Big Data Analytics For Oil and Gas Companies - Opportunities for Success

Crunching numbers and finding opportunities in the oil patch

Megabytes, terabytes, and now, petabytes. These giant leaps in data use represent a huge management headache. And a huge business opportunity for companies wanting to improve their competitive advantage.

When data becomes too difficult to manage by conventional means, either because of the volume, the speed, or the variety, it becomes what is known as big data. Oil and gas companies have been slow to embrace big data analytics. But, larger firms are slowly stepping up and taking advantage of its capabilities.

How British Petroleum Does It

At BP, there’s a growing awareness of the immense opportunity that big data offers¹. Helping engineers better understand reservoir activity, increase refinery efficiency, improve biofuels yields, and make better trading choices are just a few examples. Company decision makers recognize data analytics as a potent way to harness these opportunities. But where are they putting big data analytics to work?

  • Sensor data. Increasingly, BP engineers are putting more sensors into rigs, wells and pipelines to measure temperature, pressure, chemicals and equipment vibrations. The variety of sensors available is increasing all the time. Engineers are getting more data back in real time, with ever-shorter cycles. This is data in motion. It describes operational conditions that can be used to further strengthen safety and improve performance.

By installing fiber optics, BP engineers receive data from deep underground. Production teams know where and how effectively the well is producing hydrocarbons.

  • Predictive data. In analytics, making accurate predictions is a high-value benefit. Production engineers compare past and current data points, which enable them to spot future conditions before they occur. With this data, they can work proactively or take corrective action ahead of time.
  • Faster, sharper seismic imaging. BP established its Center for High-Performance Computing to improve its seismic imaging capabilities. Its vast data-crunching capability, equivalent to more than 40,000 laptops, is available for use by the whole organization. The center:
    • Helps seismic imaging teams simulate, process and predict what will happen in a reservoir.
    • Processes and manages huge volumes of geological data from production sites worldwide.
    • Reduces the amount of time needed to analyze large amounts of seismic data.
    • Enables more detailed in-house modelling of rock formations.

BP engineers run analytics processes to their limit, which provides them with the highest resolution possible. These higher resolutions enable engineers to make accurate predictions about the total value a reservoir is going to deliver and do it more quickly than before.

  • A test lab for new ideas: The center’s ability to process data from many sources makes it a prime way to test new ideas. Any BP business unit can test proofs of concept without using time and resources of a real production site.

But what about smaller drillers? BDA plays a big role in their success, too.

Smart Data for Indie Drillers

Large amounts of data have also come to the oil fields of tens of thousands of small and mid-sized oil and gas companies. These folks are largely responsible for the American hydrocarbon resurgence. The enabler: smart drilling. The new abundance of output comes from knowing where to drill, where to direct the drilling process underground and how to manage production efficiently in real time.

Big Data Analytics for New Drilling Scenarios

Big data analytics can provide small to mid-size independent oil producers with the real-time seismic data that identifies the most porous or hydrocarbon-rich rock. This can be most valuable in unconventional plays, areas where conventional drilling methods and assumptions don’t work well².

These areas, where fracking (fracturing rock beds that contain gas or oil) is the norm, have been described as a variation of the mining business. Rather than drilling several wells and recovering oil from a small volume of rock, engineers drill 10,000 wells in a single, huge area. Drilling becomes an assembly line process, and setting up and running efficient operations can determine whether a venture is profitable. Predictive analytics plays a role in reducing equipment downtime and the need to replace faulty machines.

Next Time: Big data analytics can contribute to profitable operations of oil companies of all sizes. So why isn’t it being used more often?

[1] “Number Crunching with Big Data” at http://www.bp.com/en/global/corporate/press/bp-magazine/innovations/number-crunching-with-big-data.html.

[2] Collin Walton, “Q&A: Big Oil, meet Big Data” Houston Chronicle, August 14, 2014  at http://www.houstonchronicle.com/business/energy/article/Q-A-Big-Oil-meet-Big-Data-5707337.php


Syntelli consultants possess extensive experience in helping Oil & Gas companies implement Big Data initiatives to leverage the power of their data.

Learn more about the value of Big Data Analytics in the oilfield and contact us today to see how we can help your organization!

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Daniel-Smith
Daniel Smith

Director of Data Science and Innovation
About Daniel: Using Business Intelligence platforms to bridge the gap between Advanced Data Analytics and the efficient effective principles of accounting, Daniel applies technology and mathematics to make business faster and smarter.

Daniel has managed solutions for diverse client sectors such as as advertising, military, insurance, and oil & gas. These solutions include Business Intelligence Platform management, online key performance indicator identification and tracking, to full predictive data model construction. Although the analytic solutions are often mathematically complex, Daniel’s presentation and academic background ensures any insights delivered by solutions are relevant and simple to understand.