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Everywhere you look these days, there is talk of how advances in big data, artificial intelligence, and machine learning will revolutionize virtually every aspect of our lives. This month, we will look at how researchers in the drilling domain are using this potential to improve well construction.

These papers provided insights and advances into field-operations automation, machine-learning-assisted petrophysical characterization, and fluid-distribution analysis in unconventional assets.

This paper presents a complete digital workflow applied to several greenfields in the Asia Pacific region that leads to successful deep-transient-testing operations initiated from intelligent planning that positively affected field-development decisions.

This study introduces a cleanup- and flowback-testing approach incorporating advanced solids-separation technology, a portable solution, equipment automation, improved metallurgy, and enhanced safety standards.

Technical papers reviewed for this feature are laden with novel technology borne of the quest to understand and solve complex geological structures and features that ultimately will improve our collective effort toward fostering efficient energy production. The three papers presented here are focused on innovative approaches to handling such complexities.

In this paper, the authors propose a regression machine-learning model to predict stick/slip severity index using sequences of surface measurements.

A Shell partnership with YPF marks a significant milestone for the Argentina LNG export facility, raising new questions about the nation’s potential to unlock the economic power of its vast shale reserves.

Updates about global exploration and production activities and developments.

Member access to pdf, digital edition, and technical papers.

Global offshore decommissioning projects hear the starting gun in Australia and the North Sea, but will the race be a marathon or a sprint?