Macrolithotype prediction and 3D geological modeling based on logging parameters

GUO Guangshan; LI Hao; TIAN Yongjing; DU Kai

doi:10.19388/j.zgdzdc.2022.01.13

Geological Survey of China > 2022 > 9(1): 125-130. > DOI: 10.19388/j.zgdzdc.2022.01.13

GUO Guangshan, LI Hao, TIAN Yongjing, et al. Macrolithotype prediction and 3D geological modeling based on logging parameters[J]. Geological Survey of China, 2022, 9(1): 125-130. DOI: 10.19388/j.zgdzdc.2022.01.13

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Macrolithotype prediction and 3D geological modeling based on logging parameters

Unconventional Research Center, CNOOC Research Institute, Beijing 100028, China

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Received Date: March 11, 2021
Revised Date: September 21, 2021

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Abstract

Abstract
In order to quantitatively distinguish the distribution characteristics of marcolithotypes, the authors in this research utilized the differences of logging response characteristics of different marcolithotypes to establish the marcolithotypes index HMLZ, according to the coal and rock description results of CBM parameter wells. The quantitative identification and verification of marcolithotypes of 30 wells in SZB block are completed through the discrimination index, and the 3D visualization of the spatial distribution characteristics of macrolithotypes are rea-lized using the stochastic modeling method. The results show that the HMLZ > 20.0 is bright coal, and the 10.0
- marcolithotypes,
- logging response,
- 3D geological modeling,
- SZB block

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References (17)

References

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