Skip to main content

Advertisement

SpringerLink
Log in

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

  • Published:
Surveys in Geophysics Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  • Bensen GD, Ritzwoller MH, Barmin MP, Levshin AL, Lin F, Moschetti MP, Shapiro NM, Yang Y (2007) Processing seismic ambient noise data to obtain reliable broad-band surface wave dispersion measurements. Geophys J Int 169(3):1239–1260. https://doi.org/10.1111/j.1365-246X.2007.03374.x

    Article  Google Scholar 

  • Carrier A, Lupi M, Fishanger F, Nawratil de Bono C (2018) Deep reaching electrical resistivity tomography (ERT) methods for middle-enthalpy geothermal prospection in the Geneva Basin, Switzerland. Geophysical Research Abstracts, vol 20, EGU2018–9865.

  • Castellanos JC, Clayton RW, Juarez A (2020) Using a time-based subarray method to extract and invert noise-derived body waves at long beach, California. J Geophys Res Solid Earth. https://doi.org/10.1029/2019JB018855

    Article  Google Scholar 

  • Cheng F, Xia J, Xu Y, Xu Z, Pan Y (2015) A new passive seismic method based on seismic interferometry and multichannel analysis of surface waves. J Appl Geophys 117:126–135. https://doi.org/10.1016/j.jappgeo.2015.04.005

    Article  Google Scholar 

  • Cheng F, Xia J, Luo Y, Xu Z, Wang L, Shen C, Liu R, Pan Y, Mi B, Hu Y (2016) Multichannel analysis of passive surface waves based on crosscorrelations. Geophysics 81(5):EN57–EN66

    Article  Google Scholar 

  • Cheng F, Xia J, Xu Z, Hu Y, Mi B (2018) Frequency–wavenumber (FK)- based data selection in high-frequency passive surface wave survey. Surv Geophys 39(4):661–682. https://doi.org/10.1007/s10712-018-9473-3

    Article  Google Scholar 

  • Cheng F, Xia J, Behm M, Hu Y, Pang J (2019) Automated Data Selection in the Tau–p Domain: Application to Passive Surface Wave Imaging. Surv Geophys 40(5):1211–1228. https://doi.org/10.1007/s10712-019-09530-2

    Article  Google Scholar 

  • Darnet M, Marquis G, Sailhac P (2006) Hydraulic stimulation of geothermal reservoirs: fluid flow, electric potential and microseismicity relationships. Geophys J Roy Astron Soc 166(1):438–444

    Article  Google Scholar 

  • de Ridder SAL, Biondi BL (2015) Ambient seismic noise tomography at Ekofisk. Geophysics 80(6):B167–B176. https://doi.org/10.1190/geo2014-0558.1

    Article  Google Scholar 

  • Dorbath L, Cuenot N, Genter A, Frogneux M (2009) Seismic response of the fractured and faulted granite of Soultz-sous-Forêts (France) to 5 km deep massive water injections. Geophys J Int 177(2):653–675. https://doi.org/10.1111/j.1365-246X.2009.04030.x

    Article  Google Scholar 

  • Fallahi MJ, Obermann A, Lupi M, Karyono K, Mazzini A (2017) The plumbing system feeding the Lusi eruption revealed by ambient noise tomography. J Geophys Res Solid Earth 122:8200–8213. https://doi.org/10.1002/2017JB014592

    Article  Google Scholar 

  • Fang H, Zhang H, Yao H, Allam A, Zigone D, Ben-Zion Y, Thurber C, van der Hilst RD (2016) A new algorithm for three-dimensional joint inversion of body wave and surface wave data and its application to the Southern California plate boundary region. J Geophys Res Solid Earth 121(5):3557–3569. https://doi.org/10.1002/2015JB012702

    Article  Google Scholar 

  • Gouédard P, Stehly L, Brenguier F, Campillo M, Colin de Verdière Y, Larose E, Margerin L, Roux P, Sánchez-Sesma FJ, Shapiro NM, Weaver RL (2008) Cross-correlation of random fields: Mathematical approach and applications. Geophys Prospect 56(3):375–393. https://doi.org/10.1111/j.1365-2478.2007.00684.x

    Article  Google Scholar 

  • Guglielmetti L, Comina C, Abdelfettah Y, Schill E, Mandrone G (2013) Integration of 3D geological modeling and gravity surveys for geothermal prospection in an alpine region. Tectonophysics 608:1025–1036

    Article  Google Scholar 

  • Hannemann K, Papazachos C, Ohrnberger M, Savvaidis A, Anthymidis M, Lontsi AM (2014) Three-dimensional shallow structure from high-frequency ambient noise tomography: new results for the Mygdonia basin-Euroseistest area, northern Greece. J Geophys Res Solid Earth 119:4979–4999

    Article  Google Scholar 

  • Hansen PC (1992) Analysis of discrete ill-posed problems by means of the L-curve. SIAM Rev 34(4):561–580

    Article  Google Scholar 

  • Herrmann RB (2013) Computer programs in seismology: An evolving tool for instruction and research. Seismol Res Lett 84(6):1081–1088. https://doi.org/10.1785/0220110096

    Article  Google Scholar 

  • Hetényi G, Molinari I, Clinton J et al. (2018) The AlpArray Seismic Network: A Large-Scale European Experiment to Image the Alpine Orogen. Surv Geophys 39:1009–1033. https://doi.org/10.1007/s10712-018-9472-4

    Article  Google Scholar 

  • Hu S, Wang J (2000) Heat flow, deep temperature and thermal structure across the orogenic belts in southeast China. J Geodyn 30:461–473

    Article  Google Scholar 

  • John BM (1974) Mesozoic thermal events in southeast China. Nature 248:480–483

    Article  Google Scholar 

  • Jousset P, Haberland C, Bauer K, Arnason K (2011) Hengill geothermal volcanic complex (Iceland) characterized by integrated geophysical observations. Geothermics 40(1):1–24

    Article  Google Scholar 

  • Kennett BLN, Sambridge MS, Williamson PR (1988) Subspace methods for large inverse problems with multiple parameter classes. Geophys J Int 94(2):237–247

    Article  Google Scholar 

  • Lawrence JF, Denolle M, Seats KJ, Prieto GA (2013) A numeric evaluation of attenuation from ambient noise correlation functions. Journal of Geophysical Research Solid Earth 118:6134–6145

    Article  Google Scholar 

  • Lehujeur M, Vergne J, Schmittbuhl J, Maggi A (2015) Characterization of ambient seismic noise near a deep geothermal reservoir and implications for interferometric methods: a case study in northern Alsace, France. Geotherm Energy 3(1):3

    Article  Google Scholar 

  • Lehujeur M, Vergne J, Maggi A, Schmittbuhl J (2016) Ambient noise tomography with non-uniform noise sources and low aperture networks: case study of deep geothermal reservoirs in northern Alsace, France. Geophys J Int 208:193–210. https://doi.org/10.1093/gji/ggw373

    Article  Google Scholar 

  • Lehujeur M, Vergne J, Schmittbuhl J, Zigone D, Le Chenadec A, Est of Team (2018) Reservoir imaging using ambient noise correlation from a dense seismic network. J Geophys Res Solid Earth, 123, 6671–6686. Doi: https://doi.org/10.1029/2018JB015440

  • Li C, Yao H, Fang H, Huang X, Wan K, Zhang H, Wang K (2016) 3D near-surface shear-wave velocity structure from ambient-noise tomography and borehole data in the Hefei urban area, China. Seismol Res Lett 87(4):882–892. https://doi.org/10.1785/0220150257

    Article  Google Scholar 

  • Li X, Main I, Jupe A (2018) Induced seismicity at the UK “hot dry rock” test site for geothermal energy production. Geophys J Int 214(1):331–344

    Article  Google Scholar 

  • Liaw AL, McEvilly TV (1977) The role of ambient microseisms in geothermal exploration. Geotherm Resour Counc Trans 1:187–188

    Google Scholar 

  • Lin FC, Moschetti MP, Ritzwoller MH (2008) Surface wave tomography of the western United States from ambient seismic noise: Rayleigh and Love wave phase velocity maps. Geophys J Int 173(1):281–298

    Article  Google Scholar 

  • Lin F-C, Li D, R, Clayton, & D. Hollis, (2013) High-resolution 3D shallow crustal structure in Long Beach, California: Application of ambient noise tomography on a dense seismic array. Geophysics 78(4):Q45–Q56

    Article  Google Scholar 

  • Liu Y, Xia J, Cheng F, Xi C, Shen C, Zhou C (2020) Pseudo-linear-array analysis of passive surface waves based on beamforming. Geophys J Int 221:640–650. https://doi.org/10.1093/gji/ggaa024

    Article  Google Scholar 

  • Luo Y, Yang Y, Xu Y, Xu H, Zhao K, Wang K (2015) On the limitations of interstation distances in ambient noise tomography. Geophys J Int 201:652–661

    Article  Google Scholar 

  • Martins JE, Ruigrok E, Draganov D, Hooper A, Hanssen RF, White RS, Soosalu H (2019) Imaging Torfajokull’s magmatic plumbing system with seismic interferometry and phase velocity surface wave tomography. J Geophys Res Solid Earth 124:2920–2940. https://doi.org/10.1029/2018JB016002

    Article  Google Scholar 

  • Mi B, Xia J, Bradford JH, Shen C (2020) estimating near-surface shear-wave-velocity structures via multichannel analysis of rayleigh and love waves: an experiment at the boise hydrogeophysical research site. Surv Geophys. https://doi.org/10.1007/s10712-019-09582-4

    Article  Google Scholar 

  • Muksin U, Bauer K, Haberland C (2013) Seismic Vp and Vp/vs structure of the geothermal area around Tarutung (North Sumatra, Indonesia) derived from local earthquake tomography. J Volcanol Geoth Res 260:27–42

    Article  Google Scholar 

  • Pan Y, Xia J, Xu Y, Xu Z, Cheng F, Xu H, Gao L (2016) Delineating shallow S -Wave velocity structure using multiple ambient-noise surface-wave methods: an example from Western Junggar, China. Bull Seismol Soc Am 106(2):327–336. https://doi.org/10.1785/0120150014

    Article  Google Scholar 

  • Pan Y, Gao L, Bohlen T (2019) High-resolution characterization of near-surface structures by surface-wave inversions: from dispersion curve to full waveform. Surv Geophys 40(2):167–195

    Article  Google Scholar 

  • Rawlinson N, Sambridge M (2003) Seismic traveltime tomography of the crust and lithosphere. Adv Geophys 46:81–199

    Article  Google Scholar 

  • Rawlinson N, Sambridge M (2005) The fast marching method: an effective tool for tomographic imaging and tracking multiple phases in complex layered media. Explor Geophys 36(4):341

    Article  Google Scholar 

  • Rawlinson N, Spakman W (2016) On the use of sensitivity tests in seismic tomography. Geophys J Int 205(2):1221–1243. https://doi.org/10.1093/gji/ggw084

    Article  Google Scholar 

  • Rost S, Thomas C (2002) Array seismology: Methods and applications. Rev Geophys 40(3):1008

    Article  Google Scholar 

  • Roux P, Sabra KG, Kuperman WA, Roux A (2005) Ambient noise cross correlation in free space: theoretical approach. J Acoust Soc Am 117:79–84

    Article  Google Scholar 

  • Sabra KG, Gerstoft P, Roux P, Kuperman AW, Fehler CM (2005) Surface wave tomography from microseisms in southern California. Geophys Res Lett 32:L14-311-1-L14-311–4

    Article  Google Scholar 

  • Sethian JA (1999) Fast marching methods. SIAM Rev 41(2):199–235

    Article  Google Scholar 

  • Shapiro NM, Campillo M (2004) Emergence of broadband Rayleigh waves from correlations of the ambient seismic noise. Geophys Res Lett 31:L07614. https://doi.org/10.1029/2004GL019491

    Article  Google Scholar 

  • Shapiro NM, Campillo M, Stehly L, Ritzwoller M (2005) High resolution surface wave tomography from ambient seismic noise. Science 307:1615–1618

    Article  Google Scholar 

  • Snieder R (2004) Extracting the Green’s function from the correlation of coda waves: A derivation based on stationary phase. Phys Rev E. https://doi.org/10.1103/PhysRevE.69.046610

    Article  Google Scholar 

  • Tibuleac I, Eneva M (2011) Seismic signature of the geothermal field at Soda Lake, Nevada, from ambient noise analysis. Geotherm Resour Counc Trans 35:1767–1771

    Google Scholar 

  • Tibuleac I, von Seggern DH, Louie JN, Anderson JG (2009) High resolution seismic velocity structure in the Reno Basin from ambient noise recorded by a variety of seismic instruments. Geotherm Resour Counc Trans 33:143–148

    Google Scholar 

  • Wang K, Luo Y, Yang Y (2016) Correction of phase velocity bias caused by strong directional noise sources in high-frequency ambient noise tomography: a case study in Karamay, China. Geophys J Int 205(2):715–727

    Article  Google Scholar 

  • Wang Y, Lin F-C, Schmandt B, Farrell J (2017) Ambient noise tomography across Mount St. Helens using a dense seismic array. J Geophys Res Solid Earth 122:4492–4508

    Article  Google Scholar 

  • Wang K, Lu L, Maupin V, Ding Z, Zheng C, Zhong S (2020) Surface wave tomography of northeastern tibetan plateau using beamforming of seismic noise at a dense array. J Geophys Res Solid Earth. https://doi.org/10.1029/2019JB018416

    Article  Google Scholar 

  • Wathelet M, Jongmans D, Ohrnberger M (2004) Surface-wave inversion using a direct search algorithm and its application to ambient vibration measurements. Near Surf Geophys 2(4):211–221

    Article  Google Scholar 

  • Xia J, Miller RD, Park CB (1999) Estimation of near-surface shear-wave velocity by inversion of Rayleigh waves. Geophysics 64(3):691–700. https://doi.org/10.1190/1.1444578

    Article  Google Scholar 

  • Xia J, Xu Y, Luo Y, Miller RD, Cakir R, Zeng C (2012) Advantages of using multichannel analysis of Love waves (MALW) to estimate near-surface shear-wave velocity. Surv Geophys 33(5):841–860

    Article  Google Scholar 

  • Xu Z, Mikesell TD, Xia J, Cheng F (2017) A comprehensive comparison between the refraction microtremor and seismic interferometry method for phase velocity estimation. Geophysics 82:1–43

    Article  Google Scholar 

  • Xu Z, Mikesell TD, Gribler G, Mordret A (2019) Rayleigh-wave multicomponent crosscorrelation-based source strength distribution inversion. Part 1: Theory and numerical examples. Geophys J Int. 218(3):1761–1780

    Article  Google Scholar 

  • Yanovskaya TB (1997) Resolution estimation in the problems of seismic ray tomography. Izv Phys Solid Earth 33(9):762–765

    Google Scholar 

  • Yao H, van der Hilst RD (2009) Analysis of ambient noise energy distribution and phase velocity bias in ambient noise tomography, with application to SE Tibet. Geophys J Int 179(2):1113–1132. https://doi.org/10.1111/j.1365-246X.2009.04329.x

    Article  Google Scholar 

  • Yao H, van der Hilst RD, de Hoop MV (2006) Surface-wave array tomography in SE Tibet from ambient seismic noise and two-station analysis—I. Phase velocity maps. Geophys J Int 166(2):732–744. https://doi.org/10.1111/j.1365-246X.2006.03028.x

    Article  Google Scholar 

  • Yin X, Xu H, Wang L, Hu Y, Shen C, Sun S (2016) Improving horizontal resolution of high-frequency surface-wave methods using travel-time tomography. J Appl Geophys 126:42–51

    Article  Google Scholar 

  • Young M, Rawlinson N, Arroucau P, Reading A, Tkalčić H (2011) High-frequency ambient noise tomography of southeast Australia: New constraints on Tasmania’s tectonic past. Geophys Res Lett 38:L13313

    Article  Google Scholar 

  • Zang A, Stephansson O, Stenberg L, Plenkers K, Specht S, Milkereit C, Schill E, Kwiatek G, Dresen G, Zimmermann G, Dahm T, Weber M (2017) Hydraulic fracture monitoring in hard rock at 410 m depth with an advanced fluid-injection protocol and extensive sensor array. Geophys J Int 208(2):790–813. https://doi.org/10.1093/gji/ggw430

    Article  Google Scholar 

  • Zhang Z, Zhang X, Badal J (2008) Composition of the crust beneath southeastern China derived from an integrated geophysical data set. J Geophys Res Solid Earth 113:B04417

    Google Scholar 

  • Zhou Y, Nolet G, Dahlen FA, Laske G (2006) Global upper-mantle structure from finite-frequency surface-wavetomography. J Geophys Res Solid Earth 111:B04304. https://doi.org/10.1029/2005JB003677

    Article  Google Scholar 

  • Zhou C, Jianghai X, Jingyin P (2020) Dataset for ambient noise tomography of Andi Geothermal Field in central Zhejiang province China. Mendeley Data. https://doi.org/10.17632/382frvcy6r.3

    Article  Google Scholar 

  • Zigone D, Ben-Zion Y, Lehujeur M, Campillo M, Hillers G, Vernon FL (2019) Imaging subsurface structures in the San Jacinto fault zone with high-frequency noise recorded by dense linear arrays. Geophys J Int 217(2):879–893. https://doi.org/10.1093/gji/ggz069

    Article  Google Scholar 

Download references

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).

Author information

Authors and Affiliations

  1. Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province, School of Earth Sciences, Zhejiang University, Hangzhou, 310027, Zhejiang, China

    Changjiang Zhou, Jianghai Xia, Jingyin Pang, Xinhua Chen, Chaoqiang Xi, Hongyu Zhang, Ya Liu, Ling Ning, Binbin Mi & Changwei Zhou

  2. Department of Earth, Environmental, and Planetary Sciences, Rice University, Houston, TX, 77005, USA

    Feng Cheng

  3. Institute of Information Engineering, Nanchang University, Nanchang, 330031, Jiangxi, China

    Tianyu Dai

  4. Zhejiang Geophysical and Geochemical Prospecting Academy, Hangzhou, 310000, Zhejiang, China

    Changwei Zhou

Authors
  1. Changjiang Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianghai Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jingyin Pang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Feng Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xinhua Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Chaoqiang Xi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hongyu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ya Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ling Ning
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Tianyu Dai
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Binbin Mi
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Changwei Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jianghai Xia.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 1486 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10712-021-09642-8

Keywords

Search

Navigation