Data Wars – The New Digital Battleground in Oil and Gas

A high tech battle for data ownership in oil and gas

Data Wars – The New Digital Battleground in Oil and Gas

Data is emerging as the new unspoken battleground for oil and gas supremacy. Why is this happening and should it be a concern?

Data – The New Battleground

Many oil and gas companies are wrestling with how they “may wish” to respond to the rising role of digital in the industry. And I say “may wish” with care, as it’s not obvious to many oil and gas executives that there is even a need to respond — some of the most consistently profitable upstream oil and gas companies dismiss digital as just so much hype promoted by consultants and technology companies anxious to sell them more stuff. Few oil and gas companies are talking publicly about their digital successes, suggesting that either the successes are so outrageous as to warrant secrecy, or there isn’t much success and progress is halted. As a CIO once reminded me, if it isn’t broken, why fix it?

After 4 years of relentless pressure on margins, volatile prices and unprecedented levels of workforce displacement, the upstream industry has fundamentally reset its cost structure to cope with what could be lower pricing forever. You might reasonably ask where is the burning platform today that attracts digital investment? Oil and gas companies across the entire spectrum (upstream production, offshore, refining, pipelines), are acutely aware that they operate large scale and dangerous infrastructure in the midst of human civilisation. Health and safety considerations are paramount as there’s not a lot of room for error. And the industry is hotly competitive, which drives a close attention to the economics of the business. 

So where is the business-driven digital prize? One candidate opportunity would be in approaching data differently. The oil and gas industry is exceptionally data rich, and generates terabytes by the minute.

The problem is that data issues and opportunities are fiendishly hard to articulate and generally fail to inspire a response inside most oil and gas outfits. This is now risky as capital markets keenly reward companies that have a strong value proposition based on their data assets. The largest companies in the world by market capitalisation at the end of 2017 were all companies that merchant primarily in data (Amazon, Apple, Alphabet, Facebook, Microsoft and Tencent). The largest companies in the world by revenue include several oil and gas companies like ExxonMobil and PetroChina  (only Apple makes the top ten on both lists). Capital and investment is shifting towards those companies with an explicit or implicit data strategy

So what? Commodity markets want the molecules of hydrocarbons, not bits. But is this changing? And if it’s not changing, could someone come along and change it?

Tribal skirmishes

As I see it, the challenges of data management internal to most industrial concerns are like the minor tribal battles of ancient cultures. Ask employees in the pipeline, upstream or LNG industry about their experience with data and they can all point to the litany of issues that frustrate them:

  • No clear vision from company management about the role and importance of data to the company. 
  • Industry software product designs that imprison data inside and thwart efforts to release.
  • A tendency by department heads and technical experts when purchasing new software to overweight analytic functions, and underweight data features
  • A resulting landscape of information islands or silos, with multiple definitions of such basic things as gas wells and compressors 
  • A reliance on Excel to solve for all manner of data-related problems, such as facilitating the exchange of data between two incompatible systems, manipulating data, and visualising data via charts and graphs.
  • Accounting rules that treat data as a cost to be managed, rather than an asset to exploit.
  • Unclear responsibilities for data ownership, and an inability to articulate the capital requirements and benefits from better data management practices.
  • Few performance metrics that are specific to data quality.
  • Internal competition for capital between divisions that gives rise to active measures to thwart data sharing, collaboration and mutual support.

It’s baffling that the country of Estonia, with 6 million citizens, has legally mandated that the government cannot ask its citizens for the same data twice. Once you have provided your home address or birth date, or tax number to a government department, just once, that’s it. They can never ask you for it again. Their systems have to sync up, by law. That’s vision.

I don’t spend much time working in other industries, but I suspect these kinds of challenges are endemic to many sectors, particularly those that are heavy asset centric (where the cost of such assets is substantial and tends to dominate balance sheets).

Oil and gas services companies now look at this state and sense an opportunity in the making. 

The war for data supremacy is underway

Ten years ago, I worked with a major fracking outfit who, as a way to high-grade their quality of service, connected all their frack spreads to their in-house control room. Frack data flowed continuously into this facility, frequently via expensive satellite uplinks. The company’s best engineers and fracking experts spent their days in the control room guiding the fracks, tuning the horsepower, dealing with upsets and generally keeping the assets as utilised as possible. They did nothing with the data once the frack was over. Today, however, they keep the data.

Four years ago I met with a downhole tool company whose measurement devices provided highly reliable visibility to production conditions — water pressures, temperatures, radioactivity, flow rates, volumes and many other data points. They sold the tools to their customers (in this case, gas well operators), who used the data to manage well performance, schedule services and forecast production

I asked them at the time why, in an emerging world of cloud computing and analytics, did they chose not to capture the data themselves and interpret it as a service for their customers. They could have built up an enormous library of well operating conditions. Too hard, they claimed, even though their own product testing regime included the analytics capabilities and dashboard.

Today, shrewd field services companies are now woke to the potential value of the data. Queries about who owns the data (paid for by the exploration company, but collected by the service company) elicit a mumbled and vague response. Service contracts are silent on who owns the data, and what restrictions there might be on the use and sharing of the data. For the moment, producers are ok, if a bit uneasy, with the Drillco/Frackco/Serviceco “utilizing” the data provided it’s not shared.

What can you do with a huge ocean of data? Why, feed it into an artificial intelligence engine and see what you can make of it. That’s how the voice engines in Siri, Alexa, and Google Home have gotten better and better. Just for fun, pull up your browser and play Google Quick Draw, an AI engine that interprets doodles and guesses what you’re attempting to draw. It’s amazing how good it is. It works because millions of people are playing with it at the same time, feeding it millions of data points.

Using AI, a fracking firm like a Calfrac gets smarter and smarter over time about frack design and execution, because it has accumulated hundreds of frack histories, and offers a superior fracking service. A drilling company does the same thing with drilling data (see Pason), and a compression company with turbines (see GE). More and more sensors will be added to industrial infrastructure over the next 5 years, rising from 8 billion in 2016 to 20 billion by 2025, and business model designs are separating sensor ownership from the data the sensor generates. That’s a good thing. But petroleum companies should be concerned about unintentionally enabling service companies to create  monopolies within their business models and the risk that the data companies proceed to extract rent.  

I’m also concerned about a looming scenario where all that data is tied up in the clutches of a dozen different companies, and not just in upstream areas, but operating data for pumps, compressors, and engines. Getting it back won’t be easy. Linking your fracking data from one company with the drilling data from another company to the artificial lift data from a third company sounds nigh impossible, or comes at a high price.

The consumer world is deeply alarmed about the use and misuse of their personal data. Sure, inadvertently sharing personal or corporate data is a risk concern, but in a world of AI, that’s yesterday’s risk. Today’s risk is business model shift.

How the battle is shaping up

I clearly see the emerging outline of a war for data, and I offer the following observations:

  • The strategic objective is to own the data resource (similar to Google’s mission to organize the world’s data), and leverage AI tools to extract value. 
  • Some service companies are stealthily on the offensive, and are increasingly concentrating their investment dollars on this objective.
  • They are maneuvering into positions of maximum advantage over their quarry (oil and gas companies).
  • By offering seductive terms (subscription models, no money down) and avoiding the strategic discussion (who owns the data, data sharing, data usage), they are securing their high ground strategic location for the future.
  • Most oil and gas companies are complacent or unaware of their precarious valley position.
  • The surprise on the battlefield will come in the form of pricing power or restrictive feature access.

It’s time to strategize.  

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