Shell Taps Big-Data From Way Down Deep


If you think extracting data for decision making in your organization can be tough, consider the task facing Tom Moroney and his team as they work to provide usable data from oil reservoirs tens of thousands of feet below the ocean's surface. Talk about a daunting challenge.

Tom Moroney
(Source: Shell Upstream Americas)
Tom Moroney
(Source: Shell Upstream Americas)

Moroney is deepwater technology deployment manager for Shell Upstream Americas, charged with providing geoscience expertise for Shell's deepwater portfolio in the Gulf of Mexico and Brazil. "Whatever the range of technology our deepwater portfolio demands, my team is leading efforts to qualify, de-risk, work with scientists internal to Shell and from external vendors, and partner to come up with creative, innovative systems," Moroney explained for All Analytics in a recent phone interview.

Sometimes, this is about hardware and building physical systems. Other times, it's about software and know-how. Either way, the goal is to find "cutting-edge technology solutions that will drive us forward and keep us being able to secure and expand our resource frontier in the deepwater," he said.

The technologies run the gamut. Moroney's organization works on well technologies for construction and drilling, as well as on operational technologies that, for example, deal with the processing of fluids. Once assets are in production, its work involves figuring out how to monitor, surveil, and optimize those assets. "We look at how we instrument them, how we take all that information in, how we process that data, and how we interpret, analyze, and conduct all the key diagnostics that are needed to make sense of these massive integrated production systems so that we can keep them running optimally and our uptime maximized," he said.

Mind you, he said, "These assets aren't sitting in your driveway."

Not being able to climb into or see, feel, and touch the assets is one big challenge, Moroney said. In particular, he talks about the fluids coming into installations floating in the Gulf of Mexico.

    The fluids are coming from reservoirs that are sitting in 3,000 to 10,000 feet of water, that are then several thousands of feet -- tens of thousands of feet -- below the sea floor. We have ways through seismic [imaging] to have interpretations of what the subsurface looks like, and certainly we've taken measurements on the key variables that describe the containers that hold the hydrocarbons. But these are very distant, deep, and difficult… and that is a challenge.

What's more, the information delivered up is imperfect and incomplete. Using its understanding of physics, Moroney said, his team can fill in the blanks through mathematical modeling and simulations to build a model of what it believes is occurring downhole in the reservoir and how the hydrocarbons move from the reservoir into the well bore, and ultimately how they are processed and brought topside. "These are complex systems that we have highly instrumented in many cases. But again, it's imperfect information and incomplete information and it's a big challenge trying to take all that real-time information -- actual measurements, however imperfect they are -- and compare against models of that system."

In some cases, Moroney's organization isn't necessarily using a model, he said. Sometimes, his team runs physics-based calculations and analytics. "If we know that pressure should drop X over this distance, and it's not, then we know perhaps that we have a plug or something restricting flow."

With production at stake, Moroney's team understandably wants to get ahead of such events using predictive analytics and advanced, forward-flowing asset management. Two years ago, it began using SAS Predictive Asset Maintenance (PAM), to help it work through the application of statistics and predictive analytics in order to find out what's occurring and what kinds of patterns it's seeing.

    We want to move from picking up events to spotting the patterns that those events potentially represent and then, before those patterns become trends that put us on a path of jeopardizing performance and allowing a well to become impaired or a facility to be thrown offline, we want to be able to intervene -- to take the necessary proactive steps to keep everything running at optimum or near-optimum efficiency.

It's about getting ahead of an event hours -- up to a full day, even -- before it manifests itself at topside, Moroney said. The event, say a separation issue occurring within the systems on the seafloor, will still show itself at the surface eventually. But using a predictive asset manager, the team can say, "We've already conducted extensive analytics using real-time data and we know the issue is imperfect separation, so maybe we have to increase the amount of foamer we're pumping down the hole or what have you." The goal is shrinking time to decision-making.

"What PAM is teaching us is that you can use statistics and advanced analytical solutions to actually de-convolve the problem and get down to an understanding and separate causal and correlated variables, and you can even do quite a lot with an imperfect data set," Moroney said.

Shell's deepwater technology team has always known the value of information, but this project has helped quantify it even further, he added.

I'll be sharing more about how the use of predictive analytics for asset management is evolving at Shell later this week. In the meantime, share your own deep-data experiences below. Have any projects you've worked on helped further quantify the value of information for your organization?

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Beth Schultz, Editor in Chief

Beth Schultz has more than two decades of experience as an IT writer and editor.  Most recently, she brought her expertise to bear writing thought-provoking editorial and marketing materials on a variety of technology topics for leading IT publications and industry players.  Previously, she oversaw multimedia content development, writing and editing for special feature packages at Network World. In particular, she focused on advanced IT technology and its impact on business users and in so doing became a thought leader on the revolutionary changes remaking the corporate datacenter and enterprise IT architecture. Beth has a keen ability to identify business and technology trends, developing expertise through in-depth analysis and early adopter case studies. Over the years, she has earned more than a dozen national and regional editorial excellence awards for special issues from American Business Media, American Society of Business Press Editors, Folio.net, and others.

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Sure about this?
  • 9/17/2013 12:19:40 PM
NO RATINGS

I think there may be an error here. "Tens of thousadns of miles?" Back in 2009, the Deepwater Horizon crew drilled the deepest oil and gas well in the world (Macondo). And that only had a vertical depth of 35,050 ft., or more than six miles.

Re: Sure about this?
  • 9/17/2013 12:28:44 PM
NO RATINGS

Yes, thank you, that was an error. Should have been "feet," as it now should read, not "miles." 

Re: Sure about this?
  • 9/17/2013 12:39:36 PM
NO RATINGS

Even that sounds excessive. Most wells in the Gulf of Mexico for example are in water depths of 5,000 feet or so. Sure the wells are deeper, but even at 20,000 to 30,000 feet. Does it really make sense to say "10s of thousands of feet?"

Re: Sure about this?
  • 9/17/2013 5:15:56 PM
NO RATINGS

 

It's a quote, so now that it's correct, there's not much else to do with it.

Under 3000 feet of water and then 5000 feet of rock, the point is the same - the action is only accessible with instrumentation. No diver can 'see' what's going on. If something is amiss, we have to figure it out with the data and patterns in data.

PC

Re: Sure about this?
  • 9/17/2013 11:56:21 PM
NO RATINGS

It is really fascinating to find out more about how they use models and analytics to process data and predict things. I have always wondered how the industry operated. Specially the deep sea oil drilling. I look forward to your next articles on Shell.

Re: Sure about this?
  • 9/18/2013 12:11:15 PM
NO RATINGS

@Phoenix, deepwater activities are fascinating, aren't they? I think because we simply can't imagine what it'd be like to live in that world! I will definitely share more, not only on the data and the analytics but also on the culture hurdles. Stay tuned!

Re: Sure about this?
  • 9/19/2013 10:37:28 AM
NO RATINGS

If more and better data can drive safety in an industry that had seen a spike in fatal accidents recently, it will be especially beneficial.

Re: Sure about this?
  • 9/19/2013 11:15:42 AM
NO RATINGS

I totally agree with that. My concern is only this: will people listen to the data and resist the urge to take shortcuts that could result in catastrophic incidents like the ones we have all heard about in recent years? 

The data is only as good as the people who follow it.

Re: Sure about this?
  • 9/19/2013 3:13:22 PM
NO RATINGS

We didn't really get into discussions regarding the benefits around safety, but you're absolutely right.

Re: Sure about this?
  • 9/26/2013 9:08:38 PM
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It is fascinating and a bit gut wrenching since they are drilling into the ocean and when something goes wrong it will effect us more than we will ever know. 

Re: Sure about this?
  • 9/19/2013 3:34:59 PM
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They are finally personifying data mining :)

Too Shaken To Even.......
  • 9/22/2013 2:01:28 AM
NO RATINGS

"What PAM is teaching us is that you can use statistics and advanced analytical solutions to actually de-convolve the problem...."



De-convolve ?   There's a new one.  I have no idea what this term is, so shocking to the senses - I don't even want to look it up !  ; )

Re: Too Shaken To Even.......
  • 9/22/2013 8:26:25 AM
NO RATINGS

I have to agree Louis -- that's a very strange word.

Re: Too Shaken To Even.......
  • 9/23/2013 9:28:36 AM
NO RATINGS

Well, since my source used it and I was directly quoting him, I did look it up to make sure I understood what he meant. I figure he meant to become less convoluted, which I think is a word we're all much more familiar with. In turns out "convolve" means to "entwine," in math the meaning being to "combine (one function or series) with another by forming their convolution." So to de-convolve would be the opposite. 

Re: Too Shaken To Even.......
  • 9/24/2013 4:35:31 PM
NO RATINGS

@Beth   Thanks for the definition.   Not too often a word causes a complete blank, but that one did.  Even though I have seen the word convolve, just never thought to phrase it's opposite as such.

Re: Too Shaken To Even.......
  • 9/24/2013 4:42:02 PM
NO RATINGS

I thought maybe it was a term used among analytical sorts. Maybe not!

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