Quantitative characterization of organic and inorganic pores in shale based on FIB-SEM

The pore structures of shale in the Shahejie formation of Dongying depression were quantitatively characterized by FIB-SEM three-dimensional imaging technology. FIB-SEM was used to obtain high-resolution SEM images and through image registration, geometric correction and image segmentation, the organic pores and inorganic pores in the shale were distinguished. The pore space was converted into a structured pore network model via maximal ball method. Then, the pore size distributions and volume contributions of shale organic pores and inorganic pores, and the coordination number of the total pore network model were statistically analyzed via the pore network model. The results showed that due to the low thermal maturity of organic matter in the Shahejie formation, fewer organic pores were observed in the shale samples, and the number of pores was dominated by inorganic pores. Statistical analysis of the pore network model indicated that the studied shale samples considerably included mesopore (size of 2-50 nm) which accounted for 61.1%, but their contribution to the total pore volume was small (4.2%). Macropores (> 50 nm) accounted for a relatively small proportion (38.9%) in number, but they provided the main storage space (95.8%) for the shale oil and gas. The volume contribution of pores to the total pore space at a certain bin size is controlled by the combination of pore number and the pore size. The coordination numbers of the two samples were mainly 0 and 1, indicating that the pore connectivity was poor and isolated pores accounted for most part. These results are critical for further reliable petrophysical simulations based on shale digital rocks as well as for the accurate understanding of their petrophysical properties.

Automated summary

The pore structures of shale in the Shahejie formation of Dongying depression were quantitatively characterized using FIB-SEM three-dimensional imaging technology. Statistical analysis of the pore network model revealed the pore size distributions, volume contributions, and coordination numbers of shale organic pores and inorganic pores. These results are critical for further reliable petrophysical simulations and accurate understanding of the petrophysical properties of shale.