Mohammad Mehrad

According to our database, Mohammad Mehrad authored at least 7 papers between 2023 and 2024.

Collaborative distances:

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

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

A new approach to mechanical brittleness index modeling based on conventional well logs using hybrid algorithms.

Milad Zamanzadeh Talkhouncheh, Shadfar Davoodi, Babak Larki, Mohammad Mehrad, Sina Rashidi, Maher Vasfi

Earth Sci. Informatics, December, 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

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