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David A. Wood 0003
Person information
- affiliation: DWA Energy Ltd., Lincoln, UK
Other persons with the same name
- David A. Wood 0001 — University of Wisconsin-Madison, Madison, USA
- David A. Wood 0002 — Brigham Young University, Provo, UT, USA
- David A. Wood 0004 — King's College London, School of Biomedical Engineering, UK
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2020 – today
- 2024
- [j14]Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Mohammed Al-Shargabi, Valeriy S. Rukavishnikov:
Machine learning insights to CO2-EOR and storage simulations through a five-spot pattern - a theoretical study. Expert Syst. Appl. 250: 123944 (2024) - [j13]Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Mohammad Reza Hajsaeedi, Valeriy S. Rukavishnikov:
Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids. J. Ind. Inf. Integr. 41: 100662 (2024) - 2023
- [j12]Abouzar Choubineh, Jie Chen, David A. Wood, Frans Coenen, Fei Ma:
Fourier Neural Operator for Fluid Flow in Small-Shape 2D Simulated Porous Media Dataset. Algorithms 16(1): 24 (2023) - [j11]Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Valeriy S. Rukavishnikov:
Combined machine-learning and optimization models for predicting carbon dioxide trapping indexes in deep geological formations. Appl. Soft Comput. 143: 110408 (2023) - [j10]Shadfar Davoodi, Mohammad Mehrad, David A. Wood, Hamzeh Ghorbani, Valeriy S. Rukavishnikov:
Hybridized machine-learning for prompt prediction of rheology and filtration properties of water-based drilling fluids. Eng. Appl. Artif. Intell. 123(Part C): 106459 (2023) - [j9]Abouzar Choubineh, Jie Chen, David A. Wood, Frans Coenen, Fei Ma:
Deep ensemble learning for high-dimensional subsurface fluid flow modeling. Eng. Appl. Artif. Intell. 126: 106968 (2023) - [j8]David A. Wood:
Weekly carbon dioxide exchange trend predictions in deciduous broadleaf forests from site-specific influencing variables. Ecol. Informatics 75: 101996 (2023) - [j7]Mohammed A. Abbas, Watheq J. Al-Mudhafar, David A. Wood:
Improving permeability prediction in carbonate reservoirs through gradient boosting hyperparameter tuning. Earth Sci. Informatics 16(4): 3417-3432 (2023) - [j6]Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Valeriy S. Rukavishnikov, Zhenxue Dai:
Machine-learning predictions of solubility and residual trapping indexes of carbon dioxide from global geological storage sites. Expert Syst. Appl. 222: 119796 (2023) - [j5]Sara Ghashghaei, David A. Wood, Erfan Sadatshojaei, Mansooreh Jalilpoor:
Grayscale Image Statistical Attributes Effectively Distinguish the Severity of Lung Abnormalities in CT Scan Slices of COVID-19 Patients. SN Comput. Sci. 4(2): 201 (2023) - 2022
- [j4]David A. Wood:
Carbonate / siliciclastic lithofacies classification aided by well-log derivative, volatility and sequence boundary attributes combined with machine learning. Earth Sci. Informatics 15(3): 1699-1721 (2022) - 2020
- [j3]Abouzar Choubineh, David A. Wood, Zahak Choubineh:
Applying separately cost-sensitive learning and Fisher's discriminant analysis to address the class imbalance problem: A case study involving a virtual gas pipeline SCADA system. Int. J. Crit. Infrastructure Prot. 29: 100357 (2020)
2010 – 2019
- 2019
- [j2]Mohammad Sabah, Mohsen Talebkeikhah, David A. Wood, Rasool Khosravanian, Mohammad Anemangely, Alireza Younesi:
A machine learning approach to predict drilling rate using petrophysical and mud logging data. Earth Sci. Informatics 12(3): 319-339 (2019) - 2018
- [j1]David A. Wood:
A critical-path focus for earned duration increases its sensitivity for project-duration monitoring and forecasting in deterministic, fuzzy and stochastic network analysis. J. Comput. Methods Sci. Eng. 18(2): 359-386 (2018)
Coauthor Index
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last updated on 2024-10-07 21:25 CEST by the dblp team
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