Santos a world beater: research

TAKEOVER target Santos’ predictive analytics program sits 3-5 years ahead of the “vast majority” of other players and indeed the industrial average, not just in the oil and gas patch but across every sector globally, new research from the Australian Information Industry Association has found.
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Steven Travers, who led Baker Hughes' operations in the Cooper Basin and was recently appointed general manager of the Internet of Things Mining and Energy Cluster launched in July with Core Energy Group in July, made the revelation to Energy News following extensive research he and his team had undertaken across Australia's mining and energy sectors.
The cluster's research found that onshore oil and gas fields present opportunities for industry since they require a range of services at a price point that large service providers find tough to match. 
Onshore developments are characterised by a continuous expansion mode by constantly drilling more wells with an imperative for continuous improvement, and the cluster found five specific areas of opportunity for oilers: field worker support, approval process support, remote analytics for equipment reliability, supplier management and improved resource evaluation. 
Woodside Petroleum has been more vocal about its digital aspirations, partnering with IBM's Watson platform for artificial intelligence, using predictive analytics to foresee and prevent unplanned shutdowns and optimise production at assets like Pluto.
Yet Travers said Santos' less-hyped approach has been setting the pace in the Cooper Basin.
"The official consensus is that Santos' predictive analytics program sits 3-5 years ahead of the vast majority of other players and indeed the industrial average, not just in terms of oil and gas but every industry, every sector across the world," he told Energy News.
"There's quite a bit going on within our large resources companies here in Australia and it's very much been supplemented by our capability right the way across the technology ecosphere.
"We can see Santos' predictive analytics program as being a massive success in a similar vein to what Woodside has done.
"They've really developed it from a concept project to something that's been rolled out across the board, and it's had some impressive results."
While predictive maintenance and improving costs appears to be the "proving ground" for a lot of predictive analytics, Travers says the real game for resource companies is getting analytics working in the main back office and field processes, which is where Santos has excelled.
"Maintenance is going to be 10% of your costs at the absolute most. It's your operational processes you really need to get working with, and we're certainly seeing that with the more successful projects," Travers said.
"We have an awful lot of information and you can see best practices. If you have a large enough dataset you don't need to waste time fully cleansing it, you can just take that really huge dataset and do your analytics over the top of it and it will work itself out with false positives."
He described the concept of false positives as "anything that's coming from wrong data, if your dataset is big enough, it will just go away".
In field worker support, Travers' cluster has seen technologies presented more on the minerals side to augment the operator and technician experience, using digital twins.
Yet digital twins - a concept which DNV GL and Emerson has been working on lately for the oil and gas sector - fits better with oil and gas, Travers said.
"It allows you to test and develop things offline, and also allows you to have a pretty infallible knowledge management system so you always have support for any of your workers that are out there, you can always go into that twin and look at what might happen, what the best procedure is,  [the] best processes to deal with what's happening," he said.
"Right now people are scratching around the surface a bit, and you'll find technology departments are looking things like the Microsoft product HoloLens.
"People are starting to look at technologies which can either put forward an augmented reality system, or if you're talking about field worker support you can automatically pinpoint problems before technicians go out and push through all the technical manuals and best practice and make sure when someone turns up on the job it's already there. "