Oilfield services company

The motherlode

Industry: Energy
Region: USA

A global oilfield services company used advanced analytics to extract insight from its data and improve efficiencies by predicting and preventing downhole failures.

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The parallels between oil and data are well established. Like oil, data must be refined before it can be used to fuel a program or business. The analogy goes dry shortly after that point. While data may not be the new oil, data has uncapped a new era of possibilities in the oil and gas industry.

The challenge

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The new era is replete with new heroes: the science, technology and analytics that make techniques like fracking and horizontal drilling more efficient.

For example, logging-whiledrilling (LWD) sensors just behind the drill bit collect data on everything from shock and vibration to gamma rays and neutron porosity. In that same vein, neutron well logging requires high-voltage neutron generators.

They gathered an agile capability team of data scientists and industry experts to develop a cloud-based analytics platform that would accomplish three goals:

  • Improve asset utilization and crew performance
  • Increase meantime between failures (MTBF) by 100%
  • Reduce nonproductive time (NPT).
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The solution

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The team’s initial task was to prove the diagnostic and predictive value of the oilfield company’s untapped data. In the first of three advanced analytics studies, they investigated several failure scenarios to find key mechanisms accelerating age and wear of drilling equipment. They analyzed:

  • Effects of high temperatures on electronics
  • Speed of temperature cycles, fast vs. slow
  • Shock and vibration data
  • Associations between different types of failures
  • Failure of components, e.g., electronic boards, sensors, neutron generators
  • Complications of extra mechanical components such as for rotary steering.

After a couple of weeks, they confirmed the predictability potential of the datasets.

Business benefit

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Altogether, the methodology, models and data lake formed a predictive platform that enabled the oilfield company to run analyses on its own. Its data scientists are using the platform to dig deeper into surface-drilling data and integral analysis of downhole as well as surface data.

The goal is to transform all their drilling and exploration practices to be driven by data, setting ever higher standards for the rest of the industry to follow.

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