Drilling
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 study aims to thoroughly assess the influence of various completions, fracturing stimulation, and intrinsic reservoir properties affecting the productivity of 10 major unconventional plays while uncovering insights and trends unique to each play
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Industry experts from Fugro analyze what the future holds for offshore energy fields and how the industry can embrace and prepare itself for an autonomous and digital future. -
The drilling of wells in shale and granite shares a common need—faster drilling is required to make it work.
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A new report shows that the tight offshore rig market is even tighter than most estimates reflect. This offers relief to battered drilling contractors which are now demanding higher dayrates.
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H&P pumps $33 million into LNG firm Galileo Technologies, supporting technology focused on decarbonization of the energy supply chain.
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Technology continues to transform every aspect of our lives and its role in modernizing oilfield operations is no different.
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An operator has redefined onsite operations reporting through the development of a standardized set of reporting activity codes as the backbone of a standardized digital well-design and execution process.
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The authors describe a study analyzing a comprehensive data set recorded in casing-cemented sandwich sections and recovered during the abandonment of a well in the Valhall Field.
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The paper describes the experience of using a machine-learning model prepared by the ensemble method to prevent stuck-pipe events during well construction in extended-reach wells.
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Drilling automation champions met to identify where this emerging technology needs to be by the end of the decade. What they ended up agreeing on most was that the business models used today are largely incompatible with the technology of the future.
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Artificial intelligence and machine learning, which can effectively mine deep insight from a large amount of drilling operational data and synthetic forward modeling data, are starting to shape the design and operations of extended-reach and complex wells.
