3 ways AI advances health, safety, and sustainability | SLB

3 ways AI advances health, safety, and sustainability in the energy industry

Kristi Vilay Arijit Paul Staffan Eriksson
by  Kristi Vilay Arijit Paul and  Staffan Eriksson
While still in its nascency (depending on who you ask), artificial intelligence is already making positive contributions to the way our industry operates. From protecting our people and planet to maintaining our products and lowering our costs, this life-altering tech is just beginning to show its potential for helping us reach our sustainability goals now and in the future.

Artificial intelligence (AI) is rapidly gaining traction across the energy industry as companies realize the benefits of using it for real-time insights that make operations safer, more sustainable, and more efficient.

Our industry is no different.

Energy production is safer today than ever before, and it’s partially due to the proper implementation of AI. This continuously evolving tech is playing an important role in our own industry’s evolution by:

  • Providing us with a deeper understanding of the subsurface
  • Supporting real-time intelligence and data processing
  • Optimizing decisions at speed and scale
  • Enabling operations to be completed remotely and, in some cases, autonomously
  • And many more.

To realize AI's full potential, the energy industry must quickly develop robust data infrastructures, governance, and processes that will enable this tech to scale. The key is to act now, so that we continue to make energy production even safer for our teams and the planet, all while driving operational efficiency throughout the industry.

While the energy industry is still at the beginning of its AI journey, there are three areas where it is significantly advancing safety and sustainability in operations today.

AI reduces time in the red zone

Traditionally, many aspects of energy production have relied on team members completing manual operations in the field. With modern tech, we are beginning to complete many of the most hazardous tasks remotely, and increasingly, autonomously. Operators can now select from entire suites of autonomous solutions. There are even some for directional drilling that leverage cloud-based software and connected intelligent systems to automate drilling processes.

By harnessing wide-ranging surface and subsurface data in the cloud, connected drilling devices can use real-time downhole data to optimize drilling trajectory. This is not dissimilar to the instant processing of sensor inputs in self-driving cars—the ones that identify hazards in time to brake or change lanes. These tools and capabilities are enabling remarkable improvements in the efficiency and consistency of exploration and production, all while minimizing environmental impact and human intervention.

AI identifies hazards and mitigates risks

Using a combination of video intelligence and AI models, you can now assess real-time feeds from on-site cameras to enhance safety for both our team members and the environment. How? Well, for example, you can begin automatically processing feeds from cameras on rigs, plants, and vehicles to not only detect if a safety-critical event is occurring, but also instantly notify your team so they can address the situation before an incident occurs. You can also store that video in the cloud to (a) use it for future learning and (b) measure safety performance more accurately over time. This risk mitigation capability has the potential to save lives as well as reduce maintenance and service costs, especially as the tech expands across more and more of our industry's operations

AI helps reduce emissions

One of the most urgent priorities we face as a planet is rapidly reducing emissions in support of a lower-carbon future. In the energy industry, eliminating methane emissions is one of the most immediate solutions, as nearly half of all emissions from oil and gas operations are attributed to methane. Detecting and measuring methane leaks has traditionally been challenging, but not anymore. Now, we have things like methane lidar (laser imaging, detection, and ranging) cameras. These cameras, together with AI-enhanced processing, allow you to create a picture that clearly identifies the beginning of the methane plume, thereby showing the emission source regardless of temperature, sunlight, and other gases, including water vapor. Under favorable conditions, the camera can detect even the smallest methane emissions and alert your teams when leaks begin—enabling them to complete repairs quickly and (you guessed it) avoid emissions.

While these examples demonstrate that AI is already driving impact throughout the industry today, the long-term potential is both profound and transformative. In our opinion, the AI revolution in energy will unfold along two interconnected paths. First, there will be growing adoption of the AI solutions that are available today, a few of which we have just described. Second, new forms of AI will emerge with the potential to have an even greater influence. One example is the potential to autonomously operate, monitor, and optimize equipment in the most remote locations, including offshore and subsurface.

Throughout our careers, there have been a few moments of rapid progress that changed the industry forever. We are living in one today. By leaning into AI's transformative capabilities, we can continue to make energy production safer and more efficient, paving the path toward a more sustainable future.


Kristi Vilay

Head of Products – Edge

Kristi leads the edge AI and IoT initiatives at SLB, leveraging her extensive 20-year background in the oil and gas industry to drive innovation in digital production. Her work centers on developing solutions that enhance intelligent operations, encompassing everything from integrating connected assets to implementing autonomous workflows. This focus helps improve safety, efficiency, and sustainability of operations within the sector.

Arijit Paul

Director of HSE Practices

With 25 years of industry experience, Arijit’s expertise spans multiple businesses and functions, from Wireline and Reservoir Performance to Supply Chain and Integrated Project Management. His various leadership roles spanned field operations, line management, service quality, business development, procurement and sourcing, integrated services, operations system and integrity, asset/CAPEX management and global account management. These have taken him across the US, Canada, Central Asia/ Caspian, India and the UK.

Staffan Eriksson

Technical Marketing Manager – Data & AI

Based in London, Staffan’s role involves developing messaging and contributing to the strategic direction of products that bridge the domains of Data and AI. His SLB career spans 17 years, starting with roles in seismic sensor engineering and downhole drilling tool firmware design. He has managed various software projects in the drilling domain and also served as the manager of the SLB Software Center in Abingdon, UK, which specializes in reservoir simulation and field development planning.