Drilling

This paper highlights a new online system for monitoring drilling fluids, enabling intelligent control of drilling-fluid performance.
This paper investigates the use of machine-learning techniques to forecast drilling-fluid gel strength.
This paper aims to close some of the many knowledge gaps that exist in the field of drilling CO2 storage wells, a task that is expected to involve handling an influx of CO2 into the drilling fluid.

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