Turning Big Data insights into bigger solutions

Energy forum attendees offer blueprints for using Big Data analytics to drive operational efficiencies, cut costs, boosting production, and improving worker productivity.

By Sidney Hill Jr. December 13, 2016

At the core, oil and gas companies have always been data-driven enterprises. From their earliest days, these companies have relied on geologists studying rock formations to pinpoint the most likely spots for finding oil or gas and then pass that data to engineers for analysis to determine the best method for extracting the product from the ground. 

Investing in digital technologies for the oil and gas industry

Over the years, the tools used to perform this data collection and analysis have become more sophisticated. Generally, the new tools produce more accurate results, partly because they generate greater volumes of data.

Some oil and gas companies have found ways of harnessing these new troves of data to help boost profits by streamlining their operations. Recently, more companies are realizing that mastering the art of data analysis is not just a good idea—it’s becoming essential to survive as the era of low oil and gas prices shows no signs of ending.

That was the predominant sentiment as several hundred oil and gas industry professionals converged in Houston this past September for the TIBCO Energy Forum.

This event was primarily a gathering of individuals who use technology from TIBCO Software Inc. in some aspect of their operations. The agenda was packed with presentations recounting the performance improvements achieved after adoption of various TIBCO products.

The TIBCO product portfolio consists of an array of software programs that help to integrate, organize, and analyze data generated by various systems across an enterprise. This puts TIBCO in the class of vendors offering Big Data analytics solutions.

At its energy forum, TIBCO was showcasing its Insight Platform, a suite of data management and analysis solutions that allow companies to build an infrastructure for plucking data from disparate systems to generate reports that can be customized for different groups of users.

Despite the forum’s exclusive focus on TIBCO technology, there were real performance improvement metrics presented by users. It’s likely that similar metrics are being produced by other companies employing data management and analysis solutions from other vendors.

The results of a survey of upstream oil and gas concerns released earlier this year indicates oil and gas companies are relying on digital technologies—and specifically Big Data analytics solutions—more heavily than ever.

In a study commissioned by Accenture and Microsoft, the 2016 Upstream Oil and Gas Digital Trends Survey included responses from individuals involved in information technology (IT) purchasing decisions for international oil companies, national oil companies, independents, and oilfield services firms.

"In the current challenging environment, the upstream oil and gas industry is focusing digital technologies on areas that help them work smarter and deliver significant efficiencies and savings in the short term while enabling them to make better decisions faster," said Rich Holsman, global head of digital in Accenture’s energy industry group. "So in the short term, we expect these companies will continue to invest in areas that help lower operations costs through technologies like increased worker productivity, with mobility, lower infrastructure costs through the cloud, and drive better asset management through analytics." 

Seeing business value in digital technologies

Oil and gas companies believe strongly in the power of technology to help them achieve those goals. Even as they continue to cut spending on personnel and capital equipment, in the face of persistently low prices, 80% of upstream oil and gas companies plan to either maintain, increase, or significantly increase spending on digital technologies over the next 3 to 5 years, according to the Accenture-Microsoft survey. More than 90% of the survey respondents said digital technologies are already bringing value to their businesses, with more than 50% saying they consider that value to be significant.

According to survey respondents, most of this value is coming in two areas: according to survey respondents including identifying ways of reducing costs and providing information that helps workers make better decisions in less time.

The survey also indicates oil and gas companies believe they can continue reaping these benefits by focusing their spending, at least in the near term, on three primary technologies:

  • Mobile applications
  • Cloud-based platforms 
  • Analytics solutions.

A majority of respondents said they no longer view the cloud as merely part of an IT infrastructure, but instead see it as an enabler of productivity tools, including mobile devices, and smart sensors spread across fields, and is now considered part of the Industrial Internet of Things (IIoT).

Two-thirds of respondents (66%) identified analytics as one of the most important capabilities for transforming a company, but only 13% felt their firm’s analytical capabilities currently are mature enough to foster true organizational transformation. There is, however, a strong desire to rectify that situation, with 65% of respondents saying they plan to implement more analytic capabilities over the next 3 years.

"By taking advantage of the intelligent cloud, greater use of analytics and IoT go hand-in-hand with what we are seeing in our business today—the advent of the industrial Internet enabling the power of digital across the oil and gas landscape," said Craig Hodges, general manager of the Gulf Coast District at Microsoft. "You can see this trend gaining traction from connected wells and intelligent pipelines to highly efficient digital refineries."

Survey respondents said digital technology is having a major positive impact on the industry’s workforce by fostering greater employee engagement, making workers more productive, and providing opportunities to get training and develop new skills.

Multiple presenters brought the numbers compiled in the Accenture-Microsoft survey to life at the TIBCO Energy Forum. Among them was Abhi Banerjee, senior IT manager at Halliburton. He spoke about the importance of IT and operations professionals collaborating to build technology platforms that can create the "actionable intelligence" needed to improve margins by, among other things, increasing production and reducing unplanned downtime.

"In 2015, we realized that this big dip in oil prices was not temporary," Banerjee said. "That triggered immediate spending cuts across the business, and we saw a 50% reduction in our IT project portfolio."

Even as it was reducing the company’s overall IT spending, Banerjee said, Halliburton management saw fit to boost its investment in certain technologies-specifically business intelligence, data mining, and analytics-by 58%. "This also brought a new focus to our business intelligence group."

Banerjee said this new focus resulted from management’s realization that the analytics solutions deployed in the business intelligence group offered the best chance of successfully tackling Halliburton’s most urgent needs in the current market environment. Those needs, according to Banerjee, are boosting operational efficiency, increasing asset utilization and availability, and optimizing labor costs. 

Identifying key performance indicators with Big Data

Addressing those needs required IT staff to engage with colleagues from various business units. However, in doing so, Banerjee said, Halliburton—like most of the companies represented in the Accenture-Microsoft survey—discovered that its analytics capabilities were not yet mature enough to drive the desired business transformation.

Most of the problems were due to the historical practice of having business units monitor their own performance independent of one another. As a result, there were no uniform definitions for key performance indicators (KPI) across the business, nor were there any standard methods for publishing or sharing that information. As a result, Banerjee said, "it was difficult to identify any trends, spot potential risks, or even identify true efficiencies."

Eventually—through continued collaboration between the IT and operations teams—Halliburton solved these problems, and in the process, discovered methods for deploying analytics that Banerjee believes would also benefit other companies.

"Our IT delivery approach is to standardize and automate dashboards for all users within a specific group," Banerjee said. "The interfaces for those dashboards must be intuitive, with no training required to use them. If there’s any pain involved, users will abandon them. All data presented should be easy to understand."

Users seeking detailed data should be able to drill down to find it, Banerjee said, but top-level data should "be as simple as a pie chart." By following these rules, Banerjee said, Halliburton created a "one-stop shop" for users across the enterprise to find the information they need to perform their jobs at optimum level. They can instantly find KPI’s related to cost, compliance, labor, or productivity, with much of that data showing up in real time.

Banerjee also noted that as the number of dashboards increased, the cost of building them decreased because much of the data going to any dashboard already had been placed in a central location and could simply be directed to multiple interfaces. "Our cost per dashboard decreased by 58% over 2 years," he said.

David McConkey, IT manager for enterprise operations at Hess Corporation, a global independent exploration and production company, had a similar story to tell at the TIBCO Energy Forum. McConkey recounted Hess’ experience with TIBCO Spotfire, a data visualization and analysis tool. Hess installed Spotfire in 2012, and to date, has created more than 1,400 reports for users across the enterprise.

Using this system has doubled over the past year to 575 unique users per month, McConkey said. McConkey adds that this usage is widespread and the demand continues to grow, spanning departments such as engineering, geoscience, drilling and completions, operations, supply chain, finance, environmental health and safety, audit, and IT.

The system is so popular, in McConkey’s view, because it "helps to analyze vast amounts of data from a variety of sources in an intuitive, visual environment to spot trends, outliers, anomalies, threats, and opportunities." 

The future of data analytics in the oil and gas industry

At the TIBCO Energy Forum, McConkey identified six specific reports that are widely used at Hess and outlined both the use case and value derived from each report (See Table 1).

One report, which Hess has labeled Bakken Asset Manager, is an example of what many experts believe is the future of data analytics in the oil and gas industry. This report tracks the performance of Hess’ assets in North Dakota’s Bakken shale play. It blends data on well performance and reservoir behavior with other data.

McConkey said all this data flows into Spotfire, where it’s combined for viewing through an interface that’s known within Hess as a "data visualization center." Users can tap into this interface and get a complete picture of how any given well is performing, or they can get a reading on things such as gross oil production within any area of Hess’ Bakken play. The report also is linked to a predictive modeling tool that allows for forecasting how various assets will perform given current environmental conditions. McConkey says this capability has helped Hess improve its decision-making in the Bakken fields.

The use of predictive modeling puts Hess a bit beyond where most oil and gas companies currently are when it comes to the use of analytics.

Currently, even the most advanced users of analytics within the sector are reviewing operational data to measure their past performance. They can use that information to make adjustments to processes and see real improvement-in terms of reduced cost or increased productivity going forward. But this improvement typically happens after the fact. With predictive modeling, the theory goes, users will be able to see the signs of poor performance in advance, and take action to avoid the problem altogether.

Halliburton’s Banerjee agrees that predictive analytics solutions are on the horizon, and he’s already envisioning a step beyond that—something called prescriptive analytics. That would entail systems that not only predict that an operation is about to go awry, but also have the capability to instantly tell the user how to rectify the situation.

Michael O’Connell, TIBCO’s chief analytics officer, shares Banerjee’s vision of the future of analytics and says it reflects the journey that TIBCO has been on with its oil and gas industry customers.

"We’ve been on this journey with you to digitize your business for quite some time," O’Connell said in his opening remarks at the TIBCO Energy Forum. "It started with looking in the rearview mirror to describe what happened in the past. Now, we’re on to predicting what’s going to happen next and determining what to do about it. We call that using data to turn insight into action."

Sidney Hill Jr. is a graduate from the Medill School of Journalism at Northwestern University. He has been writing about the convergence of business and technology for more than 20 years.

Original content can be found at Oil and Gas Engineering.