Sensor laden drilling operations are going increasingly hi-tech.
In the shale oil industry today, tiny sensors are being attached to production gear to harvest data on right about everything: from pumping pressure, rotational speed of drill bits, heat generated by drilling activity, almost every conceivable variable in the drilling operation is being captured.
This sensor-laden drilling efforts is leading big oil companies to big data, with many oil companies envisioning billions of dollars in savings over time by better managing supplies, avoiding outages, and identifying safety hazards.
Although the oil industry has since long used sophisticated methods to locate oil and gas deposits, it is only recently that they have started using the potential of big data for greater operating efficiencies.
As per ConocoPhillips, the sensors in its well fields help it significantly reduce the time it takes to drill new wells in Eagle Ford shale basin of South Texas.
As per Matt Fox, ConocoPhillips’ executive vice president for strategy, exploration and technology, thanks to the data from the sensors, the program of the drills automatically adjusts the weight placed on a drill bit and its speed, accelerating the extraction of oil.
Although this is just one application, but if it’s applied to the 3,000+ 000 wells ConocoPhillips hopes to drill in the Texas basin, the savings is likely to be in “billions and billions of dollars” said Fox in an interview.
He went on to add, “We started using data analytics in our Eagle Ford business. And everywhere we look there are applications for this.”
The complexity and cost of such system vary widely.
ConocoPhillips uses a mix of customised and readily available programs along with data repositories, it also uses Houston-based Tibco Software’s Spotfire for data visualization to analyze the information from wells.
In the days when oil used to trade at $100 a barrel, for the majority of oil firms, data analysis was an “afterthought” said Binu Mathew, who oversees digital products at GE Oil & Gas.
With oil prices hovering at $43 a barrel “the efficiency aspect is far, far more important,” said Mathew.
As per the results of a survey done by Ernst & Young in 2016, 68% of 75 large oil and gas companies had sunk in at least $100 million each, in data analytics during in the last two years.
According to companies who buy and sell data, effectively mining all of these data could eventually lead to supplanting workers with artificial intelligence and machine learning systems.
“The driller is now able to focus his attention on the well – and the performance and safety of his crews – as opposed to the manual manipulation of controls,” said Duane Cuku, vice president of sales for rig technology at Precision Drilling Corp.
As per Abhishek Gaurav, a petroleum engineer at Texas-based Standard Oil, he uses big-data analytics to help his company choose which properties to explore.
Using Spotfire, Standard applies a combination of data science and petroleum engineering to rank asking prices for land based on a variety of completion, production and geological variables, including the amount of sand that likely would be required to complete a well in a given formation.
This technique alone has helped diminish the time required for evaluating land parcels from weeks to hours and have resulted in better decision making, said Gaurav.
“We found value in properties when many other teams did not,” said Gaurav.
“There is a huge amount of data prep, data sanitization and data extraction needed for big data to be totally disruptive,” said Kate Richard, CEO of Warwick Energy, a private equity investor.
As per her projection, a major payoff from the technology is still five or ten years away.
Warwick is actively preparing for that payoff by hiring people from tech hubs in California.
“They all have computer programming and data science backgrounds,” said Kate.