Well integrity/control
This paper describes the development of a method of predicting drillstring-friction coefficient during tripping operations that can be used for early warning of stuck pipe.
This paper proposes a time-series analysis approach to build a reliable, easy-to-use tool to automatically detect stuck pipe accurately and early.
This paper presents a novel methodology that merges principles of physics, data science, and uncertainty modeling to offer more-resilient and -precise solutions for managing real-time pipe-sticking occurrences
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This paper presents a comprehensive literature review of perforate, wash, and cement techniques that compares new methods with traditional ones and uses field cases and computational fluid dynamics to find the most cost- and time-effective practices without sacrificing safety. -
New strides in computer vision, well controls indicators, and BOP alignment were showcased at the recent Offshore Technology Conference.
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The Texas Railroad Commission has tightened its guidelines on the permitting of disposal wells in the Permian Basin.
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This paper addresses the deployment of an external protective coating with a rough surface profile in wells identified as susceptible to common cementing issues.
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This paper provides examples for planning and execution of primary and remedial managed pressure cementing in deepwater drilling operations.
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This paper presents a lost-circulation model used during design and job-evaluation phases to accurately predict top of cement and equivalent circulating densities.
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SLB is introducing a new electric well-control system to replace larger conventional, fluid‑controlled hydraulic equipment.
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To enable a fully interventionless approach, a barrier-rated tubing-hanger valve has been developed to eliminate slickline intervention and minimize associated risks and operational time.
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This paper aims to present thoroughly the application of subsurface safety injection valves in extremely high-temperature environments.
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This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.
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