David A. Wood

According to our database, David A. Wood authored at least 15 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A novel data-driven model for real-time prediction of static Young's modulus applying mud-logging data.

Shadfar Davoodi, Mohammad Mehrad, David A. Wood, Mohammed Al-Shargabi, Grachik Eremyan, Tamara Shulgina

Earth Sci. Informatics, December, 2024

Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids.

Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Mohammad Reza Hajsaeedi, Valeriy S. Rukavishnikov

J. Ind. Inf. Integr., 2024

Machine learning insights to CO2-EOR and storage simulations through a five-spot pattern - a theoretical study.

Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Mohammed Al-Shargabi, Valeriy S. Rukavishnikov

Expert Syst. Appl., 2024

2023

Improving permeability prediction in carbonate reservoirs through gradient boosting hyperparameter tuning.

Mohammed A. Abbas, Watheq J. Al-Mudhafar, David A. Wood

Earth Sci. Informatics, December, 2023

Deep ensemble learning for high-dimensional subsurface fluid flow modeling.

Abouzar Choubineh, Jie Chen, David A. Wood, Frans Coenen, Fei Ma

Eng. Appl. Artif. Intell., November, 2023

Combined machine-learning and optimization models for predicting carbon dioxide trapping indexes in deep geological formations.

Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Valeriy S. Rukavishnikov

Appl. Soft Comput., August, 2023

Machine-learning predictions of solubility and residual trapping indexes of carbon dioxide from global geological storage sites.

Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Valeriy S. Rukavishnikov, Zhenxue Dai

Expert Syst. Appl., July, 2023

Weekly carbon dioxide exchange trend predictions in deciduous broadleaf forests from site-specific influencing variables.

David A. Wood

Ecol. Informatics, July, 2023

Grayscale Image Statistical Attributes Effectively Distinguish the Severity of Lung Abnormalities in CT Scan Slices of COVID-19 Patients.

Sara Ghashghaei, David A. Wood, Erfan Sadatshojaei, Mansooreh Jalilpoor

SN Comput. Sci., March, 2023

Fourier Neural Operator for Fluid Flow in Small-Shape 2D Simulated Porous Media Dataset.

Abouzar Choubineh, Jie Chen, David A. Wood, Frans Coenen, Fei Ma

Algorithms, January, 2023

Hybridized machine-learning for prompt prediction of rheology and filtration properties of water-based drilling fluids.

Shadfar Davoodi, Mohammad Mehrad, David A. Wood, Hamzeh Ghorbani, Valeriy S. Rukavishnikov

Eng. Appl. Artif. Intell., 2023

2022

Carbonate / siliciclastic lithofacies classification aided by well-log derivative, volatility and sequence boundary attributes combined with machine learning.

David A. Wood

Earth Sci. Informatics, 2022

2020

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.

Abouzar Choubineh, David A. Wood, Zahak Choubineh

Int. J. Crit. Infrastructure Prot., 2020

2019

A machine learning approach to predict drilling rate using petrophysical and mud logging data.

Mohammad Sabah, Mohsen Talebkeikhah, David A. Wood, Rasool Khosravanian, Mohammad Anemangely, Alireza Younesi

Earth Sci. Informatics, 2019

2018

A critical-path focus for earned duration increases its sensitivity for project-duration monitoring and forecasting in deterministic, fuzzy and stochastic network analysis.

David A. Wood

J. Comput. Methods Sci. Eng., 2018