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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Rigs drilling faster earn less money per foot because they are contracted by the day. But at least they are still working. Now service companies are developing new rigs with more automated functions, and want increased rates based on the productivity gains achieved.
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This paper shows how high-frequency, real-time drilling data from wired drillpipe has helped optimization of drilling performance and achievement of additional improvements in the New Mexico Delaware Basin.
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This paper describes how new technology was implemented and deployed through a downhole acoustic network through a sequence of runs in complex North Sea wells under managed-pressure conditions.
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This paper discusses how oil and gas companies are using a new generation of AI-driven applications powered by computational-knowledge graphs and AI algorithms to create a digital knowledge layer for oil and gas wells that provides a timeline of significant well events.
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Drilling systems automation (DSA) is moving into commercial activities on a broad front. Equipment suppliers are delivering automated drilling-control systems, and everyone (equipment suppliers, service companies, drilling contractors, operators) is delivering systems-automation applications.
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The complete paper presents a process used to successfully implement a rig-based drilling advisory system (RDAS) across a mixed group of rig contractors.
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The complete paper presents a drilling semantic framework that allows software solutions to achieve automatic and versatile self-configuration.
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One of the frustrating aspects of well-productivity analysis is identifying the causes of lower-than-expected production/injection during initial well lifetime. Our task is to evaluate the multivariate aspects of well design.
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In the current work, a rig advisory system is developed to continually improve rate of penetration (ROP) and drilling performance. An intelligent drilling advisory system (IDAS), based on a soft closed-loop solution with multiple regression analysis has been established.
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For the development of the Dvalin high-pressure/high-temperature (HP/HT) gas field in the Norwegian Sea, a completion scheme using standalone screens is planned.