Methods and limitations of NMR data inversion for fluid typing

Sun, Bin

doi:10.1016/j.jmr.2004.04.009

Cited by 23 publications

(5 citation statements)

References 9 publications

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“…The most general fitting function is the sum (Eq. (7)) of many exponentials, from which the distribution of relaxation times can be extracted by inverse Laplace transformation [303][304][305][306][307][308][309][310],…”

Section: Evaluation Of the Echo Decay Envelopementioning

confidence: 99%

Mobile single-sided NMR

Blümich

Perlo

Casanova

2008

Progress in Nuclear Magnetic Resonance Spectroscopy

431

299

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Section: Evaluation Of the Echo Decay Envelopementioning

confidence: 99%

Mobile single-sided NMR

Blümich

Perlo

Casanova

2008

Progress in Nuclear Magnetic Resonance Spectroscopy

431

299

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“…Additionally, the intricate shale pore network may induce large internal magnetic field gradients and thus the Brownian motion of spins, leading to deviations from the fast diffusion regime (Hürlimann, 1998;Song, 2000Song, , 2003Washburn, 2014). These diffusion effects can be quantified based on laboratory 2D-NMR experiments, from which T 2 data corrections may be derived and the contribution from diffusion-induced signals estimated (Sun & Dunn, 2004). Unfortunately, obtaining sound results from borehole measurements remains impractical in shale reservoirs with the technology currently available, owing to the high levels of noise and consequently low SNR, and…”

Section: Relaxation Mechanisms In Shalesmentioning

confidence: 99%

Considerations for the acquisition and inversion of NMR T2 data in shales

Testamanti

Rezaee

2019

Journal of Petroleum Science and Engineering

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Low-field Nuclear Magnetic Resonance (NMR) is a non-invasive method widely used in the petroleum industry for the evaluation of reservoirs. Pore structure and fluid properties can be evaluated from transverse relaxation (T 2) distributions, obtained by inverting the raw NMR signal measured at subsurface conditions or in the laboratory. This paper aims to cast some light into the best practices for the T 2 data acquisition and inversion in shales, with a focus on the suitability of different inversion methods. For this purpose, the sensitivity to various signal acquisition parameters was evaluated from T 2 experiments using a real shale core plug. Then, four of the most common inversion methods were tested on synthetic T 2 decays, simulating components often associated with shales, and their performance was evaluated. These inversion algorithms were finally applied to real T 2 data from laboratory NMR measurements in brine-saturated shale samples. Methods using a unique regularization parameter were found to produce solutions with a good balance between the level of misfit and bias, but could not resolve adjacent fast T 2 components. In contrast, methods applying variable regularization-based on the noise level of the data-returned T 2 distributions with better accuracy at short times, in exchange of larger bias in the overall solution. When it comes to reproducing individual T 2 components characteristic of shales, the Butler-Reeds-Dawson (BRD) algorithm was found to have the best performance. In addition, our findings suggest that threshold T 2 cutoffs may be derived analytically, upon visual inspection of the T 2 distributions obtained by two different NMR inversion methods.

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“…Measurement methods have been developed for improved fluid typing based on special acquisition sequences and 1D relaxation inversion techniques (Chen et al 2000;Sun and Dunn 2004;. For general applications, however, the most promising techniques are based on 2D diffusion/ relaxation inversion of suites of NMR magnetization decays acquired with CPMG-like sequences and different echo times Sun and Dunn 2002).…”

Section: Model and Limits Of Nmr Petrophysical Interpretation Analytimentioning

confidence: 99%

Limits of 2D NMR Interpretation Techniques to Quantify Pore Size, Wettability, and Fluid Type: A Numerical Sensitivity Study

et al. 2006

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Two-dimensional (2D) NMR techniques have been proposed as efficient methods to infer a variety of petrophysical parameters, including mixed fluid saturation, in-situ oil viscosity, wettability, and pore structure. However, no study has been presented to quantify the petrophysical limitations of such methods. We address this problem by introducing a pore-scale framework to accurately simulate suites of NMR measurements acquired in complex rock/ fluid models. The general pore-scale framework considered in this paper is based on NMR random walks for multiphase fluid diffusion and relaxations, combined with Kovscek's pore-scale model for two-phase fluid saturation and wettability alteration. We use standard 2D NMR methods to interpret synthetic data sets for diverse petrophysical configurations, including two-phase saturations with different oil grades, mixed wettability, or carbonate pore heterogeneity.Results from our study indicate that for both water-wet and mixed-wet rocks, T 2 (transverse relaxation)/D (diffusion) maps are reliable for fluid typing without the need for independently determined cutoffs. However, significant uncertainty exists in the estimation of fluid type, wettability, and pore structure with 2D NMR methods in cases of mixed-wettability states. Only light oil wettability can be reliably detected with 2D NMR interpretation methods. Diffusion coupling in carbonate rocks introduces additional problems that cannot be circumvented with current 2D NMR techniques.In this equation, ␥ is the proton gyromagnetic ratio, G is the average magnitude of the background magnetic field gradient over the spatial zone of investigation, and TE the interecho time or the interval between two radio-frequency pulses.Limits of the Relaxation Model. The model described previously assumes that the protons relax within one pore independently from the surrounding pores. When the bulk and diffusion terms in the

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Methods and limitations of NMR data inversion for fluid typing

Cited by 23 publications

References 9 publications

Mobile single-sided NMR

Mobile single-sided NMR

Considerations for the acquisition and inversion of NMR T2 data in shales

Limits of 2D NMR Interpretation Techniques to Quantify Pore Size, Wettability, and Fluid Type: A Numerical Sensitivity Study

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