Quantitative Classification Technology for Karst Cave Fractures in Ordovician Carbonate Reservoirs in Tahe Area

Xin WANG , Guang-xiao DENG , Han-yong HUO , Zhen WANG , Huan WEN

Science Technology and Engineering ›› 2024, Vol. 24 ›› Issue (28) : 12016 -12024.

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Science Technology and Engineering ›› 2024, Vol. 24 ›› Issue (28) : 12016-12024 DOI: 10.12404/j.issn.1671-1815.2310110
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Quantitative Classification Technology for Karst Cave Fractures in Ordovician Carbonate Reservoirs in Tahe Area
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Abstract

The prediction accuracy of favorable fracture-cavity zones and reservoir development can be effectively improved through the quantitative classification of fracture-cavity bodies. The classification and grading of internal faults within fracture-cavity bodies were explored by applying fracture development models, fracture scale classification, and stress analysis based on structural curvature. A comprehensive classification of amplitude and wave impedance was undertaken, followed by large-sample calibration and verification with the aim of establishing a karst-cave grading standard. As an illustrative example, a specific area in Tahe was employed. The fault zone in this area was divided into eight grades based on its scale and stress properties. Indications from real drilling data show that the reservoir performance in the extension area is significantly better than that in the compression area. Additionally, the threshold value of seismic attributes for hole-cave classification was established within this study area. The specified energy ratio range of "beads-on-string" features is 54% ~ 62% for holes, and the energy ratio exceeds 62% for karst caves. Ultimately, the reliability of this technology was confirmed through real drilling analysis.

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carbonate reservoir / fracture-cavity space / amplitude energy / quantitative classification / stress analysis

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Xin WANG, Guang-xiao DENG, Han-yong HUO, Zhen WANG, Huan WEN. Quantitative Classification Technology for Karst Cave Fractures in Ordovician Carbonate Reservoirs in Tahe Area. Science Technology and Engineering, 2024, 24(28): 12016-12024 DOI:10.12404/j.issn.1671-1815.2310110

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