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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In the past decade, fiber-optic -based sensing has opened up opportunities for in-well reservoir surveillance in the oil and gas industry. In this paper, the authors present a recent example of single-phase-flow profiling with distributed acoustic sensing. -
Despite the recent market conditions during the last year, our industry continued to demonstrate further advances in the monitoring and surveillance field and to attest to the added value provided.
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Cyber threats have expanded beyond data breaches and the theft of intellectual property. Drilling and production assets are at risk of being disrupted or destroyed due to vulnerable control systems.
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More than 45% of energy companies fell victim to at least one cyberattack in 2014, a higher percentage than in any other corporate sector. With constant hacking threats, companies must develop strong cybersecurity strategies.
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Use of unmanned aerial vehicles to monitor pipeline networks for theft and other issues is discussed.
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Since 2007, an operator in Nigeria has registered a significant increase of oil-spill events caused by sabotage and oil-theft activities. The technology presented here allows detecting and locating leaks taking place at a distance from the sensor of up to 35 km.
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For thin-oil-rim reservoirs, well placement, well type, well path, and the completion methods must be evaluated with close integration of key reservoir and production-engineering considerations.
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Many business and digital corporations claim that between 100 billion and 200 billion devices could be connected by 2020.
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A data-driven approach to successfully analyze and evaluate production-fluid impact during facility system divert events is presented. The work flow effectively identifies opportunities for prompt event mitigation and system optimization.
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Failure to prioritize objectives and improper selection of candidate wells can have significant implications for both derived value and potential risk.
