Method for Predicting Bound Water Saturation in Tight Sandstone Reservoirs Using Morphology and Fractal Models

Abstract

The nuclear magnetic resonance T2 spectrum was used to identify the T2 cut-off value, which is the key to determining the irreducible water saturation of a reservoir. In this paper, the saturation and centrifugal T2 spectra of sandstone and coal samples were used to explore the correlation between each parameter and the T2 cut-off value, using a single fractal dimension, a multifractal dimension and a spectral morphology discrimination method. The conclusions are as follows: (1) The T2 spectra of nine sandstone samples in this paper can be divided into four types. Type A is represented by sample 2, wherein the T2 spectrum shows a bimodal state and the area of the right T2 spectrum (2.5~100 ms) is larger than that of the left T2 spectrum (T2 < 2.5 ms), indicating that the sample has good pore connectivity and belongs to the macroporous development sample. The B-type T2 spectrum is unimodal, and the pore connectivity is poor, indicating that it is a large-pore development sample. The T2 spectrum of the C-type sample is unimodal, and the pore connectivity is very poor, indicating that it is a mesoporous development sample. The T2 spectrum of the D-type sample shows a single peak state, and the main T2 is distributed within 0.1~2.5 ms. The pore connectivity is very poor, which indicates that it belongs to the small pore development type sample. (2) The single fractal model shows that, compared with other single fractal parameters, D2 increases with the increase in the T2 cut-off value, but the correlation is weak. Therefore, it is not feasible to predict the T2 cut-off value using the single fractal dimension parameter. (3) The multifractal model shows that D−10–D10 increases linearly with the increase in D−10–D0, but there is no obvious linear correlation between D0–D10 and D−10–D10, indicating that the low pore volume area in this kind of sample controls the overall heterogeneity of pore distribution. (4) The related parameters affecting the T2 cut-off value include D−10–D10, D−10/D10, D−10–D0, TM and D2. Therefore, based on the above five parameters, a T2 cut-off value prediction model is constructed. The T2 cut-off value calculated by the model is highly consistent with the experimental value, which proves the reliability of the model.