bottomhole assembly

The authors of this paper present an autonomous directional-drilling framework built on intelligent planning and execution capabilities and supported by surface and downhole automation technologies.

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.

This paper highlights the potential of machine learning to be used as a tool in assisting the drilling engineer in bit selection through data insights previously overlooked.

The authors write that simple changes in drillstring design can lead to huge savings in a climate that demands continual reductions in well-delivery time and well costs.

Anomalies in heart function can be diagnosed in real time by measuring an electrical signal. Petroleum engineers have adapted the concept to diagnose anomalous drilling conditions in real time using a shock signature recorded downhole.

The complete paper discusses a new performance-evaluation methodology that combines bottomhole assembly (BHA) modeling with field data.

The complete paper presents a methodology designed for optimally matching drill bits, mud motors, and bottomhole-assembly components for reduced failure risks and improved drilling performance.

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.

The complete paper describes an offshore artificial island project northwest of Abu Dhabi in which drilling limits were extended continually by adopting new technologies and practices in an extended-reach-drilling (ERD) campaign.

This paper describes the analysis of sidetracks drilled in an open hole by an annular ledge formation method with a downhole motor in multilateral wells.