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Title: Dynamic three-dimensional maps of solute concentration and solute arrival times in synthetic and geologic porous media

Abstract

Experimental and training data associated with the publication entitled ‘Three-Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography’ (published in WRR, DOI: 10.1029/2021WR031554). The dataset contain three-dimensional maps of various properties on four geologic rock cores obtained from X-ray Computed Tomography and Positron Emission Tomography imaging measurements. The synthetic training dataset used in the publication is also attached.

Authors:
; ; ; ;
Publication Date:
Other Number(s):
gz610dt4642
DOE Contract Number:  
SC0019165
Research Org.:
Stanford Univ., CA (United States); Univ. of Wisconsin, Madison, WI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Subject:
58 GEOSCIENCES
OSTI Identifier:
1864596
DOI:
https://doi.org/10.25740/gz610dt4642

Citation Formats

Huang, Zitong, Kurotori, Takeshi, Pini, Ronny, Benson, Sally, and Zahasky, Christopher. Dynamic three-dimensional maps of solute concentration and solute arrival times in synthetic and geologic porous media. United States: N. p., 2022. Web. doi:10.25740/gz610dt4642.
Huang, Zitong, Kurotori, Takeshi, Pini, Ronny, Benson, Sally, & Zahasky, Christopher. Dynamic three-dimensional maps of solute concentration and solute arrival times in synthetic and geologic porous media. United States. doi:https://doi.org/10.25740/gz610dt4642
Huang, Zitong, Kurotori, Takeshi, Pini, Ronny, Benson, Sally, and Zahasky, Christopher. 2022. "Dynamic three-dimensional maps of solute concentration and solute arrival times in synthetic and geologic porous media". United States. doi:https://doi.org/10.25740/gz610dt4642. https://www.osti.gov/servlets/purl/1864596. Pub date:Sat Jan 01 00:00:00 EST 2022
@article{osti_1864596,
title = {Dynamic three-dimensional maps of solute concentration and solute arrival times in synthetic and geologic porous media},
author = {Huang, Zitong and Kurotori, Takeshi and Pini, Ronny and Benson, Sally and Zahasky, Christopher},
abstractNote = {Experimental and training data associated with the publication entitled ‘Three-Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography’ (published in WRR, DOI: 10.1029/2021WR031554). The dataset contain three-dimensional maps of various properties on four geologic rock cores obtained from X-ray Computed Tomography and Positron Emission Tomography imaging measurements. The synthetic training dataset used in the publication is also attached.},
doi = {10.25740/gz610dt4642},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jan 01 00:00:00 EST 2022},
month = {Sat Jan 01 00:00:00 EST 2022}
}