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Using Noise Control Technologies and Systems in Construction and Seismology

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Noise Control of the Beginning and Development Dynamics of Accidents

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Abstract

One of the possible solutions to the problem of monitoring the beginning of the initiation of anomalous seismic processes by carrying out of noise analysis of seismic-acoustic signals received from earth’s deep strata is considered. The diagram of the station for noise monitoring of the beginning of seismic processes is proposed in which bores of suspended oil wells (1500–5000 m) are used as communication channels to receive seismic information from earth’s deep strata. Experiments on shallow wells (40–200 m) have shown that they also reliably receive seismic-acoustic information, although within a shorter radius of reception of seismic-acoustic signals. The chapter analyzes the results of the experiments with the intelligent seismic-acoustic system for identifying the area of the focus of an expected earthquake based on the network consisting of seismic-acoustic stations built on six deep and four shallow wells. It has been established that only with the application of the noise technology, the beginning of seismic processes is reliably detected based on the estimates of the correlation function between the useful seismic-acoustic signal and its noise. The combinations of seismic-acoustic stations vary depending on their location and direction. If seismic processes from one direction are recorded by 3–5 stations, then completely different combinations of stations respond to them from the opposite direction. Due to this, the system can be used by seismologists as a tool for identifying the area of the focus of an expected earthquake based on the combinations of stations that respond to seismic processes.

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References

  1. Kanamori H, Brodsky EE (2004) The physics of earthquakes. Rep Prog Phys 67(8):1429–1496. https://doi.org/10.1088/0034-4885/67/8/R03

    Article  MathSciNet  Google Scholar 

  2. Tothong P, Cornell CA (2006) An empirical ground-motion attenuation relation for inelastic spectral displacement. Bull Seismol Soc Am 96(6):2146–2164. https://doi.org/10.1785/0120060018

    Article  Google Scholar 

  3. Ghahari SF, Jahankhah H, Ghannad MA (2010) Study on elastic response of structures to near-fault ground motions through record decomposition. Soil Dyn Earthq Eng 30(7):536–546. https://doi.org/10.1016/j.soildyn.2010.01.009

    Article  Google Scholar 

  4. Boore DM, Bommer JJ (2005) Processing of strong-motion accelerograms: needs, options and consequences. Soil Dyn Earthq Eng 25(2):93–115. https://doi.org/10.1016/j.soildyn.2004.10.007

    Article  Google Scholar 

  5. Galiana-Merino JJ, Parolai S, Rosa-Herranz J (2011) Seismic wave characterization using complex trace analysis in the stationary wavelet packet domain. Soil Dyn Earthq Eng 31(11):1565–1578. https://doi.org/10.1016/j.soildyn.2011.06.009

    Article  Google Scholar 

  6. Yee E, Stewart JP, Schoenberg FP (2011) Characterization and utilization of noisy displacement signals from simple shear device using linear and kernel regression methods. Soil Dyn Earthq Eng 31(1):25–32. https://doi.org/10.1016/j.soildyn.2010.07.011

    Article  Google Scholar 

  7. Pavlović VD, Veličković ZS (1998) Measurement of the seismic waves propagation velocity in the real medium. Sci J Facta Univ Ser: Phys Chem Technol 1:63–73

    Google Scholar 

  8. Wang Y, Lu J, Shi Y et al (2009) PS-wave Q estimation based on the P-wave Q values. J Geophys Eng 6(4):386–389. https://doi.org/10.1088/1742-2132/6/4/006

    Article  Google Scholar 

  9. Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674–693. https://doi.org/10.1109/34.192463

    Article  MATH  Google Scholar 

  10. Vidakovic B, Lozoya CB (1998) On time-dependent wavelet denoising. IEEE Trans Sig Process 46(9):2549–2554. https://doi.org/10.1109/78.709544

    Article  Google Scholar 

  11. Colak OH, Destici TC, Ozen S et al (2008) Frequency-energy characteristics of local earthquakes using discrete wavelet transform (DWT). Int J Civil Environ Eng 2(8):199–202

    Google Scholar 

  12. Hutton DV (2004) Fundamentals of finite element analysis, 1st edn. McGraw-Hill, New York

    Google Scholar 

  13. Kislov KV, Gravirov VV (2011) Earthquake arrival identification in a record with technogenic noise. Seismic Instrum 47(1):66–79. https://doi.org/10.3103/S0747923911010129

    Article  Google Scholar 

  14. Descherevsky AV, Lukk AA, Sidorin AY et al (2003) Flicker-noise spectroscopy in earthquake prediction research. Nat Hazards Earth Syst Sci 3(3–4):159–164. https://doi.org/10.5194/nhess-3-159-2003

    Article  Google Scholar 

  15. Kossobokov VG (2006) Testing earthquake prediction methods: «The West Pacific short-term forecast of earthquakes with magnitude MwHRV ≥ 5.8». Tectonophysics 413(1–2):25–31. https://doi.org/10.1016/j.tecto.2005.10.006

    Article  Google Scholar 

  16. Shebalin P, Keilis-Borok V, Gabrielov A et al (2006) Short-term earthquake prediction by reverse analysis of lithosphere dynamics. Tectonophysics 413(1–2):63–75. https://doi.org/10.1016/j.tecto.2005.10.033

    Article  Google Scholar 

  17. Hashemi M, Alesheikh AA (2011) A GIS-based earthquake damage assessment and settlement methodology. Soil Dyn Earthq Eng 31(11):1607–1617. https://doi.org/10.1016/j.soildyn.2011.07.003

    Article  Google Scholar 

  18. Hatzigeorgiou GD, Beskos DE (2010) Soil–structure interaction effects on seismic inelastic analysis of 3-D tunnels. Soil Dyn Earthq Eng 30(9):851–861. https://doi.org/10.1016/j.soildyn.2010.03.010

    Article  Google Scholar 

  19. Papagiannopoulos GA, Beskos DE (2006) On a modal damping identification model for building structures. Arch Appl Mech 76:443–463

    Article  Google Scholar 

  20. Papagiannopoulos GA, Beskos DE (2009) On a modal damping identification model for non-classically damped linear building structures subjected to earthquakes. Soil Dyn Earthq Eng 29(3):583–589

    Article  Google Scholar 

  21. Zafarani H, Noorzad A, Ansari A et al (2009) Stochastic modeling of Iranian earthquakes and estimation of ground motion for future earthquakes in Greater Tehran. Soil Dyn Earthq Eng 29(4):722–741. https://doi.org/10.1016/j.soildyn.2008.08.002

    Article  Google Scholar 

  22. Sokolov VY, Loh CH, Wen KL (2003) Evaluation of hard rock spectral models for the Taiwan region on the basis of the 1999 Chi-Chi earthquake data. Soil Dyn Earthq Eng 23(8):715–735. https://doi.org/10.1016/S0267-7261(03)00075-7

    Article  Google Scholar 

  23. Stankiewicz J, Bindi D, Oth A et al (2013) Designing efficient earthquake early warning systems: case study of Almaty, Kazakhstan. J Seismolog 17(4):1125–1137. https://doi.org/10.1007/s10950-013-9381-4

    Article  Google Scholar 

  24. Rydelek P, Pujol J (2004) Real-time seismic warning with a two-station subarray. Bull Seismol Soc Am 94(4):1546–1550. https://doi.org/10.1785/012003197

    Article  Google Scholar 

  25. Aliev TA, Abbasov AM, Aliev ER et al (2007) Digital technology and systems for generating and analyzing information from deep strata of the earth for the purpose of interference monitoring of the technical state of major structures. Autom Control Comput Sci 41(2):59–67. https://doi.org/10.3103/S0146411607020010

    Article  Google Scholar 

  26. Aliev TA, Alizada TA, Abbasov AM (2009) Method for monitoring the beginning of anomalous seismic process. Eurasian Patent 012,803, 30 Dec 2009

    Google Scholar 

  27. Aliev T, Quluyev Q, Pashayev F et al (2016) Intelligent seismic-acoustic system for identifying the location of the areas of an expected earthquake. J Geosci Environ Prot 4(4):147–162. https://doi.org/10.4236/gep.2016.44018

    Article  Google Scholar 

  28. Aliev TA, Abbasov AM, Guluyev QA et al (2013) System of robust noise monitoring of anomalous seismic processes. Soil Dyn Earthq Eng 53:11–25. https://doi.org/10.1016/j.soildyn.2012.12.013

    Article  Google Scholar 

  29. Aliev TA (2017) Intelligent seismic-acoustic system for identifying the area of the focus of an expected earthquake. In: Taher Zouaghi (ed) Earthquakes: tectonics, hazard and risk mitigation. Intech, London. pp 293–315. https://doi.org/10.5772/65403

    Google Scholar 

  30. Aliev TA, Aliev ER (2008) Multichannel telemetric system for seismo-acoustic signal interference monitoring of earthquakes. Autom Control Comput Sci 42(4):223–228. https://doi.org/10.3103/S0146411608040093

    Article  Google Scholar 

  31. Aliev TA, Musayeva NF, Sattarova UE (2014) Noise technologies for operating the system for monitoring of the beginning of violation of seismic stability of construction objects. In: Zadeh L., Abbasov A., Yager R. et al (eds) Recent developments and new directions in soft computing. Studies in fuzziness and soft computing, vol 317. Springer, Cham, pp 211–232. https://doi.org/10.1007/978-3-319-06323-2_14

    Google Scholar 

  32. Aliev TA, Alizade AA, Etirmishli GD et al (2011) Intelligent seismoacoustic system for monitoring the beginning of anomalous seismic process. Seismic Instrum 47(1):15–23. https://doi.org/10.3103/S0747923911010026

    Article  Google Scholar 

  33. Aliev TA, Abbasov AM, Mamedova GG et al (2013) Technologies for noise monitoring of abnormal seismic processes. Seismic Instrum 49(1):64–80. https://doi.org/10.3103/S0747923913010015

    Article  Google Scholar 

  34. Aliev TA (2000) Robust technology for systems analysis of seismic signals. Autom Control Comput Sci 34(5):17–26

    Google Scholar 

  35. Aliev TA, Abbasov AM (2005) Digital technology and a system of interference monitoring of the technical state of physical structures and warnings of anomalous seismic processes. Autom Control Comput Sci 39(6):1–7

    Google Scholar 

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Authors and Affiliations

  1. Institute of Control Systems, Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Telman Aliev

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  1. Telman Aliev
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Correspondence to Telman Aliev .

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Aliev, T. (2019). Using Noise Control Technologies and Systems in Construction and Seismology. In: Noise Control of the Beginning and Development Dynamics of Accidents. Springer, Cham. https://doi.org/10.1007/978-3-030-12512-7_8

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  • DOI: https://doi.org/10.1007/978-3-030-12512-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12511-0

  • Online ISBN: 978-3-030-12512-7

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