How Artificial Intelligence Will Benefit Drilling

In drilling, more often than not, automation and optimization are independently addressed. Artificial intelligence can be the bridge between the two.

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Technological innovation is a critical driver of economic growth in the oil and gas industry. One of the buzzwords in the media today is artificial intelligence, or AI. Put simply, the use of AI allows for drastic improvements in drilling with less physical input from drillers and without drillers having to explain how the machine accomplished the task it is given. The end goal is to have combined systems that know how to perform a function on their own.

More often than not, automation and optimization are independently addressed; AI is the bridge between the two. It will drastically change/disrupt the way the industry drills wells in the future, and, as an industry, we need to embrace the technology now and start changing previous ways of thinking.

Intelligent drilling automation is going to be a game changer and the new way to drill smarter producing wellbores. One essential improvement that will take immediate effect is on decision making at the rigsite. Because of the number of hands on the jar at the rigsite, no one wants to be the key decision maker. With a controlled input/output, AI systems will take that task from service companies and rig personnel and make optimized analytical decisions, thereby enabling stakeholders to achieve significant gains.

Specific Benefits of AI

With a good technology roadmap strategy for innovation, AI can affect the drilling space positively. With predictive analysis, the industry will be able to automate the drilling process to mitigate some drilling dysfunctions such as differential sticking, stuck pipe, excessive downhole vibration, managed-pressure drilling, hole cleaning, equivalent circulating density, and pressure transients. These downhole phenomena can be addressed by an input of good data curated from wellsite records, including borehole assemblies and run data, analyzed offset data, survey data, geology data, and the well plan. AI can help address these issues by using an analyzing downhole data acquisition system (sensor data). Potential anomalies can be flagged promptly using reliable indicators. The end result of an integrated automated platform in drilling is optimal control of the operation parameters, which directly affect the rate of penetration. Another key benefit of AI-infused drilling is safety; fewer people will be involved in the process, and the skill set requirement will be increased.

Numerous drilling operations can be changed or improved using computational intelligence and mathematical optimization, including

  • Reduced drillpipe wear
  • Bit direction guidance
  • Directional drilling decision automation
  • Measurement while drilling
  • Managed-pressure drilling
  • Mud programs
  • Casing while drilling
  • Rig operations processes
  • Increasing production with targeted precision
  • Decreasing drilling time
  • Wellsite geology automated formation top correlation

The benefits that AI can provide include

  • Detection of cyberthreats and rig control system security lapses
  • Prescriptive maintenance
  • Open window for performance optimization—Offset data analyzed from sensors will be used to make real-time, closed-looped predictions that will help intelligent node systems react and resolve current drilling dysfunctions. This form of transfer learning can be deployed on a fleet operating in a given shale area.
  • Better safety—This is a key issue in our industry, and the ability to change the status quo and take people off the drilling platforms will be a win for all. Drillers will be able to monitor multiple wells from remote locations while focusing on monitoring drilling performance/challenges, which will cut the cost of drilling significantly. AI will help curb the risk and exposure to dangerous working conditions for many employees.
  • More collaboration among service companies—With an open platform, a correlating increase will occur in software innovation platforms for performance-enhancement applications, which also promotes positive problem-solving competition.
  • Enable the industry to change its current mindset and promote a culture of innovation

Challenges and Myths

A key challenge to adopting AI will be the perceived effect on jobs. AI will take away key roles that humans currently play in drilling, which will open room for more skilled labor in the industry. This will disrupt the current setup, similar to how spreadsheets replaced the previous system of ledger forms filled out by hand. This did not cause a loss of jobs but actually opened up more jobs for accountants to focus on models and computations. The same could happen with adoption of AI.

Intelligent drilling automation will not change the way the industry drills wells but rather will take current drilling practices and improve real-time decision making. According to an article published by Accenture Strategy, the best practical method for AI implementation is launching the foundation of the current setup, standardizing controls, using sensor-based integrated analytical feedback, and then implementing the judgment-driven models.

AI will aid in the execution of both manual and digital back-end processes, eliminating repetitive tasks such as pipe connection as well as documentation of daily functions such as mud reports, blowout preventer checks, and equipment maintenance reports.


AI will optimize and automate the drilling process to make it more efficient. The future of AI in drilling is the introduction of smart control systems/platforms/software that companies can plug in and use to control the drilling process on-site and remotely. These plugins would have inputs from offset information gathered with the integration of machine learning and human influence, combined to react to changes that occur within microseconds in drilling.

Drilling engineers will be able to focus their time on implementing innovative technologies that will enable the drilling of a smooth wellbore, which will result in an optimized payzone. We should start the conversation on how we can prepare as an industry for this disruption, which promises to lead to better wellbore quality and increase production.

Nii Ahele Nunoo, SPE, is an asset manager at National Oilwell Varco. His oilfield career started in 2012, designing and qualifying electronics on projects for high-shock, high-pressure, and high-temperature downhole drilling tool applications. Nunoo’s focus and expertise is downhole drilling tools used for closed-loop automation. He holds a BS degree in electronic engineering from Minnesota State University and is currently pursuing an MBA from Duke University with a concentration in energy finance. Nunoo is active in the SPE Gulf Coast Section and one of the founders of the section’s Innovate Committee. He has coauthored five publications in peer-reviewed journals.