Evaluation on Hydrocarbon Source Rock of Lower Jurassic,Lenghu Area,Northern Margin of Qaidam Basin
Wen Xu
Abstract
Wen Xu
Abstract
By the theory of the organic petrology, this paper evaluates and researches the source rock of the Lower Jurassic in the Lenghu Area of the northern margin of the Qaidam Basin.The source rock's TOC content is between 2.58 to 6.7 percent, the hydrocarbon-generating potential is between 10.5 to 13.6 mg/g, the abundance of organic material is high, and it is high quality source rock; According to local source rock pyrolysis characteristics (relations of Tmax and IH, D%) and steranes C27-C28-C29 triangle figure, the organic material type is dominantly Ⅱ1, Ⅱ2, in part is Ⅰ, and the land-derived organic material is primary component, mixed with plankton. RO, CPI, C31 homohopanen-22 S / (22S +22 R), C2920S / (20S +20 R), C29 ββ / (αα + ββ) and Ts / Tm, these common parameters display regular changes with depth, revealing that most source rock in this area is in a low-mature and mature level, and a small portion is over-mature.
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By the theory of the organic petrology, this paper evaluates and researches the source rock of the Lower Jurassic in the Lenghu Area of the northern margin of the Qaidam Basin.The source rock's TOC content is between 2.58 to 6.7 percent, the hydrocarbon-generating potential is between 10.5 to 13.6 mg/g, the abundance of organic material is high, and it is high quality source rock; According to local source rock pyrolysis characteristics (relations of Tmax and IH, D%) and steranes C27-C28-C29 triangle figure, the organic material type is dominantly Ⅱ1, Ⅱ2, in part is Ⅰ, and the land-derived organic material is primary component, mixed with plankton. RO, CPI, C31 homohopanen-22 S / (22S +22 R), C2920S / (20S +20 R), C29 ββ / (αα + ββ) and Ts / Tm, these common parameters display regular changes with depth, revealing that most source rock in this area is in a low-mature and mature level, and a small portion is over-mature.
Key concepts: Source rock, Geology, Structural basin, Hydrocarbon, Geochemistry, Margin (machine learning), Total organic carbon, Mineralogy