Big Data in Oil and Gas: How to Avoid the Big Myth

By Vimal Kapur, President and CEO of Honeywell Process Solutions
Even though the oil and gas industry isn’t in the difficult times of 2015, demands on the industry have never been greater. A host of factors are i...

Even though the oil and gas industry isn’t in the difficult times of 2015, demands on the industry have never been greater. A host of factors are increasing costs, reducing revenues and creating new risk management issues for operating companies. Adding to those concerns is greatly heightened regulatory oversight and public scrutiny of environmental and safety risk.

All of this is taking place in the age of big data. The idea of a connected world and a connected industry has held great promise for quite some time, but the major challenge facing the industry is how to truly harness the power of that data. Development of the Industrial Internet has provided new opportunities for oil and gas businesses to lower the cost of operations and improve safety, but in order to most effectively maintain profitability and maximize return on investment (ROI), that data needs to be combined with the right expertise.

There is a school of thought that companies can collect lots of data and let an algorithm do the work to come up with a magic solution. This may be a good vision for the long term, but in the near term it cannot work. For companies to leverage the true power of big data – whether it’s oil and gas, chemical, pulp and paper or other industries – the data must be combined with a layer of expert domain knowledge. After all, the best software in the world is only as good as the humans who wrote it.

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The issue for the process industry is not a lack of data, but how to make use of the vast data that already exists to generate a meaningful impact on operations and overall business performance. What is different today is we can securely transfer data from the asset/plant to a centralised location (the cloud) and we have immense processing capability. Experts in the operations of these plants and assets are constantly monitoring the real-time data, making predictions on any unplanned events using various tools and offering real time advice to eliminate unplanned shutdowns, improve safety and enhance productivity. Multiple plants and facilities can be connected to the cloud, so the experts have a true global view that adds to the knowledge base. This, in effect, makes the entire system self-learning, and the benefits are translated to everyone. This is something that is available today and helping oil and gas and other process industries to drive better reliability, uptime and safety performance.

Industrial organisations also have a big opportunity to leverage vast data that exists in various plant and business systems to drive a data-driven decision culture. In each customer site, there are vast data repositories in applications such as the plant’s ERP system, real time historian, Excel sheets, maintenance systems and others that track actual plant/asset performance in real time. Solutions exist today that can leverage these vast sources of data and build enterprise-level dashboards to drive superior performance of the assets. This approach drives a culture of making decisions based on data in every asset/plant and aligns all stakeholders to common business objectives to drive more production, improved safety and lower cost.

Experience shows that the industrial internet of things (IIoT) enables transformation of nearly all industries. A connected enterprise significantly enhances decision-making, increases security and productivity as well as improves overall collaboration by providing the right information at the right time, to help optimise operations. In addition to ensuring the right data is captured and the right experts are providing analysis, companies should keep a few other things in mind when implementing their IIoT setup. First, they need to understand the value of visibility into processes and facilities. They also need to correctly identify measurements that would advance plant visibility. Thirdly, the companies should engage the workforce in the identification and implementation of these new metrics. Finally, the companies should clearly develop a shared path to success with IIoT vendors and suppliers.

In the end, industrial organisations across the globe are requiring better solutions to compete in an unpredictable market. New capabilities such as digitisation and the cloud hold great promise. But it is critical that it is done in the right way. Using data for the sake of using data won’t help anyone, because there is no substitute for good, old-fashioned expertise. When that expertise is combined with the data, along with clear and thought-out goals, the potential is limitless.


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