The Big Challenges of Big Data for Oil, Gas

Sperrazza sees production field logistics as the one area that can benefit the most from the industry’s success in addressing Big Data. Companies can maximize the revenue they get from a field by ensuring that enough trucks are made available to haul production from a site before a storage facility fills up. When a facility fills to capacity, it shuts down, which means that production from that facility is deferred production, or deferred revenue. For this reason, using Big Data to solve logistical problems could create a huge near-term benefit for a company.

The trend of analyzing Big Data for decision-making and forecasting has prompted discussions of introducing automated controls to alert operators to problems. Oil and gas companies are now seeking systems that might alert them to an event that might happen in four hours or six hours.

“Once you’ve got analytics running and predictive environments, the question becomes, ‘how do you get the system to tell you, hey you might run into this problem?’ How do you build-in automated controls so the system can rectify itself?”

This automation will be critical to optimizing operations in a safe, efficient manner, particularly in ultra-deepwater exploration. Given the expense of rig day rates, as well as the engineering requirements and need to address safety and efficiency in operations, companies are doing “whatever they can” to prevent downtime, Sperrazza noted.

“If they can drill 10 feet faster per minute, that drives profitability and makes the company more efficient and competitive.”

 “We’re always exploring for oil at the edge of data, and new drilling environments and reservoirs are typically outside the range,” Sperrazza noted.

Oil and gas companies also must track which well leases are profitable, which ones can expire, and what its contractual drilling obligations are, said Charles Karren of Oracle in an interview with Rigzone. Companies are tracking structured data, such as production data from sensors, and unstructured data, which can be emails or drilling reports filed in a cabinet. Oil and gas companies must also deal with a great number of data coming from sources such as vendors, and tracking service crews, truck traffic, equipment and hydraulic fracturing water usage.