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Near-Surface Geothermal Reservoir Imaging based on the Customized Dense Seismic Network

Abstract

Exploration of geothermal resources has become one of the major drivers for urbanization and economic transformation in southeast China, and it calls for temporal and spatial resolution improvements on conventional geophysical techniques under complex near-surface conditions. A dense seismic network including 192 sensors, with its aperture around 4.8 km, was deployed to record ambient noise for local-scale geothermal reservoir imaging in central Zhejiang Province, southeast China. With the ultrashort (less than 5 days) observation, a subset of the total station pairs was extracted to conduct seismic interferometry and dispersion measurements. This customized subnet was qualified to be an overdetermined system to achieve similar performance of entire network for the eikonal tomography with higher efficiency. The recorded high-frequency noise sources turned out to be rather homogeneous distributions, except for the dominant direction of northern Jinhua urban area. Azimuthal effects and wavelength restriction of dispersion measurements were quantified by simulating source–receiver responses under non-equipartitions of energy. The azimuth–velocity variations of field dataset verified that phase velocity measurements using the tested wavelength restriction were robust under different source–receiver orientations. The obtained phase velocity maps were comparable with the geological map. Furthermore, the inverted body wave velocities coincide well with the borehole data. Shear wave velocity profiles revealed corresponding fracture and depression structures of the reservoir. Finally, multiple geophysical properties delineate the shallow geothermy to be karst fissure water heated at certain earth temperature gradient.

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Acknowledgements

We appreciate the thorough revisions suggested by the Editor in Chief, Michael Rycroft, and two anonymous reviewers. This study is supported by the National Natural Science Foundation of China under Grant No. 41830103 and Zhejiang Geophysical and Geochemical Prospecting Academy. The seismic time series datasets utilized in this paper were archived in the Mendeley Data (Zhou et al. 2020).

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Correspondence to Jianghai Xia.

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Zhou, C., Xia, J., Pang, J. et al. Near-Surface Geothermal Reservoir Imaging based on the Customized Dense Seismic Network. Surv Geophys 42, 673–697 (2021). https://doi.org/10.1007/s10712-021-09642-8

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Keywords

  • Near surface
  • Rayleigh wave
  • Ambient noise
  • Geothermal reservoir
  • Dense network