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Gas reservoir detection by time-frequency analysis: a case study in a volcanic environment in China

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Abstract

Seismic waves will show attenuation of high-frequency energy when passing through the strata underground, and the phenomenon of high-frequency attenuation will be more obvious when the strata contain gas, then the energy will be relatively concentrated in the low-frequency part. Therefore, the detection of gas-bearing reservoirs can be realized through the “high-frequency attenuation” and “low-frequency anomaly” characteristics in single-frequency profiles. In this paper, an improved generalized S transform (IGST) is introduced to detect gas reservoirs by mapping “high-frequency attenuation” and “low-frequency anomaly” characteristics in a volcanic environment. As an improved time-frequency method, IGST shows higher time-frequency resolution compared with continuous wavelet transform (CWT) and S transform (ST). In order to confirm the reliability of the IGST method for gas-bearing detection, an anticlinal numerical model is built with different fluids in the strata. The model test result indicates that the IGST method can distinguish the gas-bearing reservoirs from water-bearing and dry layers. Field data application further confirms that the IGST is an effective method for gas-bearing reservoir detection in the volcanic environment. Through theoretical study and practical application, it is indicated that the IGST time-frequency method has an important guiding significance for gas-bearing reservoir detection in areas with few or no wells that are in an early stage of exploration in a volcanic environment.

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Acknowledgments

This research was supported by the Chongqing Natural Science Foundation General Program (no. cstc2019jcyj-msxmX0743 ).

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Authors and Affiliations

  1. School of Petroleum Engineering, Chongqing University of Science and Technology, Chongqing, 401331, China

    Jiabei Wang & Qing Chen

  2. School of Basic Sciences, Shengli College of China University of Petroleum, Dongying, 257061, China

    Jie Chi

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  1. Jiabei Wang
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  2. Jie Chi
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  3. Qing Chen
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Contributions

Jiabei Wang supervised the work and wrote the paper. Jie Chi wrote part of the program. Qing Chen contributed to revising the paper. All authors contributed to this work.

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Correspondence to Jiabei Wang.

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The authors declare that they have no competing interests.

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Responsible Editor: Narasimman Sundararajan

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Wang, J., Chi, J. & Chen, Q. Gas reservoir detection by time-frequency analysis: a case study in a volcanic environment in China. Arab J Geosci 14, 1239 (2021). https://doi.org/10.1007/s12517-021-07628-9

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