TITLE:
Quantitative and Comprehensive Prediction of Shale Oil Sweet Spots in Qingshankou Formation, Songliao Basin
AUTHORS:
Tiantian Wu, Xin Bai, Fei Shang, Haiyan Zhou, Lan Wang, Xuexian Zhou, Zhi Zhong, Zhi Yang, Jinyou Zhang, Xinyang Cheng, Peiyu Zhang, Ruiqian Chen
KEYWORDS:
Songliao Basin, Qingshankou Formation, Shale Oil, Sweet Spot, Artificial Neural Network
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.11 No.5,
May
31,
2023
ABSTRACT: The mud shale of Qingshankou Formation in Songliao Basin is the main rock
source and contains rich shale oil resources. The successful development of
shale oil depends on evaluating and optimizing the “sweet spots”. To accurately identify and optimize the favorable
sweet spots of shale oil in Qingshankou Formation, Songliao Basin, the original
logging data were preprocessed in this paper. Then the thin mud shale
interlayer of Qingshankou Formation was identified effectively by using the
processed logging data. Based on the artificial neural network method, the
mineral content of mud shale in Qingshankou Formation was predicted. The
lithofacies were identified according to the mineral and TOC content. Finally,
a three-dimensional (3-D) model of total organic carbon (TOC), vitrinite
reflectance (Ro), mineral content, and rock of Qingshankou Formation in
Songliao Basin was established to evaluate and predict the favorable sweet
spots of shale oil in the study area. The results show that there are a lot of
calcareous and siliceous thin interlayers in Qingshankou Formation, and TOC
content is generally between 2% and 3%. Ro is the highest in Gulong sag,
followed by Sanzhao sag. The lithofacies mainly consists of felsic shale and
mixed shale, mainly in the first member of Qingshankou Formation. Comprehensive
analysis shows that shale oil development potential is enormous in the eastern part
of Sanzhao Sag and the northern part of Gulong Sag.