SLB: Disrupting the Traditional Energy Industry Through AI Drilling Innovations
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SLB: Disrupting the Traditional Energy Industry Through AI Drilling Innovations

by Zsolt Katona and Thomas Lee


SLB (formerly Schlumberger), the world’s largest oilfield services company, developed autonomous directional drilling using cloud computing and machine learning models to optimize drilling. Artificial intelligence can help reach lucrative oil and gas reserves faster - technological advances SLB said will deliver more efficient and sustainable operations. Yet, applying AI to the energy industry comes with challenges. Who should own the valuable drilling data - SLB as the oil field services provider, clients, or 'the world' because data about the earth benefits the public good? How much should SLB invest in traditional drilling methods versus unproven AI-driven methods? Can SLB recoup its investments?

Learning Objectives

1) How to use new AI/ML techniques in a traditional industry.
2) The importance of data access/ownership for machine learning applications.
3) The difficulty of finding the right business model for AI-driven innovation.
4) B2B Marketing: how to convince your customers to adopt new technology

Details

Pub Date: October 1, 2023

Discipline: Innovation

Artificial Intelligence, Machine based Learning, Databases, Data Analysis, Process Innovation, Sustainability, Marketing Strategy

Product #: B6041-PDF-ENG

Industry: Energy & Natural Resources

Geography: United States, Texas, Saudi Arabia

Length: 10 page(s)

Berkeley Haas Case Series
Berkeley Haas Case Series The Berkeley Haas Case Series is a collection of business case studies written by faculty members at the Haas School of Business. Cases are conceived, developed, written, and published throughout the year, on subjects ranging from entrepreneurship and strategy to finance and marketing. Each case includes a teaching note for use in the classroom.
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The aim of the Berkeley Haas Case Series is to incite business innovation by clarifying disruptive trends and questioning the status quo.

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