Data mining/analysis

A supervised machine-learning algorithm is developed to classify drilling parameters that increase rate of penetration and bit endurance for use in unconventional fields in Australia.
This paper describes how severe rig limitations were overcome through an optimization plan in which an optimal bottomhole assembly was designed and drilling practices were customized.
The authors describe an integrated geological-engineering data-management project covering all aspects of well-engineering work flows.

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