Drilling
SPE DSATS/IADC ART Symposium to Explore ‘Comprehensive Impactful Drilling Systems—How do we Evolve?’
The event to be held on 16 March in Galveston, Texas, will address important issues for the Drilling Systems Advancement Technical Section's forward planning with industry speakers and an interactive working session.
The Granat prospect on the Norwegian Continental Shelf may be developed with a subsea tieback to existing infrastructure.
Eni reports its latest deepwater exploration well offshore Côte d'Ivoire found gas and condensate in high-quality Cenomanian sands in the Calao channel complex.
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The authors of this paper present results of a study that examined formation-damage mechanisms caused by drilling fluids in tight reservoirs in onshore oil fields in Abu Dhabi. -
The paper presents predicted vs. measured wear for six wells in the Culzean field, a high-pressure/high-temperature gas condensate field in the central North Sea.
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The authors of this paper present a laboratory-based model to determine the detachment of authigenic and detrital particles in formation damage.
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The authors of this paper discuss a biosurfactant treatment that offers an economical method for remediation of formation damage caused by high-molecular-weight paraffin wax deposition in porous media.
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This paper reviews the successful application of a mud-cooling and managed-pressure-drilling system in a high-pressure/high-temperature well to explore the potential of a Mesozoic carbonate platform in the Nile Delta of Egypt.
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Environmental report recommends shrinking the Alaska project to three drilling sites from the five initially proposed by ConocoPhillips.
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With the arrival of the digital age, solutions in big data, automation, and artificial intelligence are rapidly opening the door to a deeper and more-comprehensive understanding of drilling operations around the world.
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The authors of this paper present an autonomous directional-drilling framework built on intelligent planning and execution capabilities and supported by surface and downhole automation technologies.
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The authors of this paper discuss a global rate-of-penetration machine-learning model with the potential to eliminate learning curves and reduce time and costs associated with developing a new model for every field.
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The authors of this paper describe a project that demonstrated the feasibility of using deep-learning and machine-learning approaches to introduce camera-based solids monitoring to the drilling industry.
