Analytical Assist: Lean times for the oil and gas industry call for analytical insights

By Ian Jones, Senior Strategist for SAS' energy risk management practice

In recent industry publications, major energy companies have heralded the return on investment they gain from embracing analytics. But a new report on Canada’s oil and gas industry finds that a sizeable group of executives aren’t so sure. They don’t think they have the bandwidth – in terms of both budget and knowhow – to take advantage of the latest technology in the digital oilfield. What if these oil and gas executives could explore the potential of analytics before they take on the implementation expense and ramp up their in-house skill set?

Uncertainty among executives is understandable, but there’s no better time to get educated about analytics, according to JWN Energy’s new report, Digital Oilfield Outlook Report: Optimizing operations to unlock hidden barrels. “In the midst of a prolonged and painful trough in the oil and gas price cycle, companies have pulled in their horns and intensely re-examined their own operations to squeeze out every ounce of efficiency... Analytic technologies offer the greatest potential to cut costs, boost efficiency and strengthen the bottom line.”

The report, based on an extensive survey of Canadian oil and gas companies, found that the rewards of analytics can be great, but it’s the constraints to deploying them that are top of mind for many oil and gas executives. It’s not surprising in the current price climate that the survey rated budget considerations as the chief impediment. The executives said they also face organizational barriers to adopting analytical solutions. They worry about their ability to successfully capture quality data and blend new analytical approaches with their existing technology and infrastructure.

More telling is how the majority of survey respondents responded to questions about the potential of technology to optimize their operations:  They thought the answer was out of scope for their role. “This indicates a need to bring employees up to speed on the technologies in question and the important role the technologies will play in the future of the organization, as a lack of buy-in will only impede implementation,” according to JWN.

This is not a small thing. The report highlights two areas where analytics can offer the most bang for the buck: Production asset optimization and predictive maintenance. But 65 percent of those surveyed did not believe they had adequate insight into the technological solutions to optimize production assets. For predictive maintenance, 54 percent felt the same way. Twenty percent said they aren’t aware of the adoption requirements for analytical approaches, and seven percent said they didn’t understand the options available in the marketplace to solve their problems.

In a recent live workshop, JWN and SAS brought together oil and gas professionals to explore how they overcome these kinds of internal roadblocks to increase operational efficiency and lower costs. Among the compelling findings, recommendations and creative business models included in the workshop summary report, Conquering the Digital Divide in the Midst of the Downturn, was this executive’s comment: “We understand the importance of adopting a data analytics strategy, but are still looking at how to best gather information and effectively utilize it in a cost-effective way.”

All of this explains why many executives don’t feel ready to embrace analytics. In the survey, one-third of those who would be primary users of analytics did not see knowledge of the solutions as a key part of their role in the organization. That is likely to change as their peers increasingly rave about the results of analytics initiatives in oil industry magazines and web forums.                                                                                                                                                                                     

Executives who end up being interviewed in industry journals are those who have acknowledged they can’t do much to moderate the continued low prices on the buy side and have taken a hard look at their operations instead. They have sought out efficiencies wherever they are hiding in the value chain, with analytics providing the means to reveal these efficiencies and translate them into hard dollar results.

In the survey, most executives said unplanned outages were their most damaging expense, especially for an industry already heavily streamlining operations. The executives said they are eager for ways to minimize repair costs and reduce safety concerns. At SAS, we have heard the same. We’ve also seen the contribution predictive maintenance can make.

One dramatic example is a major European gas field whose production output is used to stabilize gas supplies by filling in for shortfalls in the domestic and regional markets. This swing producer relies on a massive, 31,000-horsepower compression train whose core hovers over a series of magnetic bearings. The completely automated operations are heavily monitored, as a change in the position of the core can result in million-dollar repairs – and about $5.2 million of deferred revenue per breakdown. To make matters worse, the levels of mercury in the compressor’s components make repairs dangerous.

With potential production losses reaching as high as $14 million a week, a predictive maintenance solution had a very attractive ROI for this customer. SAS helped the operator harness the six million records per second generated by sensors that monitor the compression train and create exception-based surveillance: A complete picture of past events is constantly compared with a current-event view to monitor the status of the sensors and anticipate equipment malfunctions. Predictive analytics allow the operator to assess the best way to maintain equipment, schedule preventative maintenance before a breakdown occurs – and increase the productivity of this very valuable asset. Analytics have cut the project’s repair times by two-thirds and saved the operator tens of millions of dollars per year.

JWN’s second analytic favorite, production asset optimization, has many potential iterations for oil and gas companies. One is employing large volumes of sensor data to increase the production capacity of steam-assisted gravity drainage (SAGD). The critical factor here is the delicate dance between the water plant that produces steam on the surface and hundreds of pairs of parallel subsurface wellbores that pump steam into the reservoir and drain the bitumen out.  Since producing steam is the highest-ticket item in the process, producing more oil with less steam adds value per barrel.

Many other elements of this complex process add to the challenge of increasing efficiency for SAGD, among them subcool temperature, water cut management, steam distribution and production targets. SAS has found that applying analytics to the data collected from each step of the process allows operators to evaluate the entire facility, the health of individual well pairs and how a change to one pair will impact the operation of others. Not only does this enable faster and better production projections, it helps operators avoid production losses by anticipating problems. Optimizing production on a 100-well project can generate an additional 1.4 million barrels per year, adding more than $20 million to annual cash flow.

As attractive as these case studies are, they are of little value if oil and gas executives hesitate to employ them due to human resource or budget constraints. So back to our original question: What if oil and gas executives could road-test the power of analytics before they commit their internal resources?

One way execs can gain confidence in the power of the technology is through an analytic outsourcing arrangement. In this lower-cost engagement, clients provide the necessary data to determine a specific analytic need, such as a weekly or monthly production report, and SAS brings to bear its analytic insight and its technological capabilities to generate results. It’s one new way customers are uncovering efficiency-generating, cost-saving business insights during lean times for the industry.

To find out more about this and other analytics approaches that support the oil and gas industry, visit www.sas.com/oilgas. Ian Jones is Senior Strategist for SAS' energy risk management practice. Prior to joining SAS in 2009, he served as editor of the energy industry trade journal The Risk Desk.