A new permeability estimation method based on blind source separation and NMR data

A new method for permeability estimation in tight sandstone formations based on the BSS algorithm and NMR data is proposed. BSS algorithm is introduced into the data processing of laboratory and downhole NMR data, and relaxation components with different NMR responses and pore size distributions can be obtained. The influence of pore structure on the percolation capacity is also discussed. The new method achieves great results in tight sandstone formations.

BSS algorithm refers to the process of separating various source signals from the observed signal when the theoretical model of the source signal is unknown and obtaining the best estimation of the source signal model and signal amplitude. When applying the BSS algorithm to NMR data processing, the laboratory and downhole NMR data can be considered as the observed signal, the relaxation components with specific NMR response can be considered as the source signal, and the proportions of different relaxation components can be considered as the signal amplitude. Based on the BSS algorithm, NMR responses and proportions of different components can be obtained.

We applied the BSS algorithm to the laboratory and downhole NMR data. Four pore types with different pore radius can be discriminated and their proportion can be extracted from the laboratory and downhole NMR data. The permeability of tight sandstone formation is affected by many factors and has poor correlations with the porosity. Based on the thin section observation, MICP and NMR analysis, the pore space of tight sandstone formation is complex and can be divided into micropore, mesopore, macropore and megapore. Pore structure is one of the main influential factors of permeability in tight sandstone formations. Relaxation components with the same NMR response and their proportions can be extracted from the BSS algorithm. Four relaxation components referring to different pore types can be obtained from laboratory and downhole NMR data. The permeability of tight sandstone formation is positively correlated with proportions of macropore and megapore, while negatively correlated with proportions of micropore and mesopore. A new permeability estimation method is established based on porosity, geometrical T₂ value, the sum proportion of macropore and megapore, and the sum proportion of micropore and mesopore. The new model achieves great results compared with the conventional models. The new method can be easily extended in other tight sandstone formations where the main influential factors of permeability are porosity and pore structure. Besides, laboratory experiments and core calibration can significantly improve the accuracy of permeability estimation.