1887
Volume 12 Number 2
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

A laboratory study was conducted to explore the relationship between pore size, pore surface‐area‐to‐volume ratio and NMR relaxation rates and to determine which geometric parameter best predicts the average NMR relaxation rate. NMR relaxation measurements were collected on water‐saturated glass beads with controlled sets of bead diameters and surface areas. Four sets of beads were used with average diameters ranging from 55‐1125 m. The surface areas of the glass beads were altered by chemically treating the beads with a weak acid, a strong base and a cream commonly used to etch glass surfaces. Following the chemical treatments, the surface areas of the beads were quantified with krypton BET gas adsorption measurements. It was found that, for the range of bead diameters used in this study, relaxation did not strictly occur in the fast diffusion regime and, as such, the relaxation time associated with the peak of the largest mode in the distribution was found to more accurately represent the pore‐scale geometry than the mean log relaxation time. Using the relaxation time associated with this peak, the results from this study show that the pore surface‐area‐to‐volume ratio is a significantly better predictor of the surface relaxation rate than the mean grain radius ( = 0.014).

Loading

Article metrics loading...

/content/journals/10.3997/1873-0604.2013064
2013-07-01
2024-04-20
Loading full text...

Full text loading...

References

  1. AllenD., FlaumC., RamakrishnanT., BedfordJ., CastelijnsK., FairhurstD. et al. 2000. Trends in NMR logging. Oilfield Review12(2), 2–19.
    [Google Scholar]
  2. ArnsC.2004. A comparison of pore size distributions derived by NMR and X‐ray‐CT techniques. Physica A: Statistical Mechanics and its Applications339(1–2), 159–165.
    [Google Scholar]
  3. ASTM Standard D2434‐68
    ASTM Standard D2434‐68 . 2006. Standard test method for permeability of granular soils (Constant Head). ASTM International, West Conshohocken, PA. doi:10.1520/D0422
  4. BlochF., HansenW. and PackardM.1946. The nuclear induction experiment. Physical ReviewA70(7–8), 474–485.
    [Google Scholar]
  5. BrownsteinK. and TarrC.1979. Importance of classical diffusion in NMR studies of water in biological cells. Physical ReviewA19(6), 2446–2453.
    [Google Scholar]
  6. Bryar, T., DaughneyC. and KnightR.2000. Paramagnetic effects of iron (III) species on nuclear magnetic relaxation of fluid protons in porous media. Journal of Magnetic Resonance142(1), 74–85.
    [Google Scholar]
  7. BryarT. and KnightR.2003. Laboratory studies of the effect of sorbed oil on proton nuclear magnetic resonance. Geophysics68(3), 942–948.
    [Google Scholar]
  8. ChalikakisK., NielsenM., LegchenkoA. and HagensenT.2009. Investigation of sedimentary aquifers in Denmark using the magnetic resonance sounding method (MRS). Comptes Rendus Geosciences341(10–11), 918–927.
    [Google Scholar]
  9. DlubacK., KnightR. and KeatingK.2013. A numerical study of the relationship between NMR relaxation and permeability in materials with large pores. Near Surface Geophysics. doi:10.3997/1873‐0604.2013042 (in press)
    [Google Scholar]
  10. DlugoschR., GüntherT., Mueller‐PetkeM. and YaramanciU.2012. A general model for predicting hydraulic conductivity of unconsolidated material using nuclear magnetic resonance. 5th International MRS Workshop, Hannover, Germany.
    [Google Scholar]
  11. EisenhauerJ.G.2003. Regression through the origin. Teaching Statistics25(3), 76–80.
    [Google Scholar]
  12. HaynesJ.1962. Use of krypton for surface area measurements. The Journal of Physical Chemistry66, 182–185.
    [Google Scholar]
  13. HillsB.P. and SnaarJ.E.M.1995. Water proton studies of pore microstructure in monodisperse glass bead beds. Molecular Physics84, 141–157.
    [Google Scholar]
  14. HinediZ.R., ChangA.C., AndersonM.A. and BorchardtD.B.1997. Quantification of microporosity by nuclear magnetic resonance relaxation of water imbibed in porous media. Water Resources Research33(12), 2697–2704.
    [Google Scholar]
  15. JaegerF., RudolphN., LangF. and SchaumannG.2008. Effects of soil solution’s constituents on proton NMR relaxometry of soil samples. Soil Science Society of America Journal72(6), 1694–1707. doi:10.2136/sssaj2007.0427
    [Google Scholar]
  16. KeatingK. and FalzoneS.2013. Relating NMR relaxation time distributions to void size distributions for unconsolidated sand packs. Geophysics78(6), D461–D472. doi:10.1190/geo2012‐0461.1
    [Google Scholar]
  17. KeatingK. and KnightR.2007. A laboratory study to determine the effect of iron oxides on proton NMR measurements. Geophysics72(E27–E32). doi:10.1190/1.2399445
    [Google Scholar]
  18. KeatingK. and KnightR.2012. The effect of spatial variation in surface relaxivity on nuclear magnetic resonance relaxation rates. Geophysics77(5), E365–E377. doi:10.1190/geo2011‐0462.1
    [Google Scholar]
  19. KleinbergR. and HorsfieldM.1990. Transverse relaxation processes in porous sedimentary rock. Journal of Magnetic Resonance88, 9–19.
    [Google Scholar]
  20. KnightR., GrunewaldE., IronsT., DlubacK., SongY., BachmanH.N. et al. 2012. Field experiment provides ground truth for surface nuclear magnetic resonance measurement. Geophysical Research Letters39(3). L03304. doi:10.1029/2011GL050167
    [Google Scholar]
  21. LaTorracaG. and DunnK.1993. Predicting permeability from nuclear magnetic resonance and electrical properties measurements. Society of Core Analysts, Conference Paper 9312.
    [Google Scholar]
  22. LegchenkoA., BaltassatJ., BeauceA. and BernardJ.2002. Nuclear magnetic resonance as a geophysical tool for hydrogeologists. Journal of Applied Geophysics50(1–2), 21–46.
    [Google Scholar]
  23. MinagawaH., NishikawaY., IkedaI., MiyazakiK., TakaharaN., SakamotoY. et al. 2008. Characterization of sand sediment by pore size distribution and permeability using proton nuclear magnetic resonance measurement. Journal of Geophysical Research113(B7), 1–9. doi:10.1029/2007JB005403
    [Google Scholar]
  24. MohnkeO. and YaramanciU.2008. Pore size distributions and hydraulic conductivities of rocks derived from magnetic resonance sounding relaxation data using multiexponential decay time inversion. Journal of Applied Geophysics66, 73–81. doi:10.1016/j.jappgeo.2008.05.002
    [Google Scholar]
  25. NimmoJ.R.1997. Modeling structural influences on soil water retention. Soil Science Society of America Journal61(3), 712–719.
    [Google Scholar]
  26. PapeH., TillichJ. and HolzM.2006. Pore geometry of sandstone derived from pulsed field gradient NMR. Journal of Applied Geophysics58(3), 232–252.
    [Google Scholar]
  27. RamakrishnanT., SchwartzL. and FordhamE.1998. Forward models for nuclear magnetic resonance in carbonate rocks. Transactions of the SPWLA 39th Annual Logging Symposium, 1–12.
    [Google Scholar]
  28. RyuS.2009. Effect of inhomogeneous surface relaxivity, pore geometry and internal field gradients on NMR logging: Exact and perturbative theories and numerical investigations. Society of Petrophysicists and Well Log Analysts 50th Annual Logging Symposium.
    [Google Scholar]
  29. StallmachF., VogtC., KärgerJ., HelbigK. and JacobsF.2002Fractal Geometry of Surface Areas of Sand Grains Probed by Pulsed Field Gradient NMR. Physical Review Letters88(10), 105505. doi:10.1103/ PhysRevLett.88.105505
    [Google Scholar]
  30. StingaciuL.R., PohlmeierA., BlümlerP., WeihermüllerL., Van DusschotenD., StapfS. and VereeckenH.2009. Characterization of unsaturated porous media by highfield and low‐field NMR relaxometry. Water Resources Research45(8), W08412. doi:10.1029/ 2008WR007459
    [Google Scholar]
  31. StraleyC. and SchwartzL. M.1996. Transverse relaxation in random bead packs: Comparison of experimental data and numerical simulations. Magnetic Resonance Imaging14(7), 999–1002.
    [Google Scholar]
  32. SwansonR.D., SinghaK., Day‐LewisF.D., BinleyA., KeatingK. and HaggertyR.2012. Direct geoelectrical evidence of mass transfer at the laboratory scale. Water Resources Research48, W10543. doi:10.1029/2012WR012431
    [Google Scholar]
  33. TimurA.1969. Producible porosity and permeability of sandstones investigated through nuclear magnetic resonance principles. The Log Analyst10(1), 3–11.
    [Google Scholar]
  34. VogtC., GalvosasP., KlitzschN. and StallmachF.2002. Self‐diffusion studies of pore fluids in unconsolidated sediments by PFG NMR. Journal of Applied Geophysics50(4), 455–467. doi:10.1016/S0926‐9851(02)00195‐7
    [Google Scholar]
  35. WalshD.O., GrunewaldE., TurnerP. and FridI.2010. Javelin: A slimhole and microhole NMR logging tool. FastTimes15, 67–72.
    [Google Scholar]
  36. WalshD., TurnerP., GrunewaldE., ZhangH., ButlerJ., RebouletE. et al. 2013. A small diameter NMR logging tool for groundwater investigations. Groundwater. (in press) doi:10.1111/gwat.12024
    [Google Scholar]
  37. WhittallK., BronskillM. and HenkelmanR.M.1991. Investigation of analysis techniques for complicated NMR relaxation data. Journal of Magnetic Resonance95, 221–234.
    [Google Scholar]
  38. YaramanciU. and LangeG.2002. Aquifer characterisation using surface NMR jointly with other geophysical techniques at the Nauen/Berlin test site. Journal of Applied Geophysics50, 47–55.
    [Google Scholar]
  39. YaramanciU., LangeG. and KnodelK.1999. Surface NMR within a geophysical study of an aquifer at Haldensleben (Germany). Geophysical Prospecting47, 923–943.
    [Google Scholar]
  40. ZenginH., HuB., SiddiquiJ.A. and OttenbriteR.M.2006. Surface modification of glass beads with poly (acrylic acid). Polymers for Advanced Technologies17(5), 372–378. doi:10.1002/pat.721
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.3997/1873-0604.2013064
Loading
/content/journals/10.3997/1873-0604.2013064
Loading

Data & Media loading...

  • Article Type: Research Article

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error