Dec 192013

The Oil and Gas (O&G) industry, especially its so-called “upstream” segment, exploration and production (or going from the rock to the pipeline), is totally based on data. A seismic survey may collect petabytes of acoustic signals. Increasingly, when wells are drilled, sensors are inserted in them, and these sensors collect data for the next 30 years of production. Two completely different applications, but in both cases they result in masses of data. O&G’s dependency on data began decades ago when the Schlumberger brothers invented the “electric log” in 1926. And yet, this sector has been one of the most conservative, even lagging, adopters of modern modeling and management techniques for both information and processes.

Over the next several years – but it may take until 2020 – we will see this change. It will not result from a sudden waking up of O&G executives, who typically have no IT background and do not consider their top IT person to be a peer in the C-suite. It will instead result from a combination of forces that give them no choice:

  1. Some problems are getting too big for a single company to solve. Integrated and more secure processes, both inside and across companies, will just not be possible without ways to exchange information that has solid semantic underpinning (ontologies, metadata models, etc.).
  2. Regulators will demand certain reports on risk and mitigation procedures, as they are doing in the finance industry, among others. They won’t be able to accept and process the information if it is in plain English, or if each company delivers it in a different proprietary format.

The only solution will be to adopt standards such as the Business Process Model and Notation (BPMN), Decision Modeling Notation (DMN), XML Metadata Interchange (XMI), and others. If you are in the O&G industry, start learning about these standards, develop some business cases, and begin developing some models, even if it is just intially for intra-company sharing.

[Editor’s Note: This post is part of the annual “Cutter Predicts …” series.]


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