Martin J. Blunt

According to our database, Martin J. Blunt authored at least 13 papers between 2012 and 2026.

Collaborative distances:

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

2026

SAMamba3D: adapting Segment Anything for generalizable 3D segmentation of multiphase pore-scale images.

Rui Zhang, Xianzhi Song, Linqi Zhu, Branko Bijeljic, Gensheng Li, Martin J. Blunt

CoRR, May, 2026

Learning Pore-scale Multiphase Flow from 4D Velocimetry.

Chunyang Wang, Linqi Zhu, Yuxuan Gu, Robert van der Merwe, Xin Ju, Catherine Spurin, Samuel Krevor, Rex Ying, Tobias Pfaff, Martin J. Blunt, Tom Bultreys, Gege Wen

CoRR, March, 2026

Enhancing the parameterization of reservoir properties for data assimilation using deep VAE-GAN.

Marcio Augusto Sampaio, Paulo Henrique Ranazzi, Martin J. Blunt

Comput. Geosci., 2026

A conditional latent diffusion framework for dynamic CT image denoising in multiphase flow and reactive transport studies of porous media.

Menglu Kang, Qianqian Ma, Lizhi Xiao, Guangzhi Liao, Branko Bijeljic, Martin J. Blunt

Comput. Geosci., 2026

2019

DeepFlow: History Matching in the Space of Deep Generative Models.

Lukas Mosser, Olivier Dubrule, Martin J. Blunt

CoRR, 2019

2018

A numerical model of two-phase flow at the micro-scale using the volume-of-fluid method.

Mosayeb Shams, Ali Q. Raeini, Martin J. Blunt, Branko Bijeljic

J. Comput. Phys., 2018

Stochastic seismic waveform inversion using generative adversarial networks as a geological prior.

Lukas Mosser, Olivier Dubrule, Martin J. Blunt

CoRR, 2018

Conditioning of three-dimensional generative adversarial networks for pore and reservoir-scale models.

Lukas Mosser, Olivier Dubrule, Martin J. Blunt

CoRR, 2018

2017

Stochastic reconstruction of an oolitic limestone by generative adversarial networks.

Lukas Mosser, Olivier Dubrule, Martin J. Blunt

CoRR, 2017

Reconstruction of three-dimensional porous media using generative adversarial neural networks.

Lukas Mosser, Olivier Dubrule, Martin J. Blunt

CoRR, 2017

2015

Interface control volume finite element method for modelling multi-phase fluid flow in highly heterogeneous and fractured reservoirs.

Ahmad S. Abushaikha, Martin J. Blunt, Olivier R. Gosselin, Christopher C. Pain, Matthew David Jackson

J. Comput. Phys., 2015

2012

Artificial neural networks workflow and its application in the petroleum industry.

N. Al-Bulushi, P. R. King, Martin J. Blunt, M. A. Kraaijveld

Neural Comput. Appl., 2012

Modelling two-phase flow in porous media at the pore scale using the volume-of-fluid method.

Ali Q. Raeini, Martin J. Blunt, Branko Bijeljic

J. Comput. Phys., 2012