• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.235-244
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• 2012

Nuclear magnetic resonance (NMR) logging has been considered one of the most complicated nevertheless, one of the most powerful logging methods for the characterization on of both rocks and natural fluids in formation. NMR measures magnetized signals (polarization and relaxation) between the properties of hydrogen nucleus called magnetic moment and applied magnetic fields. The measured data set contains two important petrophysical properties such as density of hydrogen in the fluids inside the pore space and the distinct decay rate for fluid type. Therefore, after the proper data processing, key petrophysical information, not only the quantities and properties of fluids but also supplies of rock characterization in a porous medium, could be archived. Thus, based on this information, several ongoing researches are being developed in estimating aspects of reservoir productivity information, permeability and wettability since it is the key to having correct interpretation. This study goes through the basic theory of NMR at first, and then reviews NMR logging tools as well as their technical characteristics. This paper also briefly discusses the basic knowledge of NMR simulation algorithm by using Random walk.

• Geophysics and Geophysical Exploration
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• v.16 no.2
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• pp.97-105
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• 2013

Nuclear magnetic resonance (NMR) logging has become an important technique for formation evaluation, detecting interaction signals between H protons and applied magnetic fields. Measured decay signals called relaxation, contain important information about density of H protons and different decay rate due to its fluid type in the sensitive area. Thus, petrophysical information such as porosity, permeability and wettability can be estimated through the interpretation of the decay signals. Many researches on random walk simulation have been published, since a simulation method based on random walk for solving exponential decays was adapted in the early of 1950. This study first makes a review on NMR simulation researches, explains two most important methods: simulation with or without considering magnetic field gradient. Lastly, the study makes a comparison between NMR simulation responses with and without magnetic field gradient to show the importance to consider magnetic gradient to analyze the effects of magnetic gradients on NMR responses.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.941-947
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• 2018

Since the amplitudes of spin echo train in nuclear magnetic resonance logging (NMRL) are small and the signal to noise ratio (SNR) is also very low, this paper puts forward an improved de-noising algorithm based on wavelet transformation. The steps of this improved algorithm are designed and realized based on the characteristics of spin echo train in NMRL. To test this improved de-noising algorithm, a 32 points forward model of big porosity is build, the signal of spin echo sequence with adjustable SNR are generated by this forward model in an experiment, then the median filtering, wavelet hard threshold de-noising, wavelet soft threshold de-noising and the improved de-noising algorithm are compared to de-noising these signals, the filtering effects of these four algorithms are analyzed while the SNR and the root mean square error (RMSE) are also calculated out. The results of this experiment show that the improved de-noising algorithm can improve SNR from 10 to 27.57, which is very useful to enhance signal and de-nosing noise for spin echo train in NMRL.