because you use less energy: it has a measurable and significant green effect if you run your equipment correctly,’ argues Ramsøy. If the O&G sector can capitalize on the insights it already has into operations on the ground, and consolidate the knowledge that exists at each site into a collective data analytics platform, the sector, and the planet, could be much better off.
Keep it simple, stakeholders
However, it’s not quite as simple as just connecting sensors to the cloud, as one of the largest barriers facing the adoption of IoT in O&G now is ownership of the data that is produced. ‘You have the owner of the pump, the compressor etc., each with the manufacturer’s own IoT edge gateway, but then you also have shared operatorship [of the site],’ says Ramsøy, ‘everyone wants a cut of the cake.’ To properly connect the O&G sector and improve the way equipment and general operations function, there needs to be more focus on the free movement of data between sites and between stakeholders. ‘It should be up to the asset owners to decide how they want to use their data, not the equipment manufacturers or owners,’ says Ramsøy. Until this is the case, there seems to be little chance of spreading knowledge of the IoT and the benefits that data analytics could bring if properly utilized in O&G – ‘data is not the new oil: data is worth nothing if you do nothing with it.’
To make sure that data is used and equipment insight is accessible enough to all involved, vibration sensors can be retro-fitted to monitor for faults, leakage and help provide actionable data for predictive analytics. Craig Truempi, the Director of AI and IIoT Digital Ecosystems at ATEK, spoke with me about the need to make IoT, AI and data analytics more intuitive. Traditional vibration sensors ‘listen’ to the vibrations coming from machines, but Truempi revealed that ‘50-80% of all equipment failures are due to lack of lubrication – the only way to account for these failures using vibration is with ultrasonic frequencies.’ Despite adding an extra layer of complexity to these instruments, ATEK’s systems integrate completely with all existing CMMS’s (Computer maintenance management systems) using a URL string and Rest API integration. ‘The people who have the expertise with this machinery are already used to their existing systems,’ says Truempi, ‘so the primary view of all ATEK equipment is using this framework that [plant personnel] use daily and understand perfectly.’
It’s not fluid dynamics
Integrating advanced data analysis and AI-generated actionable advice with everyday operations is crucial to promote the overall digitization of O&G sector – and simply consulting or hiring an expert to come in will not change anything. ‘If engineers and maintenance technicians don’t understand the jargon of a [data scientist or] vibration specialist, they simply won’t use their advice,’ says Truempi. Translating analysis from IoT sensors into ‘trend data that is understandable to everyone’ is key to increasing the adoption of emerging technology in a sector that requires optimization, and that has some of the harshest and deeply embedded working conditions of any sector.
Making technology accessible, rather than trying to teach complex data science to those in the field, is the key to getting the most out of IoT efficiencies that need to happen in O&G. As Truempi points out, ‘when IoT and AI are done well, you don’t even realize they’re there.’ Accessible technology is desperately needed in O&G, and companies will catch on to the benefits of comprehensive data analytics before long.
This article was written by Charles Towers-Clark from Forbes and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to legal@newscred.com.
