Drilling
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.
The integration of the latest state-of-the-art technology in modeling and measurement of drilling dynamics and borehole quality has enhanced the understanding of bit, bottomhole assembly, and drillstring design. This can be seen in recent work on analysis of cutter-formation interaction, borehole-quality improvement, and modeling improvements.
This paper describes a collaborative project to analyze affected wells, identify commonalities, and optimize bit design and drilling parameters to mitigate the effects of borehole spiraling.
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In this paper, bottomhole-assembly lateral behavior is analyzed using different types of computations, including static, dynamic, frequency-based, and time-based. -
Operators shared behind-the-scenes details on innovations like drilling horseshoe wells and trimulfrac completions along with in-basin challenges like handling produced water during SPE’s Permian Basin Energy Conference.
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Digitalization and automation of the drilling process drive the need for an interoperability platform in a drilling operation, where a shared definition and method of calculation of the drilling process state is a fundamental element of an infrastructure to enable interoperability at the rigsite.
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The birthplace of Royal Dutch Shell, Indonesia and Malaysia, buck trends and grow their gas and oil industries, expecting a record number of final investment decisions in the next 4 years in gas, deep water, and carbon capture projects to support Southeast Asia’s booming economic growth.
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Technology uptake aimed at optimizing resources, delivering consistency, and augmenting what humans can do.
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This paper highlights a new online system for monitoring drilling fluids, enabling intelligent control of drilling-fluid performance.
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A proposed integrated workflow aims to guide prediction and mitigating solutions to reduce casing-deformation risks and improve stimulation efficiency.
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This paper investigates the use of machine-learning techniques to forecast drilling-fluid gel strength.
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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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This year’s primary selections for the Drilling and Completion Fluids Technology Focus reflect now-well-established industrywide emphases on machine learning, automation, and the achievement of successful drilling of CO2 storage wells.
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