Abstract

Organic matter (OM) in continental shale serves as both the source of oil and gas and the storage space in unconventional petroleum systems. However, directly identifying the types of organic matter under SEM is challenging when simultaneously observing minerals and pores. Kong2 Member(E2k2) of Paleogene in Cangdong sag of Bohai Bay basin is a typical continental shale oil layer in China. Based on the positioning observation technology combining field emission scanning electron microscope (FE-SEM) and fluorescence microscope, the in-situ SEM identification and observation of macerals were carried out, and the identification methods and characteristics of organic macerals were summarized. The results show that: (1) Organic macerals in E2k2 shale are divided into vitrinite, inertinite, liptinite and solid bitumen by external morphology, hardness, brightness, color, protrusion, pore and fracture development of organic matter, and further subdivided into multiple subcategories. Based on the SEM charging effect of the remaining oil, it is further confirmed that the shale movable oil and oil generation potential developed by lipoid group is the largest, while the shale movable oil and oil generation potential developed by vitrinite group and inertinite group is the worst; (2) The organic pores include primary pores and secondary pores. The pores of primary organic matter are derived from the biological structure of primary organic matter, and the secondary organic pores are developed during the thermal maturation of oily organic matter. Clay mineral catalysis, difference of hydrocarbon generation potential and residual pores of primary organic matter control the development of organic pores; (3) Calcareous-dolomitic shale and felsic shale are typical lithology formed in relatively dry and humid climate respectively, and the types of organic macerals are significantly different. Although the former has weak total hydrocarbon generation, it has stronger oil generation potential and is worthy of attention in dessert prediction and exploration.

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