Drilling
Developing the theory of mechanical specific energy from the perspective of instantaneous drilling power rather than the compressive strength of the formation leads to an improved understanding of drill-bit mechanical efficiency.
The oilfield service company will supply power plants capable of electrifying 180,000 US homes with geothermal energy.
This paper presents an efficient mathematical optimization method for well placement that maximizes contact with the productive zones for the best locations in the reservoir.
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This paper presents the design and functionality of an apparatus that measures directly and automatically the pressure/volume/temperature (PVT) behavior of the drilling fluid contained in a pit. -
In this paper, alternative approaches to solids characterization are presented that lend themselves better to automation and real-time monitoring than API retort measurement.
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Intellilift and Transocean are working together on a software solution to expedite the well construction process.
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The buzz about the future of automated drilling and it becoming reality depends on improvements in downhole data gathering now. Halliburton is working on it.
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ExxonMobil has drilled a horizontal well with a rig billed by Nabors as the first fully automated land rig. The big question now is whether ExxonMobil will come back for more after this three-well test.
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Few industries contain as many phases, steps, and levels of interface between the start and end product as the oil and gas industry. It therefore is hardly surprising that communication, in all its varied forms, is at the very heart of our business.
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This paper describes a study aiming to provide input for the well-completion-strategy design and operational parameters for a carbonate reservoir experiencing electrical-submersible-pump failures.
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Deal marks the first ADNOC partnership with Pakistani energy companies.
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This paper details new technologies and work flows implemented for Australian offshore wells to improve drilling efficiency while managing associated risks.
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The paper demonstrates the application of an interpretable machine-learning work flow using surface drilling data to identify fracable, brittle, and productive rock intervals along horizontal laterals in the Marcellus shale.
