Data & Analytics
Canada’s development of large-scale digital drilling core libraries and open geoscience data platforms follows approaches pioneered in Australia, particularly Western Australia, through decades of government investment in geoscience data collection and preservation.
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.
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Not only are individual wells challenging, but most are part of a complex reservoir network that must be managed over an extended period. -
Statoil, operating the Troll field in the Norwegian sector of the North Sea, wished to run a deep sidetrack from the main bore in a multilateral well that would exit through the liner in the reservoir. Several zonal-isolation methods had been evaluated, but on the basis of previous experience Statoil decided to use swellable-packer technology. Testing revealed that th…
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The steam-assisted-gravity-drainage (SAGD) process along with an efficient steam-use process can reduce production costs and increase the oil-recovery rate. The use of real-time downhole monitoring is an effective approach to achieve this optimization.
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I recently attended an internal conference in my company where one of the major topics was unconventionals. I have followed at some distance the business and technical trends that have shaped this still-emerging opportunity set, but this was my first exposure to behind-the-scenes experiences.
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This paper describes an all-in-one system that combines nodal-analysis and numerical-simulation models to calculate the effect of intelligent-completion components—such as swell packers, internal control valves, and inflow-control devices—on lateral production profiles.
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The smart multilateral well has assisted in addressing premature water breakthrough, has enhanced water-free oil production, and has facilitated uniform depletion, which results in improved hydrocarbon recovery.
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Silixa’s iDAS (intelligent Distributed Acoustic Sensor) offers a solution for permanent and continuous downhole production monitoring and reservoir monitoring by overcoming the cost and technology challenges encountered with traditional point sensors.
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