The Oil and Gas industry, especially in the upstream Exploration and Production (EP) sector, has been enjoying a renewed vigour in the past few years. I have kept in touch with the developments of the EP side because I always have a soft spot for the industry. I have engaged in infrastructure and solutions in the petrotechnical side in my days at Sun Microsystems back in the late 90s. The engagements with EP intensified in my first stint at NetApp, wearing the regional Oil & Gas consulting engineer here in South Asia for almost 6 years. Then, with Interica in 2014, I was dealing with subsurface data and seismic interpretation technology. EP is certainly an exciting sector to cover because there are so much technical work involved and the technologies, especially the non-IT, are breath taking.
I have been an annual registrant to the Digital Energy Journal events since 2013, except last year, and I have always enjoyed their newsletter. This week I attended Digital Energy 2-day conference again, and I was taken in by the exciting times in EP. Here are a few of my views and trends observation in this data renaissance.
The never-ending story of messy data management and files
The perennial problem since the dawn of data in Oil & Gas has never really went away. Over the decades, we get the same old challenges
- Duplicate files – multiple versions of the same file – related to data relevancy
- Multiple locations of files – The same file exist in local drive, USB, Sharepoint, NAS and personal home computer
- Multiple versions of files – poor understanding of the data relevancy
- Different naming convention of the same files
- Missing files – files exist on records but are missing
- Zombie files – files exist but not related to any projects
But newer technology with AI (Artificial Intelligence) data management capabilities are coming into the picture. Data management with smart taxonomy cataloguing is changing the landscape, and with more advanced file analytics has the potential to reduce the data management and file lifecycle challenges in EP.
DevOps versus Grey Crew
The industry has been going through massive changes in the past 5-6 years. The seasoned G&G engineers are getting grey hair and often felt challenges with the younger upstarts, the Millenials. The grey crew has earned their stripes through blood and sweat, and seasoned with overcoming some of the most difficult problems in the industry. The G&G (Geological & Geophysical) engineer, through experience and wisdom, could “sniff out” where oil and gas can be found are being told that the younger could do even better. The young data scientist I spoke to at the event could not spell out what “G&G” meant.
At the event, we hear of ExxonMobil, one of the super majors, going through a mini DevOps revolution in subsurface data management development. Agile, scrums, sprints are all alien words to the seasoned subsurface project leader but the process of injecting the “fail often, fail fast” mentality has already begun. I asked the question of the cultural challenges in implementing DevOps into EP, in an industry which prides itself of being the top of all industries in the world, but the answer I was expecting was side stepped by the ExxonMobil team.
Despite this new “old versus new” banter, the fact remains that data has become the eagle eye to find where the world’s most valuable resource (before data) is found. And it is very, very costly to do oil and gas exploration. Finding it accurately, and finding it fast mean untold profit to the oil companies.
Cloud and beyond
The role of data has never changed in Oil & Gas, and even more so in EP. The thing which changing the game is the digitalization of data in the oil fields. This is the core of the data renaissance in EP, and driving a feverish push towards deep seismic processing, interpretation and data analytics technology in the clouds.
For a while, cloud in EP was frowned upon. But not anymore, as the acceptance of huge computing power and resources of the public cloud infrastructure even with AWS and Microsoft Azure are growing. At the event, Halliburton shared their DecisionSpace 365, cloud-native EP software suite which includes Scalable Earth Modeling and Full-Scale Asset Simulation.
Expect more cloud-based EP applications from other oil field application vendors soon, as applications involving machine learning, deep data analytics and AI to take root in this lucrative EP segment of the industry.
Edging toward the Edge
From the cloud, breeds the Edge. While this technology segment is still nascent, I believe this will have the biggest impact on the Oil & Gas industry. The engineering side of EP measures everything, and Edge Computing with time-series near real-time analysis with sensors, and endpoint devices would bring forth an explosion of data analytics.
Geologix was one of the speakers at the event, shared a use case using both temporal and spatial data analytics on well logs which I found fascinating. This use case was a great example of Edge analytics revealing real-time data a well in a block where the drill bits were taking in too much sand during drillng and thus causing poor yield at the particular oil field.
I am seeing EP taking on new generation of technologies with gusto. It will get better, faster, cheaper and safer. The sail of this data renaissance is embracing the great tailwinds and in time, in the near future, we will see even better outcomes for Oil & Gas in the decades to come.