Digital Transformation

Five key themes to AI's success including standardization, automation, integration, scalability, and continuous improvement can provide a clear roadmap for effective AI deployment, addressing challenges and driving sustainability across the subsurface energy sector.

Tune in 28 October for a discussion with SPE Technical Directors about the future of data science for professionals in the energy sector.

Prajakta Kulkarni, SPE, has spearheaded the development of a global digital platform to optimize pricing, strategy, and sales in the industry. With a background in petroleum engineering, she identified a digital gap in the industry, leading her to create a platform that enhances data-driven decision-making, streamlines operations, and integrates AI technologies to imp…

Explore how data science has become essential across diverse sectors, how people can learn about data science, and how engineers can transition into this field.

In the final part of this three-part series, we extend our learning of Part 2 to the multivariate model and train a single model to predict three outcomes: oil, gas, and water.

Explore the challenges associated with fiber-optics data analysis and how recent advances in technology can be leveraged to maximize the value of the data.

These seven open-source simulators are available for free use and are among the best available in the industry.

Dan Jeavons, Shell’s VP of computational science and digital innovation, discussed the findings in MIT’s recent report on digital technology’s impact on a net-zero emissions future with Aman Srivastava, TWA deputy editor in chief.

Join us for the final installment in our four-part series focused on addressing the implementation of AI in the petroleum industry using a real case study.

Continue our journey with Part 3 of this four-part series focused on addressing the implementation of AI in the petroleum industry using a real case study.