Accelerating business value with Generative AI in INNOVATION FACTORI

We are fortunate to live in a world where technology evolves at an incredible pace. The latest breakthrough is in Generative AI, presenting us with previously unimaginable ways to tackle the complex challenges of today's world.

My mission

In my current role within SLB, my mission revolves around solving complex customer challenges by creating innovative solutions using AI for the energy industry. Coming from a business and operations background, rather than a purely technical one, I ensure that our innovations go further than solving challenges. They must deliver tangible business value that scales within our customers' organizations.

This includes interoperability with existing and future domain systems and data formats and ensuring that these tools can be leveraged by anyone in the customer’s organization. Equally important is safeguarding the integrity and privacy of their data and ensuring that we apply new technology in a legal, explainable, and ethically responsible way. My mission, therefore, is to foster a culture of innovation in close collaboration with our customers that bridges the gap between complex AI technologies and practical, reliable, secure, and valuable solutions tailored for the energy sector.

Traditional AI vs Generative AI
Generative AI distinguishes itself significantly from traditional AI. Putting it simply, traditional AI allows us to analyze data and provide insights, whereas Generative AI uses data to create new data or insights. Traditional AI requires specific training for each task it performs; however, Generative AI operates on foundational models that learn in an unsupervised manner from larger datasets.

Generative AI accelerates innovation and, consequently, business impact in several ways: it aids in creativity and idea exploration, can help sift through massive datasets and find hidden patterns and insights, lowers barriers to creation and rapid prototyping, and enables an unprecedented degree of tailoring to user specific needs and integration in their daily lives.

Transformative impact on project execution

For an example of the impact Generative AI can have on the speed and quality of results, I reflect on my time overseeing large integrated projects. A key component of successful operations was the Project Readiness Assessment. This process involved evaluating extensive information, from historic daily drilling reports (DDR) to HSE risk assessments and best operational practices. Previously, considerable time was spent just gathering and consolidating this information for analysis by domain and function experts.

Discover INNOVATION FACTORI

Today, thanks to advancements in Generative AI, we can adapt the way we process information from numerous DDRs in various formats much more quickly through what is termed 'Prompts'. For instance, asking, "Show me the well design for well X?" or "What are the NPT risks in Section Y based on similar wells?" significantly speeds up data retrieval and ensures that more information is considered.

For drilling risk analysis for example, we achieved dramatic improvement in speed in the order of months to hours, and improvement in the quality, e.g. how many risks uncovered. This enables end users to much faster adapt their queries and extract more insights without having to rely on building heavy queries in traditional BI tools for example.

We can take the information retrieval to the next step by coupling this data with our traditional engines, simulators and tools which allows for validation and building workflows with unprecedented levels of autonomy.

Domain expertise remains vital
The quality of the answers is directly influenced by the quality of the questions posed, the way the underlying retrieval system is designed, how the foundational models are trained and fine-tuned, guardrails applied etc. highlighting the importance of domain expertise in generating relevant outputs and measuring the accuracy of results.

Innovation at INNOVATION FACTORI

At INNOVATION FACTORI, the organization I lead, we are developing use cases for Generative AI in energy. Our projects range from data structuring and generative planning to insights generation and intelligent operations. These initiatives underscore our commitment to leveraging cutting-edge technology to solve industry-wide challenges, enhancing efficiency, and safety across operations.

Looking forward, the potential of Generative AI to revolutionize the energy sector is immense. As we continue to explore and expand its applications, our focus remains on developing solutions that meet today's needs and unlock the possibilities of tomorrow. Generative AI stands to reshape how we approach everything from operational efficiency to environmental sustainability, paving the way for a more innovative, data-driven future.

Sustainable change for the energy industry

The journey with Generative AI is just beginning, and its potential to impact the industry and the world at large is as vast as our imagination allows. As we harness its power, we are transforming the work we do in SLB, and setting the stage for a seismic shift across the entire energy industry. We are committed to leading this charge, ensuring that our innovations drive not only business value but also broader positive and sustainable changes across the globe.

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