The Big Data Future Of US Oil

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Originally Published on the ECOreport

Lux Research just released a report stating that as prices keep falling, “Big Oil” is increasingly using smarter sensors and “Big Data” to manage risks, cut costs by increasing efficiency, and increase revenues. (Access it here) I recently did a Q&A with Colleen Kennedy, Lux Research Analyst and co-author of the report, about her report and the big data future of US oil.

Screen-Shot-2015-09-15-at-9.21.42-AM-1038x576The Role Software Programs Play

RH: Tell me more about the role software programs play in smarter surveys. Do you have a metric/opinion for how much that could reduce cost?

IMG_3033CK: Good examples of analyzing data for smarter surveys are companies like Ocean Floor Geophysics and Waveseis- which have invented proprietary algorithms that increase accuracy of seismic data. For example, Waveseis focuses on mapping sub-salt structures. If the mapping is more precise, there is less of a chance that unexpected geological structures will waylay drilling operations. Similarly, early kick detection software can reduce the risk of a technician overlooking small change in downhole conditions. If an operator uses a new technique, such as Waveseis’ Revolutionary Imaging Technology (RIT), they might identify a slight dip or anomaly in the formation before drilling that could have cost $250,000 in Non-Productive-Time. Or, if it identified a better sweet spot to target, the well could produce 15-20% more than anticipated- those numbers could be huge.

RH: You cited Halliburton as saying it could save $500,000 a hole, but what does that mean in terms of the total cost of that hole? (10%?; 50%?)

CK: This number came from a specific case study released by Halliburton, where a new tool was used in underbalanced pressure conditions to perforate 12,000 ft lateral. Realistically, the total cost of this completion project could have been $10-20 million total. The point is that hitting target zones with more accuracy using techniques such as geosteering- especially in complex formations- can easily result in big savings, especially when that data is then translated to several wells or laterals.

RH: You mentioned software crunching 2 months of data in 10 minutes, what does that mean in terms in terms of a company’s overall cost and efficiency?

CK: In this particular quote- they are discussing predictive failure maintenance. If they can identify and correct a failure pattern before say 20 more gas steam turbines fail and need to be replaced- I can imagine the savings being immense. I don’t know actual costs, but I would anticipate hundreds of thousands of dollars, maybe even millions, saved in repairs, replacements, and downtime.


Increased Efficiency

RH:  In what other areas does this increased efficiency come into play?

CK: We cover a lot of ways big data can be used to increase efficiency in this report. Increasing and improving data transmission speeds from downhole, a focus of start-ups Cold Bore Technology and XACT Telemetry, is one major trend. Since the report has been published, Lux has covered even more technologies that increase efficiency in the oil and gas space. For example, IntelligentDots is developing a new method of deploying seismic surveys with solar powered, network connected nodes. Another company we recently spoke with, SigmaFlow, provides software that re-assigns specific tasks when one rig has a problem and operations for the next six months need to be adjusted.

RH: As a result of the current collapse of oil prices, some companies are no longer finding it feasible to continue. Could software & smarter technology reverse this?

CK: Software and smarter technology will probably not be able to reverse this for companies struggling currently, simply because the cost of initial implication may be too high and the savings may not be immediate enough. An interesting topic I recently discussed with the CEO of OAG Analytics, is that companies with better data analytics in place currently or companies who are able to implement it soon enough, may be better positioned to define their assets and reserves when “debtors come calling.”


A Lower Carbon Footprint

RH: Increased efficiency would also translate into a lower carbon footprint. Do you have any metrics for this?

CK: This would be very hard to quantify directly. A professor from USC spoke to us about organizing workers like Uber drivers, which reminded me of when the roughnecks used to tell me they carpooled to “do their part for the environment.” Streamlining transportation of workers is just one way of the many ways Big Data can absolutely be used to lower the carbon footprint. Similarly, using big data to analyze materials transportation to drill sites could be a low-hanging fruit for reducing carbon footprint.

Anecdote: One time, while I was working as a geologist on an oil exploration rig in central California, I was given a Prius rental car to drive to work. The irony of driving 80+ miles a day, most of which was off road, in a “green” vehicle to drill for oil was lost on no one.

RH:  Richard Stover, PhD, and the Center for Biological Diversity counted nearly 8,000 significant oil spills in the US between 1986 and 2014, in records of the pipeline safety administration. Do you have any metric for estimating how many of these could be prevented through more advanced software and smart technology?

CK: Oil spills are often the result of several small errors, which would make defining that metric difficult but not impossible. There will definitely be an influx in technology into pipeline management, focusing on advanced sensors, drones and other remote monitoring systems.

RH: One of the criticisms of the response to a recent oil spill at Santa Barbara, CA, was the length of time that transpired between the pipe rupture and turning the flow of oil off. Do we have software that can reduce this response time to seconds rather than minutes or hours?

CK: According to this article, the company had sensors to detect anomalies and automatically shut down the pipeline. It appears that the protocol was not followed by employees. I spoke with one offshore technology developer who is designing a system to automatically elevate issues and alert upper management to deter complacency that can lead to catastrophes.

RH: To what extent can software compensate for human error?

CK: Of course, there will always be a limit. The digital oilfield isn’t about completely replacing human decisions with algorithms or choosing not to deploy automated systems because they might fail. Going forward, companies should focus on finding harmony between the two and using that harmony to their advantage.


Tar Sands Emissions

RH:  This is off topic, but I am aware of two companies that claim they can clean up tar sands emissions. This raises the question of whether we could see a much cleaner fossil fuel sector in the future. Do you want to make any comment about this?

CK: A lot of companies lay claim to reducing overall carbon emissions. If you could send me the names, I’d be happy to see how exactly their technology would make an impact. According to Bloomberg, Canadian tar sands emissions are only .1% of global greenhouse emissions.

RH:  That makes Canada’s oil sands emissions sound trivial. According to the Pembina institute, 7% of Canada’s emissions came from the oil sands in 2010 and this is the nation’s fastest growing source of emissions. ( On page 18 of Environment Canada’s report “Canada’s Emissions Trends 2014” (, it says, “Emissions from oil and gas are projected to increase by 28% (from 159 Mt to 204 Mt) over the 2005 to 2020 time frame. This is due mainly to increases in oil sands production.” The chart below, taken from page iii of that report, shows that Canada will not make its commitment under the Copenhagen Accord even if the government puts the “current measures”into effect.


RH: As regards the two companies I mentioned claiming they can clean up tar sands emissions, a Canadian company named Mobius Technologies has a dry processing system which they say significantly reduces emissions, but as far as I know they have yet to reach the stage of being independently tested. A US firm called MCW Energy was founded by former Exxon President of the Arabian Gulf region, Dr. R. Gerald Bailey. It claims to have an environmentally friendly process which is “producing 250 barrels a day right now at a very reasonable production cost of $30 per barrel” (

CK: MCW’s technology certainly looks compelling, but as Dr.Bailey conveys in his interview, comparing Utah’s oil sands to Canada’s is comparing apples to oranges and they aren’t extracted using the same methods, thus targeting overall emissions is different.

Photo Credits: Graphic of smart technology taken from the report; Colleen Kennedy, Lux Research Analyst and co-author of the report “Big Data in Oil and Gas: The Intelligent Oilfield”; Three charts taken from the report; chart taken from Environment Canada’s report “Canada’s Emissions Trends 2014“)

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Roy L Hales

is the President of Cortes Community Radio , CKTZ 89.5 FM, where he has hosted a half hour program since 2014, and editor of the Cortes Currents (formerly the ECOreport), a website dedicated to exploring how our lifestyle choices and technologies affect the West Coast of British Columbia. He is a research junkie who has written over 2,000 articles since he was first published in 1982. Roy lives on Cortes Island, BC, Canada.

Roy L Hales has 441 posts and counting. See all posts by Roy L Hales

6 thoughts on “The Big Data Future Of US Oil

  • The best way to reduce emission from the FF sector is simple: use less!

    • Correct. Efficiency is the lowest hanging fruit.

      If it’s time to buy a different car everyone should try to get themselves into a new/used EV/PHEV and make a massive cut in their personal oil use. Time to do to the oil companies what we’ve started doing to the coal companies.

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