A decomposition method of nuclear magnetic resonance T2 spectrum for identifying fluid properties

To make up for the limitations and improve the accuracy of 1D nuclear-magnetic-resonance (NMR) logging in the evaluation of formation fluid properties, 2D NMR logging has become the focus of research. Increasing the sequence and inversion parameters of the 2D NMR can effectively improve the antinoise properties and resolution of the inversion, but at the same time, the reduced inversion speed and increased memory occupied will put forward higher requirements on the computer configuration and add to the cost of calculation, which poses challenges to the application of the traditional 2D NMR inversion algorithms. In view of the above defects, we have developed a new fast 2D NMR inversion LSQR-RSVD hybrid algorithm, and we have used the nonnegative least-squares (LSQR) calculation result as the initial value of the RSVD inversion. Taking oil-water and gas-water models as examples, the 2D NMR inversion effects of ( T2, D), ( T1, T2) are analyzed in detail, and ( T1, D) is also discussed by several groups of echo trains with variable echo interval ( TE) and waiting time ( TW). Compared to the inversion algorithm commonly used, the new hybrid algorithm can improve the inversion speed and significantly reduce the memory occupancy. Its remarkable advantages can further promote the application of 2D and even multidimensional NMR logging in practice.

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Surface nuclear magnetic resonance signals recovery by integration of a non-linear decomposition method with statistical analysis

Geophysical Prospecting ◽

10.1111/1365-2478.12296 ◽

2015 ◽

Vol 64 (2) ◽

pp. 489-504 ◽

Cited By ~ 8

Author(s):

Reza Ghanati ◽

Mohammad Kazem Hafizi ◽

Mahdi Fallahsafari

Keyword(s):

Nuclear Magnetic Resonance ◽

Statistical Analysis ◽

Magnetic Resonance ◽

Decomposition Method ◽

Non Linear ◽

Nuclear Magnetic

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Rapid modeling of borehole measurements of nuclear magnetic resonance via spatial sensitivity functions

Geophysics ◽

10.1190/geo2020-0755.1 ◽

2021 ◽

pp. 1-149

Author(s):

Mohammad Albusairi ◽

Carlos Torres-Verdín

Keyword(s):

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Tool Geometry ◽

Processing Unit ◽

Spatial Sensitivity ◽

Sensitivity Functions ◽

Fluid Properties ◽

Mean Square Errors ◽

Mud Filtrate ◽

Nuclear Magnetic

Borehole measurements of nuclear magnetic resonance (NMR) are routinely used to estimate in situ rock and fluid properties. Conventional NMR interpretation methods often neglect bed-boundary and layer-thickness effects in the calculation of fluid volumetric concentrations and NMR relaxation-diffusion correlations. Such effects introduce notable spatial averaging of intrinsic rock and fluid properties across thinly bedded formations or in the vicinity of boundaries between layers exhibiting large property contrasts. Forward modeling and inversion methods can mitigate the aforementioned effects and improve the accuracy of true layer properties in the presence of mud-filtrate invasion and borehole environmental effects across spatially complex formations. We have developed a fast and accurate algorithm to simulate borehole NMR measurements using the concept of spatial sensitivity functions (SSFs) that honor NMR physics and incorporate tool, borehole, and formation geometry. Tool sensitivity maps are derived from a 3D multiphysics forward model that couples NMR tool properties, magnetization evolution, and electromagnetic propagation. In addition, a multifluid relaxation model based on Brownstein-Tarr’s equation is introduced to estimate layer NMR porosity decays and relaxation-diffusion correlations from pore-size-dependent rock and fluid properties. The latter model is convolved with the SSFs to reproduce borehole NMR measurements. The results indicate that NMR spatial sensitivity is controlled by porosity, electrical conductivity, excitation pulse duration, and tool geometry. We benchmark and verify the SSF-derived forward approximation against 3D multiphysics simulations for a series of synthetic cases with variable bed thickness and petrophysical properties, and in the presence of mud-filtrate invasion in a vertical well. Results indicate that the approximation can be executed in a few seconds in a central processing unit, by a factor of 1000 times faster than rigorous multiphysics calculations, with maximum root-mean-square errors of 1%.

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An emerging technology: Nuclear magnetic resonance microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010010706x ◽

1988 ◽

Vol 46 ◽

pp. 1000-1001

Author(s):

M.J. Hennessy ◽

E. Kwok

Keyword(s):

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Relaxation Times ◽

Basic Research ◽

Local Environment ◽

Magnetic Resonance Images ◽

Nmr Microscopy ◽

Mri Scans ◽

Temperature Relaxation ◽

Nuclear Magnetic

Much progress in nuclear magnetic resonance microscope has been made in the last few years as a result of improved instrumentation and techniques being made available through basic research in magnetic resonance imaging (MRI) technologies for medicine. Nuclear magnetic resonance (NMR) was first observed in the hydrogen nucleus in water by Bloch, Purcell and Pound over 40 years ago. Today, in medicine, virtually all commercial MRI scans are made of water bound in tissue. This is also true for NMR microscopy, which has focussed mainly on biological applications. The reason water is the favored molecule for NMR is because water is,the most abundant molecule in biology. It is also the most NMR sensitive having the largest nuclear magnetic moment and having reasonable room temperature relaxation times (from 10 ms to 3 sec). The contrast seen in magnetic resonance images is due mostly to distribution of water relaxation times in sample which are extremely sensitive to the local environment.

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Nuclear magnetic resonance microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100156110 ◽

1989 ◽

Vol 47 ◽

pp. 828-829

Author(s):

Paul C. Lauterbur

Keyword(s):

Magnetic Field ◽

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Magnetic Fields ◽

Signal To Noise ◽

Field Gradients ◽

Useful Signal ◽

Magnetic Field Gradients ◽

Observation Times ◽

Nuclear Magnetic

Nuclear magnetic resonance imaging can reach microscopic resolution, as was noted many years ago, but the first serious attempt to explore the limits of the possibilities was made by Hedges. Resolution is ultimately limited under most circumstances by the signal-to-noise ratio, which is greater for small radio receiver coils, high magnetic fields and long observation times. The strongest signals in biological applications are obtained from water protons; for the usual magnetic fields used in NMR experiments (2-14 tesla), receiver coils of one to several millimeters in diameter, and observation times of a number of minutes, the volume resolution will be limited to a few hundred or thousand cubic micrometers. The proportions of voxels may be freely chosen within wide limits by varying the details of the imaging procedure. For isotropic resolution, therefore, objects of the order of (10μm) may be distinguished.Because the spatial coordinates are encoded by magnetic field gradients, the NMR resonance frequency differences, which determine the potential spatial resolution, may be made very large. As noted above, however, the corresponding volumes may become too small to give useful signal-to-noise ratios. In the presence of magnetic field gradients there will also be a loss of signal strength and resolution because molecular diffusion causes the coherence of the NMR signal to decay more rapidly than it otherwise would. This phenomenon is especially important in microscopic imaging.

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