As shale oil investors seek higher returns, E&P companies are looking for quick, efficient means of reducing costs. With U.S. shale production on the rise, digitalization and automation are taking control of the oilfields and developments in artificial intelligence (“AI”) are helping companies increase drilling, completion and production rates with lower cost and less risk.
Several factors are driving today’s rapid implementation of AI technology, including the pressure to increase production efficiency and reduce costs, an increased need for automation to meet mass U.S. shale E&P needs, a significant increase in venture capital investments and the rise in big data technology calling for enhanced data analysis capabilities.
Midstream AI Highest Area of Growth
Artificial intelligence aims to cut costs by boosting operational efficiency and reducing expensive downtime through predictive maintenance, offering a variety of enhanced functions for all facets of the industry, including:
- Field Services
- Machine Inspection
- Predictive Maintenance
- Quality Control
- Project Planning
Midstream AI is the current area of highest growth since U.S. shale expansion necessitates rapid pipeline, terminal, rail and tanker development. Midstream AI is used to gather transportation data and allows workers to control and maintain projects remotely, helping to resolve pressure fluctuations, characterize reservoirs and interpret well logs, among many other functions.
Currently, the largest market for AI technology is in U.S. and Canadian oilfields, followed by European and the Asia Pacific markets. Meanwhile, Africa and the Middle East boast the fastest growing AI markets, where newly discovered Red Sea reserves have increased E&P demands and investments in AI application start-ups are on the rise.
Speaking at the Abu Dhabi International Petroleum Exhibition Conference (“ADIPEC”) in mid-November, Microsoft's MENA Oil and Gas Director for the Middle East and Africa, Omar Saleh, said, “AI will have the greatest technological impact on the oil and gas industry over the coming years.”
Quantico Reveals AI Cuts Costs Up to 70% Per $200K Job
CEO and founder of Quantico Energy, Barry Zhang, spoke about the vast applications of AI in oil and gas at last month’s Hart Energy DUG Eagle Ford Conference & Exhibition, explaining how significantly AI application is affecting the industry.
In a Quantico case study, Zhang reported that, when compared to traditional inversion data, higher-resolution, AI-obtained seismic data on the Eagle Ford exposed greater porosity – cutting a potential $100,000 project down by 50%.
In a separate case study analyzing data from Schlumberger Ltd., Zhang reported that AI technology revealed potential cuts of up to 70% per $150,000 to $200,000 project.
Zhang used EOG Resources Inc. as an illustration of successful AI implementation, explaining that EOG currently uses more than 65 proprietary applications. EOG workers can control every asset from mobile apps that transmit real-time data 24/7. AI has allowed EOG to pinpoint lateral targets, use petrophysical models to geosteer drill bits, and apply geologic setting to enhance expansion designs.
Cybersecurity Risk and Expense Still Pose Challenges
Several challenges still exist around the development and implementation of AI in oil and gas. Most concerns revolve around the potential for cybersecurity breaches and unauthorized data release. Regulatory guidelines are still lacking for AI application in the oil and gas industry. In addition, the cost of installing AI software, hardware and services will remain relatively high until technologies become more mainstream.
In discussing the challenges of oil and gas AI, Quantico Energy’s Barry Zhang mentioned that several factors have kept AI from taking off faster in E&P, particularly in the subsurface arena. “Most oil and gas companies do not have the big data that’s required for successful big data implementation,” Zhang said. “One of the big things that I always emphasize to operators is to not pursue AI projects that are big moon shots… Pursue, at least in the beginning, things that have tangible ways to save you money.”
“Then you get the handle on what the right applications are, and then you go bigger from there. If you start the other way, you lose control of the cost.”
Software is the currently the oil and gas industry’s most used AI application, with most hardware and services applications still in development. Some major players in today’s oil and gas AI development market include IBM, Google, Intel, Microsoft, Shell, Oracle, Cisco, Accenture, Hortonworks, Sentient Technologies, Infosys, and General Vision.