Digital image recognition method of rock particle and pore system and its application

The thin-section micro images of sandstone are used as an example to investigate the image recognition, quantification and statistical analysis methods for rock particle and pore system. A binary image is obtained by using multi-color segmentation and spot removal operations. An improved seed algorithm is proposed, by which the pore throats with certain diameter can be closed automatically so as to divide and identify different pores and particles. A probability statistical method is introduced to calculate a three-dimensional sorting coefficient based on two-dimensional particle areas. The probability entropy and fractal dimension are used to describe the directionality and the variation of shape complexity, respectively. On the basis of theoretical researches, the software “Pore (Particle) and cracks analysis system” (PCAS) is developed. In the example, PCAS is applied in the investigation of formation mechanism of compaction bands in porous sandstone. The image processing results show that: (1) The particles and pores are recognized and quantified accurately, and micro structures of different sandstone can be described and distinguised effectively by using the statistical parameters; (2) In comparison with that with chevron compaction bands, the host rock with straight compaction bands has greater porosity, average pore area and better grain sorting. The research indicates the formation of compaction bands in sandstone is closely related to the micro structures, and the recognition and the analysis methods of micro structures are reliable.