Two-dimensional NMR relaxometry study of pore space characteristics of carbonate rocks from a Permian aquifer

Schoenfelder, Wiete; Gläser, Hans-Reinhard; Mitreiter, Ivonne; Stallmach, Frank

doi:10.1016/j.jappgeo.2008.03.005

Cited by 28 publications

(10 citation statements)

References 31 publications

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“…It is this relationship that is exploited in the P2DRM. NMR experiments on brine-saturated core samples of many different types of sandstones and carbonates have shown consistency with the equation pair[4,20,41,42]. These experiments empirically show that for large pores, , , and the ratio , while for small pores, the experiments are consistent with the relation , hereafter…”

supporting

confidence: 54%

Obtaining T 1 - T 2 distribution functions from 1-dimensional T 1 and T 2 measurements: The pseudo 2-D relaxation model

Williamson

Röding

Galvosas

et al. 2016

Journal of Magnetic Resonance

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We present the pseudo 2-D relaxation model (P2DRM), a method to estimate multidimensional probability distributions of material parameters from independent 1-D measurements. We illustrate its use on 1-D T1 and T2 relaxation measurements of saturated rock and evaluate it on both simulated and experimental T1-T2 correlation measurement data sets. Results were in excellent agreement with the actual, known 2-D distribution in the case of the simulated data set. In both the simulated and experimental case, the functional relationships between T1 and T2 were in good agreement with the T1-T2 correlation maps from the 2-D inverse Laplace transform of the full 2-D data sets. When a 1-D CPMG experiment is combined with a rapid T1 measurement, the P2DRM provides a double-shot method for obtaining a T1-T2 relationship, with significantly decreased experimental time in comparison to the full T1-T2 correlation measurement.

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supporting

confidence: 54%

Obtaining T 1 - T 2 distribution functions from 1-dimensional T 1 and T 2 measurements: The pseudo 2-D relaxation model

Williamson

Röding

Galvosas

et al. 2016

Journal of Magnetic Resonance

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“…With decreasing T 1 (corresponding to decreasing pore sizes) the 2D distribution function shows an increasing ratio T 1 /T 2 from two to three. These ratios agree well with several data obtained for porous media like rocks [16] and cements [17] and with theoretical considerations [17,18]. An important observation is the lack of any detectable cross-peak contribution.…”

Section: Fig (3) Showssupporting

confidence: 91%

Relaxation in a Natural Soil: Comparison of Relaxometric Imaging, T1– T2 Correlation and Fast-Field Cycling NMR

Haber‐Pohlmeier¹

2010

TOMRJ

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Longitudinal and transverse relaxation times are used to characterise the pore system of a natural Kaldenkirchen sandy loam. Here we present new results obtained by relaxometric imaging (MEMS) and two-dimensional T 1 -T 2 correlation relaxometry, and compare these with available T 1 -relaxation time distributions of water obtained by the analysis of fast field cycling relaxometry (FFC) data. The soil shows relatively broad bimodal distribution functions P(T 1 ) and P(T 2 ) with a T 1 /T 2 ratio of about 2:1. The average T 1 as well as the spatial distribution, which are obtained from the relaxometric imaging corresponds well to the relaxometric results. From the analysis of the field dependent FFC data at low field including T 1 data obtained at high field the basic locally averaged relaxation mechanism is derived from the dispersion curve, i.e. the dependence of the relaxation rate from the magnetic field strength over five orders of magnitudes. From this we conclude that two-dimensional diffusion at locally flat surfaces controls the relaxation, i.e. the shapes of the distribution functions are controlled by surface relaxation.

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“…In Figure , we attempted to show that high Fe(III) content in the Sherwood cores could explain the elevated

T_{2 p}^{- 1}

values and justify the use of a separate

ρ_{2 italiceff}

for these cores; however, Figure also shows high Fe(III) content for AC and PB, cores that do not display elevated

T_{2p}^{- 1}

values in Figure b, suggesting that Fe(III) content alone cannot be used to justify using an additional

ρ_{2 italiceff}

parameter. Accounting for the uncertainty in k models resulting from the choice of

D_{(|, +)}^{S}

and

ρ_{2 italiceff}

is essential before these k models can be applied in the field and future work should focus on nonsandstone materials (e.g., carbonates [e.g., Halisch et al ., ; Schoenfelder et al ., ], unconsolidated sediments [e.g., Weller et al ., ; Dlugosch et al ., ]) with a range of mineralogies.…”

Section: Discussionmentioning

confidence: 99%

A laboratory study to estimate pore geometric parameters of sandstones using complex conductivity and nuclear magnetic resonance for permeability prediction

Osterman

Keating

Binley

et al. 2016

Water Resources Research

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We estimate parameters from the Katz and Thompson permeability model using laboratory complex electrical conductivity (CC) and nuclear magnetic resonance (NMR) data to build permeability models parameterized with geophysical measurements. We use the Katz and Thompson model based on the characteristic hydraulic length scale, determined from mercury injection capillary pressure estimates of pore throat size, and the intrinsic formation factor, determined from multisalinity conductivity measurements, for this purpose. Two new permeability models are tested, one based on CC data and another that incorporates CC and NMR data. From measurements made on forty‐five sandstone cores collected from fifteen different formations, we evaluate how well the CC relaxation time and the NMR transverse relaxation times compare to the characteristic hydraulic length scale and how well the formation factor estimated from CC parameters compares to the intrinsic formation factor. We find: (1) the NMR transverse relaxation time models the characteristic hydraulic length scale more accurately than the CC relaxation time ( normalR2 of 0.69 and 0.33 and normalized root mean square errors (NRMSE) of 0.16 and 0.21, respectively); (2) the CC estimated formation factor is well correlated with the intrinsic formation factor (NRMSE=0.23). We demonstrate that that permeability estimates from the joint‐NMR‐CC model (NRMSE=0.13) compare favorably to estimates from the Katz and Thompson model (NRMSE=0.074). This model advances the capability of the Katz and Thompson model by employing parameters measureable in the field giving it the potential to more accurately estimate permeability using geophysical measurements than are currently possible.

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Two-dimensional NMR relaxometry study of pore space characteristics of carbonate rocks from a Permian aquifer

Cited by 28 publications

References 31 publications

Obtaining T 1 - T 2 distribution functions from 1-dimensional T 1 and T 2 measurements: The pseudo 2-D relaxation model

Obtaining T 1 - T 2 distribution functions from 1-dimensional T 1 and T 2 measurements: The pseudo 2-D relaxation model

Relaxation in a Natural Soil: Comparison of Relaxometric Imaging, T1– T2 Correlation and Fast-Field Cycling NMR

A laboratory study to estimate pore geometric parameters of sandstones using complex conductivity and nuclear magnetic resonance for permeability prediction

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