Drilling

This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
This paper proposes a novel approach toward drilling maximum-reservoir-contact wells by integrating automated drilling and geosteering software to control the downhole bottomhole assembly, thereby minimizing the need for human intervention.
When it comes to drilling automation, deciding where your technology should be deployed is a critical factor in overall solution design. Similar to other industries, there is an eternal debate on the merits of cloud vs. edge systems.

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