Particle size distribution analysis of mudstone based on digital image processing

Mudstone is becoming increasingly important for unconventional oil and gas development. The morphologi-cal characteristics of clastic are not only contributions to the 3D framework of mudstone, but they can clearly affect the physical properties of a mudstone reservoir, including surface area, pore-size distribution, and poros-ity. However, it is very difficult and time-consuming to measure the particle size distribution (PSD) of mudstone because of its small particle size and strong cementation. However, because of the importance of oil and gas extraction, it is urgent to develop a fast, accurate, and objective analysis method to measure the PSD of mud -stone. Based on a comparison of various PSD measurement methods commonly used in the energy industry and geology, the best PSD measurement method for mudstone should be digital image processing. Two imaging methods, trainable Weka segmentation (TWS) and black mudstone particle size measurement, were used to analyze sections of the early Silurian Longmaxi mudstone of China's Sichuan Basin. The PSD data obtained by manual measurement, TWS, and the contribution method are compared. Image analysis finds that the particle sizes of all samples fall in the range of coarse silt to clay, and the average sizes fall in the range of coarse silt to fine silt. The skewness, kurtosis, standard deviation, and other distribution characteristics parameters find mi-nor errors, and the relative error is less than 15%. The Pearson correlation coefficient of the 10th quantile of TWS, black mudstone particle size measure, and manual measurement were calculated, which found R2 values typically ranging between 0.64 and 0.87. Kolmogorov-Smirnov test results find that the data obtained by the three measurement methods are from the same distribution at the level of 0.05. Analytic results find that the method presented is effective, cost-efficient, and could avoid artificial errors.