Application of quantitative grain fluorescence techniques to study subtle oil migration pathway of lithological reservoir

CHEN Dongxia1, ZHANG Jun1, LI Minggang1, PANG Xiongqi2

Front. Earth Sci. ›› 2007, Vol. 1 ›› Issue (4) : 498-504.

PDF(935 KB)
PDF(935 KB)
Front. Earth Sci. ›› 2007, Vol. 1 ›› Issue (4) : 498-504. DOI: 10.1007/s11707-007-0061-y

Application of quantitative grain fluorescence techniques to study subtle oil migration pathway of lithological reservoir

  • CHEN Dongxia1, ZHANG Jun1, LI Minggang1, PANG Xiongqi2
Author information +
History +

Abstract

This paper analyzes the quantitative grain fluorescence (QGF) and quantitative grain fluorescence on extract (QGF-E) properties of 101 rock samples by using quantitative grain fluorescence techniques. The samples are collected from five wells in tight sandstone and thin siltstone in the third sector of the Shahejie Formation in the Niuzhuang sag of the Dongying depression. It was observed that both the tight sandstone and thin siltstone show relatively high fluorescence intensity of hydrocarbon, which suggests that they are possibly good subtle oil-migration pathways in the present or geological time. These thin subtle oil-migration pathways afford important clues for the researches on hydrocarbon accumulation in lithological reservoirs in the middle and lower of Es3 in deep sag zone, which has the hydrocarbon source from the upper of Es4 when there is no apparent fault playing oil migration conduits to connect lithologic traps and deep source rocks. This study shows good prospect of QGF techniques in discriminating oil migration pathways and paleo-oil zones. The results of this study may be of great significance to the researches on hydrocarbon accumulation mechanism of subtle reservoirs in the Dongying depression and other areas.

Cite this article

Download citation ▾
CHEN Dongxia, ZHANG Jun, LI Minggang, PANG Xiongqi. Application of quantitative grain fluorescence techniques to study subtle oil migration pathway of lithological reservoir. Front. Earth Sci., 2007, 1(4): 498‒504 https://doi.org/10.1007/s11707-007-0061-y
AI Summary AI Mindmap
PDF(935 KB)

Accesses

Citations

Detail

Sections
Recommended

/