1. A systematic characterization of multi-scale natural fractures in the Triassic Chang 8 Member, southwestern Ordos Basin, China is presented.
2. Three periods of strike-slip faults and four scales of natural fractures are identified, including mega-, macro-, meso-, and micro-scale fractures.
3. These multi-scale fractures influence the distribution and effectiveness of traps and reservoirs, as well as the sandstone physical properties and tight oil well production performance.
The article provides a comprehensive overview of the multi-scale natural fractures in the Triassic Chang 8 Member in the southwestern Ordos Basin, China. The authors present a detailed analysis based on outcrops, seismic reflections, well cores, well logs (image and conventional logging), casting thin sections, and scanning electron microscope observation to identify three periods of strike-slip faults and four scales of natural fractures. The article also discusses how these multi-scale fractures influence the distribution and effectiveness of traps and reservoirs, as well as the sandstone physical properties and tight oil well production performance.
The article is generally reliable with regards to its content; however there are some potential biases that should be noted. For example, it does not explore any counterarguments or alternative explanations for the findings presented in the article. Additionally, it does not provide any evidence for some of its claims or discuss any possible risks associated with its conclusions. Furthermore, it does not present both sides equally; instead it focuses solely on one side without exploring other perspectives or points of view. Finally, there is a lack of detail regarding some aspects such as how exactly each scale fracture influences reservoir performance or what kind of risks may be associated with their development.
In conclusion, while this article provides an informative overview on multi-scale natural fractures in tight sandstones from a case study in China’s Ordos Basin, there are some potential biases that should be taken into consideration when evaluating its trustworthiness and reliability.