Drilling
This edition highlights three offshore technology papers that address a common industry theme: how targeted engineering solutions can reduce uncertainty, shorten operations, and make technically constrained offshore well activities more executable.
This paper aims to establish a set of best practices for generating particle-size-distribution data from core samples.
This paper discusses the successful execution of two openhole gravel-pack completions in two Gulf of Mexico fields with depleted reservoirs.
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Drilling change requires training drillers. Leadership matters, as does motivation, engaging displays, and understanding office politics. Four different looks at the human side of drilling productivity improvement. -
The complete paper describes a physics-based model of interference and a sensitivity study to propose guidelines for well spacing and a drilling timeline for multiple horizontal wells in the Vaca Muerta shale.
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The well will immediately be brought on production and is expected to flow at more than 100 MMscf/D of gas and 3,000 B/D of associated condensate, the company said.
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The discovery marks London-based Tullow’s first operated contribution to a long list of discoveries since 2015 in the emerging petroleum province.
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Leaders from two large US onshore rig contractors said their expectations that the rig-count slide would hit a second-quarter bottom were off and are now refraining from making new predictions as to when it will end.
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The company's new 3D-inversion visualization process enables precise geosteering and accurate well placement.
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The Italian operator reported positive appraisal and exploration results from wells drilled some 10,000 km apart.
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The green light for Santos Energy’s drilling program in the McArthur Basin comes after a moratorium on hydraulic fracturing in the Northern Territory was lifted in 2018.
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Moving their directional drillers into their Houston real-time remote operations centers has improved drilling efficiency for two of the top shale producers.
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This paper is part of an ongoing effort to minimize the likelihood of failure using data-mining and machine-learning algorithms.
