vibration

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

This paper analyzes the interaction of high-frequency torsional oscillations (HFTO) with lateral vibrations based on a model that accounts for the superimposed movement of whirl and HFTO at the bit.

This paper discusses a full-scale drilling test rig that allows comprehensive study of the influences of bit characteristics on high-frequency torsional oscillations (HFTO) for the first time.

The authors discuss a study based on twistoffs experienced with bottomhole assembly components during drilling operations and provide recommendations for reduction or elimination of these incidents.

The authors describe how tools in machine learning are used to develop data-driven models that can be used for accurate and efficient fatigue-damage prediction for marine risers.

A combination of computational-fluid-dynamics and finite-element modeling offers a potentially powerful tool for assessing and diagnosing multiphase-flow-induced vibration problems in hydrocarbon-production piping systems.

This paper explores the nature of the vibrational dysfunction known as BHA chatter. A field-proven frequency-domain model illustrates the cause of the dysfunction, its rotary-speed dependence, and mitigation methods and results.

This paper presents dynamic simulations, prototype testing, and field-test results of a BHA component that isolates the upper part of the BHA from HFTO.

This paper examines multiple factors that can affect the severity of stick/slip and measures their actual effect.

Drillstring vibration is a leading cause of downhole-tool failure and premature wear of downhole equipment.