Neural network modeling of in situ fluid-filled pore size distributions in subsurface shale reservoirs under data constraints

Long Short-Term Memory and Variational Autoencoder With Convolutional Neural Networks for Generating NMR T2 Distributions

(2018) Hao Li et al.   IEEE Geoscience and Remote Sensing Letters

Prediction of Subsurface NMR T2 Distributions in a Shale Petroleum System Using Variational Autoencoder-Based Neural Networks

(2017) Hao Li et al.   IEEE Geoscience and Remote Sensing Letters

Simulation of NMR response from micro-CT images using artificial neural networks

(2017) Reza Farzi et al.   Journal of Natural Gas Science and Engineering

Multilayer Neural Network with Multi-Valued Neurons in time series forecasting of oil production

(2016) Igor Aizenberg et al.   NEUROCOMPUTING

Prediction of free flowing porosity and permeability based on conventional well logging data using artificial neural networks optimized by Imperialist competitive algorithm – A case study in the South Pars gas field

(2015) Majid Jamshidian et al.   Journal of Natural Gas Science and Engineering

Estimating NMR T2 distribution data from well log data with the use of a committee machine approach: A case study from the Asmari formation in the Zagros Basin, Iran

(2014) Naser Golsanami et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

(2011) Mojtaba Asoodeh et al.   ROCK MECHANICS AND ROCK ENGINEERING

Estimation of NMR log parameters from conventional well log data using a committee machine with intelligent systems: A case study from the Iranian part of the South Pars gas field, Persian Gulf Basin

(2010) Mohammad Mahdi Labani et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING