Numerical Calculation of NMR Response for the 3D Digital Core Constructed with CT Images of the Tight Rock

Article Preview

Abstract:

The tight rock often has low porosity, low permeability and poor pore connectivity, which it is difficult for formation evaluation. Nuclear Magnetic Resonance (NMR) logging is widely used in fluid typing and reservoir parameters determination to provide the information of porosity, permeability and pore size distribution. NMR relaxation mechanisms are characterized by the pore-scale petrophysical models. Monte Carlo algorithm describes the Brownian motion of fluid molecules in pore space. In the paper we setup a 3D digital core of the tight sandstone with X-ray computer tomography (CT) images to model NMR response with Monte Carlo random walk algorithm. We compared T2 distributions from the numerical calculated pulse echo trains from the measurements. The results show that the simulated NMR response is consisted with the experiment.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1089-1092

Citation:

Online since:

January 2015

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Bergmann D., Dunn K., Theory of diffusion in porous medium with application to pulsed-field-gradient NMR, Phy. Rev. B, 50(1994) 9153-9156.

DOI: 10.1103/physrevb.50.9153

Google Scholar

[2] Toumelin E., Torres-Verdin C., Chen S., etc., Reconciling NMR measurements and numerical simulations: assessment of temperature and diffusive coupling effects on two-phase carbonate samples, Petrophysics, 44(2003)91-107.

Google Scholar

[3] Toumelin E., Torres-Verdin C., etc., Limits of 2D NMR interpretation techniques to quantify pore size, wettability and fluid type: a numerical sensitivity study", SPE J., 11(2006) 354-363.

DOI: 10.2118/90539-pa

Google Scholar

[4] Arns C. H., A comparison of pore size distributions derived by NMR and Xray-CT techniques, Physica A, 339(2004)159-165.

DOI: 10.1016/j.physa.2004.03.033

Google Scholar

[5] Arns C.H., Sheppard A. P., Sok R. M., etc., NMR petrophysical predictions on digitized core images, Petrophysics, 48(2007) 202-221.

Google Scholar

[6] Zheng L. H., and Chiew Y. C., Computer simulation of diffusion controlled reactions in dispersions of spherical sinks, J. of Che. Phy., 90(1989) 321-327.

DOI: 10.1063/1.456532

Google Scholar

[7] Iassonov P., Gebrenegus T., and Tuller M., Segentation of X-ray computed tomography images of porous material: a crucial step for characterization and quantitative analysis of pore structures, Water Resources Research, 45(2009) W09415.

DOI: 10.1029/2009wr008087

Google Scholar