Robust determination of surface relaxivity from nuclear magnetic resonance DT2 measurements

Luo, Zhi Xiang; Paulsen, Jeffrey L.; Song, Yi‐Qiao

doi:10.1016/j.jmr.2015.08.002

Cited by 38 publications

(16 citation statements)

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“…The degree to which diffusion is restricted depends on the pore size and diffusion time (Sen, 2004). Models have been developed to relate DðtÞ to S∕V, pore size, and surface relaxivity , enabling the estimation of these parameters by measuring DðtÞ for a range of diffusion times (e.g., Latour et al, 1993;Hürlimann et al, 1994;Vogt et al, 2002;Fleury, 2007;Duschl et al, 2015;Luo et al, 2015). The D-T 2 distributions have also been used directly to obtain information about S∕V, the distribution of pore sizes, and ρ Zielinski et al, 2010;Liu et al, 2014).…”

Section: Diffusion In Porous Materialsmentioning

confidence: 99%

Investigating the effect of internal gradients on static gradient nuclear magnetic resonance diffusion measurements

2017

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Nuclear magnetic resonance (NMR) methods can be used to measure the diffusion coefficient D of fluids. In porous materials, diffusion of the pore fluid is restricted by pore boundaries, such that D may be smaller than the diffusion coefficient of the bulk fluid. This reduction in D provides information about the geometry of the pore space. Significant overestimates of D can, however, occur due to internal gradients caused by magnetic susceptibility contrasts between the pore fluid and the solid phase. We have investigated the way in which internal gradients can impact the measured diffusion coefficient and obscure the link to pore geometry in unconsolidated sediments. We focus on measurements of D obtained with a static gradient diffusion-editing sequence, which can be used with NMR logging tools to measure D in subsurface sediments. Laboratory measurements of D measured with a diffusion-editing D-T 2 sequence indicate significant impacts from internal gradients, including D values several orders of magnitude larger than D of bulk water. The log-mean D values were found to be highly correlated with estimated internal gradient magnitudes and indicate no clear relationship to pore size. Samples with heterogeneous magnetic susceptibility of the solid phase indicate D distributions with multiple peaks, reflecting the nonuniform distribution of internal gradients in the sediment. We found evidence of high internal gradients impacting a majority of our samples, resulting in increased D values that do not reflect pore size even in samples with low magnetic susceptibility.

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Section: Diffusion In Porous Materialsmentioning

confidence: 99%

Investigating the effect of internal gradients on static gradient nuclear magnetic resonance diffusion measurements

2017

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“…38 Além disso, recentemente, publicouse um método para determinar a relaxatividade superficial magnética a partir de múltiplos mapas de correlação × . 3 Neste método, são mapeadas as dependências da difusão restrita e relaxação transversal para diferentes tempos de difusão ∆. Definindo-se assim uma difusão média para cada e ∆:…”

Section: Fonte: Elaborada Pelo Autorunclassified

“…No caso difusivo, a tortuosidade é definida pela razão / (∆), onde ∆ é o tempo de difusão, que deve ser suficientemente longo para que os deslocamentos das moléculas do fluido sejam afetados pela tortuosidade do meio. Portanto, dado o objetivo de analisar a eficiência do método proposto por Luo et al, 3 escolheu-se por, primeiramente, definir o sistema sob uma condição ideal.…”

Section: Coeficiente De Difusão Restrita Por Rmnunclassified

“…k é um parâmetro a ser determinado e deve variar para cada morfologia, dependendo do empacotamento dos grãos e a conectividade dos poros. Luo et al, 3 analisaram um conjunto de amostras, onde k variou entre 1,9 e 2,5. No caso apresentado na Figura 50, vemos que, considerando apenas o regime de tempos curtos de difusão, o parâmetro k tende a divergir, apresentando valor da ordem de 10 2 ou até mesmo 10 3 .…”

Section: Coeficiente De Difusão Restrita Por Rmnunclassified

“…No entanto, para fluidos confinados, os núcleos não podem difundir livremente pelo meio, sofrendo restrições da superfície dos poros. Sabe-se que para um tempo muito curto de ∆, em que os núcleos difundam uma distância ∆ muito menor que a escala • ¤*d* do poro, os únicos a sentirem alguma restrição são aqueles Para tempos de difusão longos o suficiente, onde os núcleos podem mover-se pela amostra e sentir a restrição média do meio ao movimento, a difusão resultante deve convergir de forma assintótica para (∞) = [ , onde [ (0 < [ < 1) é o recíproco da tortuosidade, erelacionado a conectividade dos poros 3,48. A tortuosidade difusiva está relacionada a dificuldade imposta pelo meio à difusão do fluido e, desta forma, definida porWong (1987) como a razão do coeficiente de difusão do fluido sem restrição, com relaxação ao coeficiente de difusão em meios restritos (difusão restrita).…”

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Modelagem físico-computacional da RMN em meios porosos - aplicações na indústria do petróleo

Lucas-Oliveira¹

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Extracting and understanding morphological properties of porous media is the focus of many areas of knowledge. In the case of oil industry, extracting the tridimensional morphological features of rock reservoirs allows the evaluation of the well productivity. Nuclear Magnetic Resonance (NMR) is one of the most important techniques applied in the study of reservoir rocks, capable of providing information about both their morphologies and the confined fluids. The most used parameters measured by NMR to study fluids in reservoir rocks are the magnetic relaxation and diffusion coefficients. Fluid molecules diffuse through the pore space and relax due to the fluid-surface interaction, macroscopically defined by the magnetic surface relaxivity ρ. The magnetic surface relaxation time TS is given in terms of three parameters: ρ, pore size distribution (PSD), and pore connectivity, being ρ extremely important and difficult to measure. The magnetic surface relaxivity can be determined by correlating TS to the PSD obtained from other techniques. However, in general, pore length scale defined by the molecular diffusion during the NMR magnetic relaxation is not equivalent to pore sizes measured, for example, by thin section and mercury intrusion. While the thin section offers essentially two-dimensional information about the pores, the mercury intrusion technique measures the bulk pore-throat size distribution. Due to this reason, a new NMR computational physics approach was proposed to correlate magnetic relaxation experimental data with those simulated using Digital Porous Media obtained by X-ray microcomputed tomography, which offers an alternative method to measure of ρ. This computational physics method, unlike the others, preserves the porous media morphology, molecular dynamics and NMR properties. Additionally, it is straightforward to implement advanced NMR pulse sequences using the proposed computational model, including those carried out under magnetic field gradients. Thus, it is possible to reproduce data resulting from NMR techniques applied in either laboratory or well-logging conditions. Therefore, the proposed computational physics model is capable of reproducing the NMR parameters of interest to the oil industry, most notably the longitudinal and transverse relaxation times T1 and T2, as well as the diffusion coefficient D and their correlations T1xT2, DxT2, and T2xT2.

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In vivo microscopic diffusional kurtosis imaging with symmetrized double diffusion encoding EPI

Paulsen

Zhou

et al. 2018

Magnetic Resonance in Med

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Robust determination of surface relaxivity from nuclear magnetic resonance DT2 measurements

Cited by 38 publications

References 34 publications

Investigating the effect of internal gradients on static gradient nuclear magnetic resonance diffusion measurements

Investigating the effect of internal gradients on static gradient nuclear magnetic resonance diffusion measurements

Modelagem físico-computacional da RMN em meios porosos - aplicações na indústria do petróleo

In vivo microscopic diffusional kurtosis imaging with symmetrized double diffusion encoding EPI

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