A hybrid compression method for the NMR data based on window averaging and Discrete Cosine Transform

Abstract

A large amount of raw echo data is collected by NMR logging, especially in multi-dimensional NMR logging, and a direct inversion for the raw echo data is time-consuming, so the echo data collected need to be compressed before inversion to improve inversion speed. This paper proposes a multi-dimensional NMR data compression method based on Discrete Cosine Transform (DCT). Utilizing the energy concentration characteristics of DCT, the low-frequency information of the echo data is retained to realize the compression of raw echo data. On this basis, a hybrid compression (WAC-DCT) method is proposed, which uses the window averaging method (WAC) to pre-compress the raw echo data, and then uses the DCT compression method to compress the pre-compressed echo data again to achieve a high compression rate. The compression effects of the WAC method, the FastSVD method, the WAC-SVD method, the DCT method and the WAC-DCT method are compared by numerical simulation. The results show that some fluid information is lost in the DCT compression process with a low compression rate. The FastSVD method, the WAC-SVD method and the WAC-DCT method all have the characteristic of a high compression rate. When the number of compressed echoes is very small, the WAC-DCT method has obvious advantage in T1 distribution. Compared with the case of without compression, the WAC-DCT method not only ensures a high compression rate, but also effectively reduces the inversion time, which has a good application effect in multi-dimensional NMR data compression.