UKGEOS_PNM_Supporting_Data.zip (59.38 MB)

UKGEOS PNM Supporting Data

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posted on 17.12.2020, 15:37 by Ryan Payton, Mark Fellgett, Brett L. Clark, Domenico Chiarella, Andrew Kingdon, Saswata Hier-Majumder
This folder contains files for analysis of 3D micro CT images for the article "Pore Scale Assessment of Subsurface Carbon Storage Potential: Implications for the UK Geoenergy Observatories Project" by Payton, Fellgett, Clark, Chiarella and Hier-Majumder.

To create the figures presented in the article run the python script 'analysis.py'

Description of data:

- overall_GG_SF_poro_perm.csv = porosity and permeability data collected in this study, obtained from measurements on the micro CT images using PerGeos.

- Each folder with the prefix 'GG' (Glasgow) contains 2 files:
- all_pores.csv = measurements made characterising the pore geometry within the sample using PerGeos on the micro CT images. 'all' indicates both connected and disconnected porosity.
- all_throats.csv = measurements made characterising the throat geometry within the sample using PerGeos on the micro CT images. 'all' indicates both connected and disconnected porosity.

- Each folder with the prefix 'SF' (Sellafield) contains 4 files:
- all_pores.csv = measurements made characterising the pore geometry within the sample using PerGeos on the micro CT images. 'all' indicates both connected and disconnected porosity.
- all_throats.csv = measurements made characterising the throat geometry within the sample using PerGeos on the micro CT images. 'all' indicates both connected and disconnected porosity.
- effective_pores.csv = measurements made characterising the pore geometry within the sample using PerGeos on the micro CT images. 'effective' indicates only connected porosity.
- effective_throats.csv = measurements made characterising the throat geometry within the sample using PerGeos on the micro CT images. 'effective' indicates only connected porosity.

- The folder 'literature_data' contains the supporting data used to plot the figures in this article which are fully referenced in the article itself. We uses these data as a comparison to our own.
- 'Poro_Perm' contains the supporting porosity and permeability measurements used where each CSV file in this folder is named after the original author, referenced in the article.
- 'PRThomson' contains the supporting data from our research group in CSV file format where the file name reflects the reference in our article.

Funding

London NERC DTP Studentship (NE/L002485/1)

BGS BUFI Studentship

Oracle for Research Grant

History

Date Created

September 2019 - August 2020

Date Available

17/12/2020

File Formats

Python (.py) scripts, CSV (.csv) data files and text (.txt) files.

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