Найдено 20 результатов.

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Результаты
1.
Restricted-Orientation Convexity : with 74 Fifures / E. Fink, D. WoodПубликация: : Springer-Verlag, 2004Описание: 96 p. : il.Доступность: Экземпляры, доступные для выдачи: НТБ ТПУРасстановочный шифр: 514 F54 (1).

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A geomechanical approach to casing collapse prediction in oil and gas wells aided by machine learning / N. Mohamadian, H. Ghorbani, D. A. Wood [et al.]Уровень набора: Journal of Petroleum Science and EngineeringДоступность: :

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Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes / H. Ghorbani, D. A. Wood, N. Mohamadian [et al.]Уровень набора: Flow Measurement and InstrumentationДоступность: :

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Prediction performance advantages of deep machine learning algorithms for two-phase flow rates through wellhead chokes / H. Sh. Barjouei, H. Ghorbani, N. Mohamadian [et al.]Уровень набора: Journal of Petroleum Exploration and ProductionДоступность: :

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Predicting Formation Pore-Pressure from Well-Log Data with Hybrid Machine-Learning Optimization Algorithms / M. Farsi, N. Mohamadian, H. Ghorbani [et al.]Уровень набора: Natural Resources ResearchДоступность: :

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Hybrid machine learning algorithms to predict condensate viscosity in the near wellbore regions of gas condensate reservoirs / Behesht Abad Abouzar Rajabi, M. Mousavi Seyedmohammadvahid, N. Mohamadian [et al.]Уровень набора: Journal of Natural Gas Science and EngineeringДоступность: :

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Nanoparticle applications as beneficial oil and gas drilling fluid additives: A review / M. Al-Shargabi, Sh. Davoodi, D. Wood [et al.]Уровень набора: Journal of Molecular LiquidsДоступность: :

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A critical review of self-diverting acid treatments applied to carbonate oil and gas reservoirs / M. Al-Shargabi, Sh. Davoodi, D. A. Wood [et al.]Уровень набора: Petroleum ScienceДоступность: :

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Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms / M. Rajabi, O. Hazbeh, Sh. Davoodi [et al.]Уровень набора: Journal of Petroleum Exploration and ProductionДоступность: :

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Machine-learning models to predict hydrogen uptake of porous carbon materials from influential variables / Sh. Davoodi, Vo Thanh Hung, D. A. Wood [et al.]Уровень набора: Separation and Purification TechnologyДоступность: :