Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K

Liu Leisong; Chen Zhigang; Chen Jie; Ma Hui; Sun Xing; Wang Yuzhu; Han Yuchun

doi:doi:10.11648/j.ogce.20180605.12

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Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K

Liu Leisong, Chen Zhigang, Chen Jie, Ma Hui, Sun Xing, Wang Yuzhu, Han Yuchun

Published in International Journal of Oil, Gas and Coal Engineering (Volume 6, Issue 5)

Received: 30 May 2018 Accepted: 9 August 2018 Published: 10 September 2018

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Abstract

In Block K of South Turgay Basin in central Kazakhstan, the development of target, Aibalin, is controlled by the boundary of graben (especially rift-type stratigraphy-lithology assemblage). The Aibalin Fm is mainly developed with delta and lakeshore swamp facies, and composed of grey sandstone, siltstone, shale and coal-bearing strata, with extensive carbonized vegetal debris. Moreover, it contains thin and horizontally-variable reservoirs. Coal beds affect seismic survey greatly. Because of the influence of tuning effect in seismic data, thin sandstone reservoir distribution and physical properties cannot be reflected accurately in seismic data. Meanwhile, thin sandstone reservoir cannot be effectively predicted through seismic-based conventional inversion methods and processes. In this paper, a new prediction process for thin sandstone reservoir in this block is proposed, contributing to the effective prediction of thin sandstone reservoir distribution and physical properties. Firstly, sensitive parameters for lithology interpretation are defined and lithology interpretation template was established, through comprehensive analysis of drilling, logging and seismic data. Secondly, seismic wave impedance Bayes inversion genetic algorithm and cloud transform gamma attribute prediction technique are used to derive wave impedance and gamma data volume. Finally, the wave impedance and gamma data volume are combined with lithology interpretation template to predict the physical properties of the reservoirs.

Published in	International Journal of Oil, Gas and Coal Engineering (Volume 6, Issue 5)
DOI	10.11648/j.ogce.20180605.12
Page(s)	88-95
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Coal Measure Strata, Sensitive Parameter, Genetic Method, Cloud Transform

References

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APA Style

Liu Leisong, Chen Zhigang, Chen Jie, Ma Hui, Sun Xing, et al. (2018). Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K. International Journal of Oil, Gas and Coal Engineering, 6(5), 88-95. https://doi.org/10.11648/j.ogce.20180605.12

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ACS Style

Liu Leisong; Chen Zhigang; Chen Jie; Ma Hui; Sun Xing, et al. Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K. Int. J. Oil Gas Coal Eng. 2018, 6(5), 88-95. doi: 10.11648/j.ogce.20180605.12

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AMA Style

Liu Leisong, Chen Zhigang, Chen Jie, Ma Hui, Sun Xing, et al. Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K. Int J Oil Gas Coal Eng. 2018;6(5):88-95. doi: 10.11648/j.ogce.20180605.12

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@article{10.11648/j.ogce.20180605.12,
  author = {Liu Leisong and Chen Zhigang and Chen Jie and Ma Hui and Sun Xing and Wang Yuzhu and Han Yuchun},
  title = {Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K},
  journal = {International Journal of Oil, Gas and Coal Engineering},
  volume = {6},
  number = {5},
  pages = {88-95},
  doi = {10.11648/j.ogce.20180605.12},
  url = {https://doi.org/10.11648/j.ogce.20180605.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ogce.20180605.12},
  abstract = {In Block K of South Turgay Basin in central Kazakhstan, the development of target, Aibalin, is controlled by the boundary of graben (especially rift-type stratigraphy-lithology assemblage). The Aibalin Fm is mainly developed with delta and lakeshore swamp facies, and composed of grey sandstone, siltstone, shale and coal-bearing strata, with extensive carbonized vegetal debris. Moreover, it contains thin and horizontally-variable reservoirs. Coal beds affect seismic survey greatly. Because of the influence of tuning effect in seismic data, thin sandstone reservoir distribution and physical properties cannot be reflected accurately in seismic data. Meanwhile, thin sandstone reservoir cannot be effectively predicted through seismic-based conventional inversion methods and processes. In this paper, a new prediction process for thin sandstone reservoir in this block is proposed, contributing to the effective prediction of thin sandstone reservoir distribution and physical properties. Firstly, sensitive parameters for lithology interpretation are defined and lithology interpretation template was established, through comprehensive analysis of drilling, logging and seismic data. Secondly, seismic wave impedance Bayes inversion genetic algorithm and cloud transform gamma attribute prediction technique are used to derive wave impedance and gamma data volume. Finally, the wave impedance and gamma data volume are combined with lithology interpretation template to predict the physical properties of the reservoirs.},
 year = {2018}
}

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TY  - JOUR
T1  - Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K
AU  - Liu Leisong
AU  - Chen Zhigang
AU  - Chen Jie
AU  - Ma Hui
AU  - Sun Xing
AU  - Wang Yuzhu
AU  - Han Yuchun
Y1  - 2018/09/10
PY  - 2018
N1  - https://doi.org/10.11648/j.ogce.20180605.12
DO  - 10.11648/j.ogce.20180605.12
T2  - International Journal of Oil, Gas and Coal Engineering
JF  - International Journal of Oil, Gas and Coal Engineering
JO  - International Journal of Oil, Gas and Coal Engineering
SP  - 88
EP  - 95
PB  - Science Publishing Group
SN  - 2376-7677
UR  - https://doi.org/10.11648/j.ogce.20180605.12
AB  - In Block K of South Turgay Basin in central Kazakhstan, the development of target, Aibalin, is controlled by the boundary of graben (especially rift-type stratigraphy-lithology assemblage). The Aibalin Fm is mainly developed with delta and lakeshore swamp facies, and composed of grey sandstone, siltstone, shale and coal-bearing strata, with extensive carbonized vegetal debris. Moreover, it contains thin and horizontally-variable reservoirs. Coal beds affect seismic survey greatly. Because of the influence of tuning effect in seismic data, thin sandstone reservoir distribution and physical properties cannot be reflected accurately in seismic data. Meanwhile, thin sandstone reservoir cannot be effectively predicted through seismic-based conventional inversion methods and processes. In this paper, a new prediction process for thin sandstone reservoir in this block is proposed, contributing to the effective prediction of thin sandstone reservoir distribution and physical properties. Firstly, sensitive parameters for lithology interpretation are defined and lithology interpretation template was established, through comprehensive analysis of drilling, logging and seismic data. Secondly, seismic wave impedance Bayes inversion genetic algorithm and cloud transform gamma attribute prediction technique are used to derive wave impedance and gamma data volume. Finally, the wave impedance and gamma data volume are combined with lithology interpretation template to predict the physical properties of the reservoirs.
VL  - 6
IS  - 5
ER  -

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Author Information

Liu Leisong

Geological Research Center, Bureau of Geophysical Prospect, Zhuozhou, China
Chen Zhigang

Geological Research Center, Bureau of Geophysical Prospect, Zhuozhou, China
Chen Jie

Geological Research Center, Bureau of Geophysical Prospect, Zhuozhou, China
Ma Hui

Geological Research Center, Bureau of Geophysical Prospect, Zhuozhou, China
Sun Xing

Geological Research Center, Bureau of Geophysical Prospect, Zhuozhou, China
Wang Yuzhu

Geological Research Center, Bureau of Geophysical Prospect, Zhuozhou, China
Han Yuchun

Geological Research Center, Bureau of Geophysical Prospect, Zhuozhou, China

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Plain Text BibTeX RIS

APA Style

Liu Leisong, Chen Zhigang, Chen Jie, Ma Hui, Sun Xing, et al. (2018). Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K. International Journal of Oil, Gas and Coal Engineering, 6(5), 88-95. https://doi.org/10.11648/j.ogce.20180605.12

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ACS Style

Liu Leisong; Chen Zhigang; Chen Jie; Ma Hui; Sun Xing, et al. Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K. Int. J. Oil Gas Coal Eng. 2018, 6(5), 88-95. doi: 10.11648/j.ogce.20180605.12

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AMA Style

Liu Leisong, Chen Zhigang, Chen Jie, Ma Hui, Sun Xing, et al. Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K. Int J Oil Gas Coal Eng. 2018;6(5):88-95. doi: 10.11648/j.ogce.20180605.12

Copy | Download

@article{10.11648/j.ogce.20180605.12,
  author = {Liu Leisong and Chen Zhigang and Chen Jie and Ma Hui and Sun Xing and Wang Yuzhu and Han Yuchun},
  title = {Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K},
  journal = {International Journal of Oil, Gas and Coal Engineering},
  volume = {6},
  number = {5},
  pages = {88-95},
  doi = {10.11648/j.ogce.20180605.12},
  url = {https://doi.org/10.11648/j.ogce.20180605.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ogce.20180605.12},
  abstract = {In Block K of South Turgay Basin in central Kazakhstan, the development of target, Aibalin, is controlled by the boundary of graben (especially rift-type stratigraphy-lithology assemblage). The Aibalin Fm is mainly developed with delta and lakeshore swamp facies, and composed of grey sandstone, siltstone, shale and coal-bearing strata, with extensive carbonized vegetal debris. Moreover, it contains thin and horizontally-variable reservoirs. Coal beds affect seismic survey greatly. Because of the influence of tuning effect in seismic data, thin sandstone reservoir distribution and physical properties cannot be reflected accurately in seismic data. Meanwhile, thin sandstone reservoir cannot be effectively predicted through seismic-based conventional inversion methods and processes. In this paper, a new prediction process for thin sandstone reservoir in this block is proposed, contributing to the effective prediction of thin sandstone reservoir distribution and physical properties. Firstly, sensitive parameters for lithology interpretation are defined and lithology interpretation template was established, through comprehensive analysis of drilling, logging and seismic data. Secondly, seismic wave impedance Bayes inversion genetic algorithm and cloud transform gamma attribute prediction technique are used to derive wave impedance and gamma data volume. Finally, the wave impedance and gamma data volume are combined with lithology interpretation template to predict the physical properties of the reservoirs.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Application of Reservoir-Predicting Technique to Thin Sandstones in Coal-Bearing Strata in Block K
AU  - Liu Leisong
AU  - Chen Zhigang
AU  - Chen Jie
AU  - Ma Hui
AU  - Sun Xing
AU  - Wang Yuzhu
AU  - Han Yuchun
Y1  - 2018/09/10
PY  - 2018
N1  - https://doi.org/10.11648/j.ogce.20180605.12
DO  - 10.11648/j.ogce.20180605.12
T2  - International Journal of Oil, Gas and Coal Engineering
JF  - International Journal of Oil, Gas and Coal Engineering
JO  - International Journal of Oil, Gas and Coal Engineering
SP  - 88
EP  - 95
PB  - Science Publishing Group
SN  - 2376-7677
UR  - https://doi.org/10.11648/j.ogce.20180605.12
AB  - In Block K of South Turgay Basin in central Kazakhstan, the development of target, Aibalin, is controlled by the boundary of graben (especially rift-type stratigraphy-lithology assemblage). The Aibalin Fm is mainly developed with delta and lakeshore swamp facies, and composed of grey sandstone, siltstone, shale and coal-bearing strata, with extensive carbonized vegetal debris. Moreover, it contains thin and horizontally-variable reservoirs. Coal beds affect seismic survey greatly. Because of the influence of tuning effect in seismic data, thin sandstone reservoir distribution and physical properties cannot be reflected accurately in seismic data. Meanwhile, thin sandstone reservoir cannot be effectively predicted through seismic-based conventional inversion methods and processes. In this paper, a new prediction process for thin sandstone reservoir in this block is proposed, contributing to the effective prediction of thin sandstone reservoir distribution and physical properties. Firstly, sensitive parameters for lithology interpretation are defined and lithology interpretation template was established, through comprehensive analysis of drilling, logging and seismic data. Secondly, seismic wave impedance Bayes inversion genetic algorithm and cloud transform gamma attribute prediction technique are used to derive wave impedance and gamma data volume. Finally, the wave impedance and gamma data volume are combined with lithology interpretation template to predict the physical properties of the reservoirs.
VL  - 6
IS  - 5
ER  -

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