Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-23T00:54:04.507Z Has data issue: false hasContentIssue false

Characterization of Darai Limestone Composition and Porosity Using Data-Constrained Modeling and Comparison with Xenon K-Edge Subtraction Imaging

Published online by Cambridge University Press:  29 May 2015

Sheridan C. Mayo*
Affiliation:
CSIRO Manufacturing Flagship, Private Bag 10, Clayton, VIC 3169, Australia
Sam Y.S. Yang
Affiliation:
CSIRO Manufacturing Flagship, Private Bag 10, Clayton, VIC 3169, Australia
Marina Pervukhina
Affiliation:
CSIRO Energy Flagship, P.O. Box 1130, Bentley, WA 6102, Australia
Michael B. Clennell
Affiliation:
CSIRO Energy Flagship, P.O. Box 1130, Bentley, WA 6102, Australia
Lionel Esteban
Affiliation:
CSIRO Energy Flagship, P.O. Box 1130, Bentley, WA 6102, Australia
Sarah C. Irvine
Affiliation:
Swiss Light Source, Paul Scherrer Institut, 5232 Villigen PSI, Switzerland Department of Mechanical & Aerospace Engineering, Monash University, Wellington Road, Clayton, VIC 3800, Australia
Karen K. Siu
Affiliation:
Australian Synchrotron, 800 Blackburn Rd, Clayton, VIC 3168, Australia School of Physics, Monash University, Wellington Rd, Clayton VIC 3800, Australia
Anton S. Maksimenko
Affiliation:
Australian Synchrotron, 800 Blackburn Rd, Clayton, VIC 3168, Australia
Andrew M. Tulloh
Affiliation:
CSIRO Manufacturing Flagship, Private Bag 10, Clayton, VIC 3169, Australia
*
*Corresponding author. [email protected]
Get access

Abstract

Data-constrained modeling is a method that enables three-dimensional distribution of mineral phases and porosity in a sample to be modeled based on micro-computed tomography scans acquired at different X-ray energies. Here we describe an alternative method for measuring porosity, synchrotron K-edge subtraction using xenon gas as a contrast agent. Results from both methods applied to the same Darai limestone sample are compared. Reasonable agreement between the two methods and with other porosity measurements is obtained. The possibility of a combination of data-constrained modeling and K-edge subtraction methods for more accurate sample characterization is discussed.

Type
Materials Applications and Techniques
Copyright
© Microscopy Society of America 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agbogun, H.M.D., Al, T.A. & Hussein, E.M.A. (2013). Three dimensional imaging of porosity and tracer concentration distributions in a dolostone sample during diffusion experiments using X-ray micro-CT. J Contam Hydrol 145, 4453.CrossRefGoogle Scholar
Andrew, M., Bijeljic, B. & Blunt, M.J. (2014). Pore-scale contact angle measurements at reservoir conditions using X-ray microtomography. Adv Water Resour 68, 2431.Google Scholar
Arns, C.H., Bauget, F., Ghous, A., Sakellariou, A., Senden, T.J., Sheppard, A.P., Sok, R.M., Pinczewski, W.V., Kelly, J.C. & Knackstedt, M.A. (2005). Digital core laboratory: Petrophysical analysis from 3D imaging of reservoir core fragments. Petrophysics 46(4), 260277.Google Scholar
Bera, B., Gunda, N.S.K., Mitra, S.K. & Vick, D. (2012). Characterization of nanometer-scale porosity in reservoir carbonate rock by focused ion beam-scanning electron microscopy. Microsc Microanal 18(1), 171178.CrossRefGoogle Scholar
Bera, B., Mitra, S.K. & Vick, D. (2011). Understanding the micro structure of Berea sandstone by the simultaneous use of micro-computed tomography (micro-CT) and focused ion beam-scanning electron microscopy (FIB-SEM). Micron 42(5), 412418.Google Scholar
Boone, M.A., Kock, T.D., Bultreys, T., Schutter, G.D., Vontobel, P., Hoorebeke, L.V. & Cnudde, V. (2014). 3D mapping of water in oolithic limestone at atmospheric and vacuum saturation using X-ray micro-CT differential imaging. Mater Charact 97, 150160.Google Scholar
Chen, W.H., Yang, S.Y.S., Xiao, T.Q., Mayo, S.C., Wang, Y.D. & Wang, H.P. (2014). A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative analysis of anthracite coal microstructure. J Synch Rad 21(3), 586593.Google Scholar
Cnudde, V. & Boone, M. (2013). High-resolution X-ray computed tomography in geosciences: A review of the current technology and applications. Earth Sci Rev 123, 117.CrossRefGoogle Scholar
Fusi, N. & Martinez-Martinez, J. (2013). Mercury porosimetry as a tool for improving quality of micro-CT images in low porosity carbonate rocks. Eng Geol 166, 272282.CrossRefGoogle Scholar
Ghous, A., Senden, T., Sok, R., Sheppard, A., Pinczewski, W. & Knackstedt, M. (2007). Characterisation of microporosity in carbonate cores. In Middle East Regional SPWLA Symposium: Petrophysics and Brown Field Resource Optimization, Society of Petrophysicists and Well Log Analysts (SPWLA), USA (Ed.), pp. 11. Abu Dhabi.Google Scholar
Gureyev, T.E., Nesterets, Y., Ternovski, D., Thompson, D., Wilkins, S.W., Stevenson, A.W., Sakellariou, A. & Taylor, J.A. (2011). Toolbox for advanced X-ray image processing. Adv Computat Met X-Ray Opt II 8141, 81410B.Google Scholar
Ketcham, R.A. & Iturrino, G.J. (2005). Nondestructive high-resolution visualization and measurement of anisotropic effective porosity in complex lithologies using high-resolution X-ray computed tomography. J Hydrol 302(1–4), 92106.CrossRefGoogle Scholar
Klobes, P., Riesemeier, H., Meyer, K., Goebbels, J. & Hellmuth, K.H. (1997). Rock porosity determination by combination of X-ray computerized tomography with mercury porosimetry. Fresenius J Anal Chem 357(5), 543547.CrossRefGoogle Scholar
Mayo, S.C., Tulloh, A.M., Trinchi, A. & Yang, S.Y.S. (2012). Data-constrained microstructure characterization with multispectrum X-ray micro-CT. Microsc Microanal 18(3), 524530.Google Scholar
Nugent, K., Gureyev, T., Cookson, D., Paganin, D. & Barnea, Z. (1996). Quantitative phase imaging using hard X rays. Phys Rev Lett 77(14), 2961.Google Scholar
Paganin, D., Mayo, S.C., Gureyev, T.E., Miller, P.R. & Wilkins, S.W. (2002). Simultaneous phase and amplitude extraction from a single defocused image of a homogeneous object. J Microsc 206, 3340.Google Scholar
Pinczewski, W.V., Kelly, J.C. & Knackstedt, M.A. (2005). Digital core laboratory: Petrophysical analysis from 3D imaging of reservoir core fragments. Petrophysics 46(4), 260277.Google Scholar
Snigirev, A., Snigireva, I., Kohn, V., Kuznetsov, S. & Schelokov, I. (1995). On the possibilities of X‐ray phase contrast microimaging by coherent high‐energy synchrotron radiation. Rev Sci Instrum 66(12), 54865492.Google Scholar
Trinchi, A., Yang, Y.S., Huang, J.Z., Falcaro, P., Buso, D. & Cao, L.Q. (2012). Study of 3D composition in a nanoscale sample using data-constrained modelling and multi-energy X-ray CT. Model Simul Mater Sci Eng 20(1), 015013.Google Scholar
Umetani, K., Ueda, K., Takeda, T., Akisada, M., Nakajima, T. & Anno, I. (1991). Iodine K-edge dual-energy imaging for subtraction angiography using synchrotron radiation and a 2-dimensional detector. Nucl Instrum Met Phys Res Sec A 301(3), 579588.Google Scholar
Van Geet, M., Swennen, R. & Wevers, M. (2000). Quantitative analysis of reservoir rocks by microfocus X-ray computerised tomography. Sediment Geol 132(1–2), 2536.CrossRefGoogle Scholar
Wang, H.P., Yang, Y.S., Wang, Y.D., Yang, J.L., Jia, J. & Nie, Y.H. (2013 a). Data-constrained modelling of an anthracite coal physical structure with multi-spectrum synchrotron X-ray CT. Fuel 106, 219225.Google Scholar
Wang, Y.D., Yang, Y.S., Cole, I., Trinchi, A. & Xiao, T.Q. (2013 b). Investigation of the microstructure of an aqueously corroded zinc wire by data-constrained modelling with multi-energy X-ray CT. Mater Corros-Werkstoffe Und Korrosion 64(3), 180184.Google Scholar
Wang, Y.D., Yang, Y.S., Xiao, T.Q., Liu, K.Y., Clennell, B., Zhang, G.Q. & Wang, H.P. (2013 c). Synchrotron-based data-constrained modeling analysis of microscopic mineral distributions in limestone. Int J Geosci 4, 344351.Google Scholar
Wilkins, S.W., Gureyev, T.E., Gao, D., Pogany, A. & Stevenson, A.W. (1996). Phase-contrast imaging using polychromatic hard X-rays. Nature 384(6607), 335338.Google Scholar
Withjack, E.M. & Akervoll, I. (1988). Computed tomography studies of 3-D miscible displacement behavior in a laboratory five-spot model. In SPE Annual Technical Conference and Exhibition, SPE-18096-MS. Houston, TX: Society of Petroleum Engineers.Google Scholar
Yang, S., Mayo, S., Pervukhina, M., Clennell, B., Esteban, L., Irvine, S., Siu, K., Maksimenko, A. & Tulloh, A. (2014 a). Carbonate rock X-ray CT and DCM microstructure data. v1. CSIRO. Data Collection. 10.4225/08/5476787E08766.Google Scholar
Yang, S., Tulloh, A., Chu, C., Chen, F., & Taylor, J. (2014 b). DCM - A software platform for advanced 3D materials modelling, characterisation and visualization. v9. CSIRO. Data Collection. 10.4225/08/55371BD329075.Google Scholar
Yang, Y., Tulloh, A., Muster, T., Trinchi, A., Mayo, S. & Wilkins, S. (2010 a). Data-constrained microstructure modeling with multi-spectrum X-ray CT. In SPIE 7804, Developments in X-Ray Tomography VII, 78040N, doi: 10.1117/12.861964.Google Scholar
Yang, Y.S., Gureyev, T.E., Tulloh, A., Clennell, B. & Pervukhina, M. (2010 b). Feasibility of a data-constrained prediction of hydrocarbon reservoir sandstone microstructures. Meas Sci Technol 21, 047001.Google Scholar
Yang, Y.S., Liu, K.Y., Mayo, S., Tulloh, A., Clennell, M.B. & Xiao, T.Q. (2013 a). A data-constrained modelling approach to sandstone microstructure characterisation. J Petrol Sci Eng 105, 7683.CrossRefGoogle Scholar
Yang, Y.S., Tulloh, A., Chen, F., Liu, K.Y., Clennell, B. & Taylor, J. (2013 b). Data-constrained characterization of sandstone microstructures with multi-energy X-ray CT. 11th International Conference on X-Ray Microscopy (XRM2012). J Phys: Conf Ser. 463, 012048.Google Scholar