GE Adaptix Uses the Power of Data to Increase Efficiency in the Oil Sands

For most of us, history is the best guide to making efficient decisions. Whether we’re deciding when to have a medical checkup, how to budget for office supplies, or the best way to make coffee, we usually return to the processes or tools that have already worked in the past. Then we hope for the best.

It’s no different for oil-sands producers. They rely on experience and history to make decisions about everything from maintenance schedules to extraction processes.

But what if there were a better way? How would we know?

Through state-of-the-art digital technology, GE is about to offer answers to those questions with the Adaptix software suite, which launched on Nov 30 with an event at the Customer Innovation Centre in Calgary.

What is Adaptix? “It’s a set of software tools to improve upstream operations by applying machine learning and adaptive intelligence,” says Warren Gieck, AI and production optimization leader with GE, based at the Customer Innovation Centre in Calgary.

The initial focus of GE Adaptix will be thermal production optimization, targeting the in situ oil-sands sector.

In situ—Latin for “on site”—refers to methods of extraction that take bitumen out of deposits deep underground. These processes use steam to “melt” the bitumen, lowering its viscosity so it can be pumped to the surface.

Compared to the familiar strip-mining technique, in which oil-bearing sand is hauled by truck to a central plant for extraction, in situ methods allow much deeper deposits to be tapped. Today, in situ extraction accounts for the majority of oil sands production.

There are two main in situ processes: Steam-assisted gravity drainage, or SAGD, which uses two horizontal well bores; and cyclic steam stimulation, or CSS (also called “huff and puff”), which uses one vertical well that alternates between steam extraction and oil collection.themal-opti-pull-quoteThanks to advanced real-time digital models of wells in service, GE Adaptix and its SteamIQ and WellIQ components will be able to help producers not only reduce their use of steam, but also the natural gas used to heat it.

 “In the past, the process has been determined through experience,” Gieck says. “These new solutions allow operators to test their wells digitally.”

A computerized model of a SAGD pair, for example, will allow operators to literally see the results of various adjustments in steam injection, so they can be much more precise in their application.

Improved precision will reduce both costs and greenhouse gas emissions — a win-win scenario for industry and the planet. To date, Gieck says, his team has found that improvements of one to six percent can be achieved immediately by applying SteamIQ in the field.

“If you can reduce your cost to produce, it can open up reserves you wouldn’t have had access to previously,” he says. “You can increase your available resources.”

The digital models created with GE Adaptix hold tremendous promise for increased efficiency, too. For example, oil-sands plants normally stick to a regular maintenance schedule, shutting down, refitting and replacing equipment on a predetermined timeline.

“Imagine the possibilities if you were taking equipment offline to increase efficiency only when needed, rather than on an experience-based schedule,” Gieck says. “How does that impact your profitability?”

GE Adaptix, especially when integrated with the GE Predix data-collection and sharing platform, could potentially change the way teams work together, he adds.

“It helps break down silos between different operating divisions of the business. Using the Predix platform, you have visibility across the organization. This creates a window into the process that each division can look at in the way they need to see it.”


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