This news is classified in: Traditional Energy Oil and Gas
Mar 15, 2019
Smartphones, smart-meters and smart-cars – premised on digital tools making communication, monitoring energy consumption and driving more efficient – are among us. It seems oil and gas explorers have their own nifty kit – the 'smart' rig! It's been around for a while, in use offshore and is getting smarter as data analytics, robotics and artificial intelligence proliferate.
At IHS Markit's CERAWeek 2019, a major energy conference in Houston, U.S., the exhibition floor appears abuzz with a plethora of kit, sensors, data tools, robotic claws, remote management devices and drones of all descriptions, shapes and sizes, and lest we forget – use cases! Industry vendors are eyeing billions of dollars in sales, while oil and gas drillers are looking at savings resulting from process optimization.
For Chris Dartnell, President of the Oil, Gas and Petrochemicals Business at Schneider Electric (EPA:SU), it signifies the confluence of information technology (IT) and operational technology (OT). "Change management or digitization in oil exploration and production (E&P) is being driven right from the top, whether we are talking about state-owned Abu Dhabi National Oil Company (ADNOC) or a FTSE 100 international oil company like BP.
So what is the fuss all about? Picture this – the oil or gas well has been dug, hydrocarbon resource has been found, it's all connected up and once all of that is done – everything from process safety to production levels, composition of resource to flow rate – is monitored offsite.
"And that's not some industry utopia; it's already here in the case of offshore platforms. The first unmanned natural gas platform appeared almost 20 years ago as the deployment is simpler there than in the case of an oil rig," Dartnell adds.
And now onshore site operators are lapping the technology up too, a move that became visible less than five years ago in the wake of the June 2014 oil price slump that saw crude futures plummet from $110 per barrel prices to under $30 early in 2016, before a market recovery took hold.
Peter Zornio, Chief Technology Officer of the Automation Division at Emerson (NYSE:EMR) notes: "Back then, if you looked onshore you would be surprised how non-automated things were. They would put the minimum amount of automation and soak costs that come with it, with engineering call-outs for the smallest of matters and high onsite personnel levels. But 2014 is when we really started to see things change."
Retrofitting for a reason
Not only are greenfield projects registering advanced automation, oil and gas explorers have also started revisiting and retrofitting older onstream production sites and for good reason.
Dartnell says: "It's all about getting the maximum return on investment (ROI) from an asset. So when E&P players started noticing the gains from greenfield sites, retrofitting existing sites or at least thinking about retrofitting was a logical pathway."
For instance, Schneider Electric data reveals that onsite energy consumption – one of the biggest costs associated with hydrocarbon extraction – came down by 50% as result of smarter, more automated operations.
"And a host of other factors come into play- from safety associated with remote monitoring of platforms to data gathering on resource and drilling techniques that can be effectively extrapolated to improve further exploration. And now it's a race to get ahead of the curve."
What's more "resource maximization" also comes into play, adds Emerson's Zornio. "There's the most optimized and cost efficient way of extracting the hydrocarbon, and then there’s the maximization of the basin volume as well.
"Most reservoirs produce 30% to 35% of the hydrocarbon, leaving behind nearly 60% in many cases. The rush is now on to digitally organize and maximize output that could lead to an upgrade of a producer's resource reserves position, something that investors keep a keen eye on. Technology enabled reservoir modelling, followed by headline production maximization is advancing rapidly."
A numbers game beyond reserves
But that's not the only thing impressing investors, says Deborah Byers, Americas Sector and Solutions Leader, and U.S. Oil and Gas Leader at EY. "Technology does change the economics of the project and an improvement in the headline valuation of an oil and gas producer does factor into investors’ and analysts’ mindset. However, in the age of 'Industry 4.0' and the current oil price climate, investors are also eyeing the level of cost optimization a company is bringing about."
With all the technology that is available, the Industrial Internet of Things (IIoT) has gone way beyond data and maintenance schedules. Real time data is being gathered, historical data collected over time, and fed into algorithms to improve not just onstream production, but further drilling drives at the same or nearby sites.
"Just cataloging reserves on standalone basis won't cut it. Lots of companies have reserves but they need to show how cost effective their extraction process can be. Wall Street, given the relatively lower valuations of legacy oil and gas companies, is now looking at who is being proactive in embracing cost optimization, rather than reactive, in the current climate," Byers adds.
While companies can't control oil and gas prices, being good at controlling their own upstream efficiencies is what it is bottling down to, and it doesn't come cheap. Given the competitive nature of project tenders, vendors remain cagey in revealing the price of their kit whether we are talking drones or analytics systems.
Andrew Steinhubl, Principal and Strategy Practice Lead at KPMG U.S.' Energy and Natural Resources Practice, says one-off costs might appear off-putting on paper but tangible benefits are obvious.
"Every project, every company has different cost/benefit parameters. Evidence and industry interaction points to incremental returns from deployment of optimization technology. Of course, scale matters which is why you will find that oil and gas majors are deploying smart solutions faster than independents.
"That said, even if state of the art kit might not be visible at smallcap upstream players, predictive analysis most certainly is. Interpretation of big data is getting ubiquitous in the industry."
Dartnell, Zornio, Byers and Steinhubl all agree with industry consensus that upstream players are way more efficient at $60 oil prices than they ever were at $120.
It seems there's nothing quite like necessity. They've taken the downstream mentality of refiners and product marketers – who have always had to contend with fine margins and lower crack spreads to survive – taken it upstream. Technology happens to be the enabler across the board.
