| NMR logging not only can evaluate permeability of stratum, but also can gettotal porosity of rock, saturation of oil, gas or water, coefficient of diffusion, viscosityof oil. It is usually the one of the several effective methods for complex lithology. Sothe NMR logging is the fastest growing logging method in recent ten years. It has nowbecome an important part of the comprehensive geophysical logging methods forpetroleum and natural gas exploration.NMR inversion method is the core content of NMR logging theory. NMR datainversion gets transverse relaxation time and other magnetic parameters of pore fluidin stratum by inversion of the spin echo trains from NMR logging. Porosity,permeability and saturation of oil, gas or water can be computed by these magneticparameters. A train of echoes is a multiple exponential relaxation signal which iscomposed of many single exponential relaxation signals. The mathematical model ofthe magnetic parameters inversion by spin echo trains is a Fredholm’s integralequation of the first kind. The numerical solution of the integral equation alwaysreduces it to a system of linear algebraic equations, and then we can use singularvalue decomposition or regularization method to solve those linear algebraicequations. In practical application the existing algorithms have many problems, suchas the requirement of signal to noise is too high, calculation speed is slow orspectrums are not continuous. On the other hand, as a result of logging instrumentperformance and underground environmental constraints, the signal to noise ratio of NMR logging is very low. So it is necessary to improve the existing algorithm for afast inversion algorithm which is able to adapt low signal to noise ratio.An improved SVD algorithm named linear cutoff algorithm is proposed byanalysis of the relationship between the best number of singular value retained andSNR. It can make the inversion of T2spectrum quickly and effectively, and it isstabler than the traditional SVD algorithm: the difference of the T2spectrumsinversed by linear cutoff algorithm with different signal to noise ratio is not veryapparent. The linear cutoff algorithm can adapt to low SNR (SNR>10) T2spectruminversion. That means the T2spectrum inversed by linear cutoff algorithm can be realeven in low SNR. A formula of regularization factor is proposed by analyzing therelationship between the improved SVD and regularization method. The empiricalregularization factor proposed in this paper is closer to the average value of the bestfactors in low SNR. In addition, the influence of initial value to simultaneous iterativereconstruction inversion algorithm is investigated. Construct a simultaneous iterativereconstruction inversion algorithm, which initial value is the result of linear cutoffalgorithm. We compare the improved algorithm with foreign software results to verifythe effectiveness of the algorithm. Analyze the effects of methods of pre-assignedrelaxation bins and the number of pre-assigned relaxation bins on inversions.Construct the improved SVD algorithm with30or50logarithmic spaced timeconstants. Practical examples show that the improved algorithm with logarithmic30or50logarithmic spaced time constants have better identification capacity to largepore under the condition of low SNR. It can give the true relaxation distributions forthe formation pore structure better.Several methods for fluids typing using nuclear magnetic resonance data arediscussed. The concrete implementation process of T1, T2search, fluid typing basedon difference of T1, fluid typing based on difference of T2and TDA are introduced.Software for NMR data inversion and iterpretation is developed. This softwarecan do the inversion of T2spectrum and the iterpretation of the result of inversion. Itcan provide reliable geological data for oilfield exploration and development. |
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