High-resolution X-ray micro-tomography and nano-tomography datasets of Estaillades Limestone

The datasets contain 5 stitched X-ray micro-tomographic images (grey-scale, doped, difference, segmented porespace and segmented micro-porespace with porespace) and 3 X-ray nano-tomographic images of a region of microporous porespace in Estaillades Limestone. The x-ray tomographic images were acquired at a voxel-resolution of 3.9676 µm using a Zeiss Versa XRM-510 flat-panel detector at 70 kV, 6W, and 85 µA with an exposure time of 0.037s and 64 frames. The X-ray nano-tomographic images were reconstructed using a proprietary filtered back projection algorithm from a set of 1601 projections, collected with the Zeiss Ultra 810 with 32nm voxel size using a 5.4keV energy quasi-monochromatic beam with an exposure time of 90s. The data was collected at Imperial College London and Zeiss Labs with the aim of investigating pore-scale microporosity in carbonates with a heterogenous pore structure. Understanding the effect of microporosity on flow is important in many natural and industrial processes such as contaminant transport, and geo-sequestration of supercritical CO2 to address global warming. These tomographic images can be used for validating various pore-scale flow models such as direct simulations, pore-network and neural network models for upscaling flow across scales.

Date (Creation): 2018-01

Identifier: http://data.bgs.ac.uk/id/dataHolding/13607368

Author

Qatar Carbonates and Carbon Storage Research Centre - qccsrc@imperial.ac.uk

United Kingdom

Point of contact

Qatar Carbonates and Carbon Storage Research Centre - qccsrc@imperial.ac.uk

United Kingdom

Point of contact

Imperial College London - Hannah Menke

London , United Kingdom

Maintenance and update frequency: notApplicable notApplicable

GEMET - INSPIRE themes, version 1.0

Geology

BGS Thesaurus of Geosciences

Carbonate rocks
Carbon capture and storage
X ray analysis
Pore space
Tomography
NGDC Deposited Data
UKCCS

dataCentre

Keywords

NERC_DDC

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Other constraints: licenceOGL

Other constraints: Available under the Open Government Licence subject to the following acknowledgement accompanying the reproduced NERC materials "Contains NERC materials ©NERC [year]"

Use constraints: otherRestrictions Other restrictions

Other constraints: The copyright of materials derived from the British Geological Survey's work is vested in the Natural Environment Research Council [NERC]. No part of this work may be reproduced or transmitted in any form or by any means, or stored in a retrieval system of any nature, without the prior permission of the copyright holder, via the BGS Intellectual Property Rights Manager. Use by customers of information provided by the BGS, is at the customer's own risk. In view of the disparate sources of information at BGS's disposal, including such material donated to BGS, that BGS accepts in good faith as being accurate, the Natural Environment Research Council (NERC) gives no warranty, expressed or implied, as to the quality or accuracy of the information supplied, or to the information's suitability for any use. NERC/BGS accepts no liability whatever in respect of loss, damage, injury or other occurence however caused.

Other constraints: Available under the Open Government Licence subject to the following acknowledgement accompanying the reproduced NERC materials "Contains NERC materials ©NERC [year]"

Metadata language: EnglishEnglish

Topic category

Geoscientific information

Begin date: 2018-01-01

End date: 2018-07-01

Reference System Information

No information provided.

Distribution format

.raw ()
.am ()
.tiff ()

OnLine resource: http://www.bgs.ac.uk/ukccs/accessions/index.html#item112949

OnLine resource: Digital Object Identifier (DOI)

Hierarchy level: nonGeographicDataset Non geographic dataset

Other: non geographic dataset

Conformance result

Date (Publication): 2011

Explanation: See the referenced specification

Pass: No

Conformance result

Date (Publication): 2010-12-08

Explanation: See http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:323:0011:0102:EN:PDF

Pass: No

Statement: First a 10mm diameter mechanically drilled sample of (air saturated) Estaillades was scanned low (10 µm) resolution. Fiducial marks made of aluminium tape were placed on the surface of the sample to enable alignment between the laser micro-machining stage and the sample. The low resolution image was then segmented into microporosity, macroporosity and solid mineral grains. This micro porosity was then inspected to identify the location within the Nano-CT corresponding to location within the fine pillar of the region of 40% porosity. This region was then scanned with a 32nm voxel size within the fine pillar. The resulting reconstructed image was first denoised using an edge preserving non-local means filter, then segmented using ZEISS Zen Intellesis machine learning based segmentation. The resulting porosity observed within the image (41%) matched well with the inferred porosity of the 30 µm x 30 µm x 30 µm region initially identified from the macroscopic 10µm voxel size image of the 10mm diameter core. Micro-tomographic Images: The x-ray tomographic images were acquired at a voxel-resolution of 3.9676 µm using a Zeiss Versa XRM-510 flat-panel detector at 70 kV, 6W, and 85 µA with an exposure time of 0.037s and 64 frames. A new 5mm diameter, 24mm long core of Estaillades was then drilled from the same 1 m3 block of limestone as the nano scale study. The core was then imaged dry. The core was confined using DI water at 10 bar and two pumps were used to drive highly doped brine of 20% wt KI through the core with a constant back pressure of 2 bar and scanned after 100 pore volumes. The core was then washed and then three differential pressure measurements were taken during flow. The details of the sample preparation and fluid injection strategy can be found in Menke et al. (2018). The images were acquired in .txrm format. These were then reconstructed using the Zeiss reconstructor software and processed using ImageJ, Avizo, ORS, and Zeiss Intellesis software and converted to .tiff formats. The greyscale images are in 16 bit unsigned .tiff, and binary (segmented) images are in 8 bit unsinged .tiff format.