AKTİF ÇOK KANALLI YÜZEY DALGASI ANALİZİ (A-ÇKYDA)YÖNTEMİNDE VERİ TOPLAMA VE TABAKA PARAMETRELERİNİN TEMEL MOD DİSPERSİYON EĞRİSİ ÜZERİNDEKİ ETKİLERİ

Abstract

Aktif ÇKYDA yönteminde, sığ yeraltının güvenilir bir S-dalgası hız-derinlik profilini elde etmek için en önemli aşamalarından biri, geniş frekans aralığında sürekli ve yüksek ayrımlı bir dispersiyon eğrisinin elde edilmesidir. Bu makalede, tabaka (S- ve P-dalga hızları, yoğunluk ve kalınlık) ve veri toplama (kaynak ofseti-X0, alıcı aralığı-dx ve sayısı-N, serim boyu-L=(N-1)*dx) parametrelerinin, yüzey dalga alanının temel mod dispersiyon eğrisi üzerindeki etkileri, yapay atış verilerinin analizi ile incelenmiştir. Yapay veriler, tabaka yansıma/iletim katsayısı tekniği ile hesaplanan dispersiyon eğrisi kullanılarak, her bir alıcıda harmonik mod toplama tekniği ile oluşturulmuştur. Buna göre, düşük S-dalga hızlı ara tabakalar dispersiyon eğrisinin düşük frekans bölgesinde düşük hızlara kaymasına, yüksek hızlı ara tabakalar ise, dispersiyon eğrisinin yüksek frekanslarda sürekliliğinin bozulmasına (zig-zag etkisi) ve yüksek mod etkisi yanılgısına neden olabileceği gözlenmiştir. Kaynak ofseti yüzey dalgalarının tam dalga formlarının oluşmasında etkin iken, ilk ve son alıcı arası uzaklık olan serim uzunluğunun ise, dispersiyon eğrisinin frekans bandını ve çözünürlüğünü etkilediği görülmüştür. Ayrıca, geniş alıcı aralıklarının, dispersiyon eğrisinin düşük frekans bölgesindeki güvenirliğinin arttırmasının yanında, yüksek frekans bölgesinde dalga sayısı katlanması nedeniyle dispersiyon eğrisinin sürekliliğini bozduğu görülmüştür. Sonuç olarak, farklı dalga hızlarına sahip yer modelleri için üretilen yapay veriler üzerinde yapılan analizler N<24 4.0m≤dx≤2m, N≥24 0.5m≤dx≤2m ve X0≥4*dx veya X0≥L/5 kombinasyonlarının, farklı yer altı koşullarının kestirimi amacıyla toplanacak aktif ÇKYD verileri için güvenilir olacağını göstermiştir.

Keywords

• Veri Toplama
• Tabaka Parametreleri
• Dispersiyon Eğrisi
• A-ÇKYDA
• Modelleme

INFLUENCES OF DATA ACQUISITION AND LAYER PARAMETERS ON FUNDAMENTAL DISPERSION CURVE IN ACTIVE MULTICHANNEL ANALYSIS OF SURFACE WAVE (A-MASW) METHOD

Abstract

Obtaining a continuous and high resolution dispersion curve in a wide frequency range is one of the most important steps to determine a reliable shear (S) wave velocity-depth profile of the shallow subsurface in active MASW method. In this article, the effects of layer (or physical) (S- and P-wave velocities, density and thickness) and data acquisition (source offset-X0, receiver spacing-dx and number-N, spread length-L=(N-1)*dx) parameters on the fundamental mode dispersion curve of the surface wave field were investigated by analyzing the synthetic shot gathers. The synthetic data were generated by harmonic mode summation technique at each receiver with using of the dispersion curve calculated by the layer reflection/transmission coefficient technique. Accordingly, it was observed that low S-wave velocity interlayers may cause shifting the dispersion curve to low velocities in the low frequency band, while high velocity interlayers may cause both discontinuity on the dispersion curve at high frequencies (zig-zag effect) and high-mode effect error. It was seen that while the source offset is effective in the formation of full waveforms of surface waves, the distance between the first and last receiver affects the frequency band and resolution of the dispersion curve. In addition, it is observed that wide receiver sampling increases the reliability of the dispersion curve in the low frequency region, though it disrupts the continuity of the dispersion curve at high frequencies due to wavenumber aliasing. As a result, the analyses made on the synthetic data generated for various subsurface layer models with different wave velocities demonstrate that the combinations of N<24 4.0m≤dx≤2m, N≥24 0.5m≤dx≤2m and X0≥4*dx or X0≥L/5 would provide practical convenience for the selection of acquisition parameters for active MASW data in the field.

Keywords

• Data Acquisition
• Layer Parameters
• Dispersion Curve
• MASW
• Modelling

References

1. Aki K., Richards P.G. Quantitative seismology. 2nd ed. University Science Books; 2002.
2. Beaty, K. S., Schmitt, D. R., Sacchi, M., 2002. Simulated annealing inversion of multimode Rayleigh wave dispersion curves for geological structure, Geophysical Journal International 151:622-631.
3. Buchen, P. W., Ben-Hador, R., 1996. Free-mode surface-wave computations. Geophysical Journal International, 124 (3), 869–887.
4. Chen, X., 1993. A systematic and efficient method of computing normal modes for multilayered half-space, Geophys. J. Int., 115, 391-409.
5. Dal Moro, G., Pipan, M., Forte, E., & Finetti, I., 2003. Determination of Rayleigh wave dispersion curves for near surface applications in unconsolidated sediments. In SEG International Exposition and Seventy-Third Annual Meeting, 24-31 October 2003, Dallas, Texas (Vol. 22, pp. 1247–1250).
6. Dal Moro, G., Ferigo, F., 2011. Joint analysis of Rayleigh and Love wave dispersion for Near-surface studies: issues, Criteria and Improvements. Journal of Applied Geophysics 75: 573–89.
7. Dal Moro, G., Keller, L., Moustafa, S.R., Al-Arifi, N., 2016. Shear-wave velocity profiling according to three alternative approaches: a comparative case study. Journal of Applied Geophysics 134: 112–24.
8. Dikmen, Ü., Arısoy, M. Ö., ve Akkaya, İ., 2010, Offset and linear spread geometry in the MASW method: J. Geophys. Eng., 7, 211–222.

9. Foti, S., Parolaj, S., Albarello, D., ve Picozzi, M., 2011. Application of Surface-Wave Methods for Seismic Site Characterization: Survey in Geophysics, 32, 777–825.
10. Foti S, Lai CG, Rix GJ, Strobbia C. Surface wave methods for near-surface site characterization. Boca Raton, FL: CRC Press, Taylor & Francis Group; 2015.
11. Foti, S., Hollender, F., Garofalo, F., Albarello, D., Asten, M., Bard, P.-Y., Comina, C., Cornou, C., Cox, B., Giulio, G.D., Forbriger, T., Hayashi, K., Lunedei, E., Martin, A., Mercerat, D., Ohrnberger, M., Poggi, V., Renalier, F., Sicilia, D., Socco, V., 2017. Guidelines for the good practice of surface wave analysis: a product of the InterPACIFIC project, Bulletin Earthquake Engineering, 1–54.
12. Gao, L., Xia, J., Pan, Y., Xu, Y., 2016. Reason and condition for mode kissing in MASW method, Pure Appl Geophys., 173(5):1627–38.
13. Hisada Y., 1994. An efficient method for computing Green’s function for a layered half space with sources and receivers at close depth, Bulletin of the Seismological Society of America, 84, 1456-1472.
14. Hisada Y., 1995. An efficient method for computing Green’s function for a layered half space with sources and receivers at close depth (part 2), Bulletin of the Seismological Society of America, 85, 1080-1093.
15. Ivanov, J., Park, B. C., Miller, R. D., Xia, J., 2005. Analysing and Filtering Surface-Wave Energy By Muting Shot Gathers. Journal of Environmental and Engineering Geophysics, 10:307–322
16. Kanli, A. I., Tildy, P., Pranay, Z., Pınar, A, Hermann, L., 2006. Vs30 mapping and soil classification for seismic site effect evaluation in Dinar region, SW Turkey, Geophysical Journal International, 165:223-235.
17. Karslı, H., Şenkaya, G., Şenkaya, M., Güney, R., 2017. Investigation of soil structure in Uzungöl settlement area by Shallow Seismic Methods, Eurasian Journal of Soil Science, 6, 134-143.
18. Kennett, B. L. N., 1983. Seismic wave propagation in stratified media, Cambridge University Press, Cambridge.
19. Lai, C.G., (1998). "Simultaneous Inversion of Rayleigh Phase Velocity and Attenuation for Near-Surface Site Characterization," Ph.D. Dissertation, Georgia Institute of Technology.
20. Lai, C.G., ve Rix, G.J., 1998, Simultaneous Inversion of Rayleigh Phase Velocity and Attenuation for Near-Surface Site Characterization: Georgia Institute of Technology, School of Civil and Environmental Engineering, Report No. GIT-CEE/GEO-98-2, 258 pp.
21. Lai, C.G., Foti, S., Rix, G.J., 2005. Propagation of data uncertainty in surface wave inversion. J Environ Eng Geophys, 10(2):219–28.
22. Miller, R. D., Xia, J., Park, C. B., Ivanov, J. M., 1999. Multichannel analysis of surface waves to map bedrock, The Leading Edge, 12:1392-1396.
23. Olafsdottir, E.A., Bessason, B., Erlingsson, S., 2018. Combination of dispersion curves from MASW measurements, Soil Dynamics and Earthquake Engineering, 113, 473–487.
24. Park, C. B., Miller, R. D., Xia, J., 1998. Imaging dispersion curves of surface waves on multi-channel record” 68th Annual International Meeting of Society of Exploration Geophysics, Expanded Abstract 1377-1380.
25. Park, C. B., Miller, R. D., ve Xia, J., 1999, Multichannel analysis of surface waves (MASW): Geophysics, 64, 800-808.
26. Park, C. B., Miller, R. D., Xia, J., 2001. Offset and resolution of dispersion curve in 724 multichannel analysis of surface waves (MASW), Proceedings of the SAGEEP, 725 SSM4, 1-6.
27. Park, C.B., Miller, R.D., ve Miura, H., 2002. Optimum field parameters of an MASW survey: Extented Abstract, SEG-J, May 22-23, Tokyo.
28. Park, C. B. 2011. Imaging dispersion of MASW data-Full vs. selective offset scheme, Journal of Environmental and Engineering, Geophysics, 16:13-23.
29. Pei D., 2007. Modeling and inversion of dispersion curves of surface waves in shallow site investigations, Ph.D. Thesis. Reno, NV, University of Nevada.
30. Pei, D. Louie, J. N., Pullammanappallil, S.K., 2008. Improvements on Computation of Phase Velocities of Rayleigh Waves Based on the Generalized R/T Coefficient Method , Bulletin of the Seismological Society of America, Vol. 98, No. 1, pp. 280–287.
31. Rix, G.J., Lai, C.G., 2000. Software package tools for surface wave analysis. Available at the WEB site: http://www.ce. gatech.edu/;grix/surface_wave.html#Software.
32. Sauvin, G., Vanneste, M., Heureux, J.S.L., L’Heureux J-S., O’Connor P., O’Rourke S., 2016. Impact of data acquisition parameters and processing techniques on S-wave velocity profiles from MASW–Examples from Trondheim, Norway. In: Proceedings of the 17th Nordic Geotechnical Meeting. 2016, 1297–306.
33. Song, X., Gu, H., 2007. Utilization of multimode surface wave dispersion for characterizing roadbed structure, Journal of Applied Geophysics, 63(2):59–67.
34. Şenkaya, M., Karsli, H., 2016. Joint inversion of Rayleigh-wave dispersion data and vertical electric sounding data: synthetic tests on characteristic sub-surface models, Geophysical Prospecting, 64, 228-246, 2016.
35. Şenkaya, M., Karslı, H., Socco, V.L., Foti, S., 2020. Obtaining reliable S-wave velocity depth profile by joint inversion of geophysical data: the combination of active surface-wave, seismic refraction and electric sounding data, Near Surface Geophysics, 18, 659-682.
36. Taipodia, J., Baglari, D., Dey, A., 2018. Recommendations for generating dispersion images of optimal resolution from active MASW survey, Innovative Infrastruct. Solut. 3, 1–19.
37. Taipodia J., Dey, A., Gaj S., Baglari D., 2020. Quantification of the resolution of dispersion image in active MASW survey and automated extraction of dispersion curve. Computer and Geoscience, 135:104360-1-19.
38. Taipodia J., Dey, A., Gaj S., Baglari D., 2020. Influence of receiver layout on active MASW survey conducted at different sites having varying substrata characteristics, Arabian Journal of Geosciences (2021) 14: 1143.
39. Uyanık, O., Çatlıoğlu, B., 2010, Determination of density from seismic velocities, the 19th International Geophysical Congress and Exhibition of Turkey 23 – 26 November Ankara / Turkey.
40. Vanlı Senkaya, G., Senkaya, M., Karsli, H., Güney, R., 2020, Integrated shallow seismic imaging of a settlement located in a historical landslide area, Bulletin of Engineering Geology and the Environment, 79 1781–1796.
41. Xia, J., Miller, R. D., Park, C. B., 1999. Estimation of near-surface shear-wave velocity by inversion of Rayleigh wave, Geophysics, 64:691-700.
42. Xia, J., Miller, R.D., Park, C.B., Tian, G., 2003. Inversion of high frequency surface waves with fundamental and higher modes, Journal of Applied Geophysics, 52(1):45–57.
43. Xia, J., Miller, R.D., Park, C.B., Ivanov, J., Tian, G., and Chen, C., 2004, Utilization of high-frequency Rayleigh waves in near-surface geophysics: The Leading Edge, 23(8) 753–759.
44. Xu, Y., Xia, J., Miller, R. D., 2006. Quantitative estimation of minimum offset for multichannel surface-wave survey with actively exciting source, Journal of Applied Geophysics, 59:117-125.
45. Yılmaz, O., Eser, M., 2002. A unified workflow for engineering seismology, 72nd Ann. Mtg. SEG (Salt Lake City, UT) pp 1496–9.
46. Zhang, S.X., Chan, L.S., 2003. Possible effects of misidentified mode number on Rayleigh wave inversion, Journal of Applied Geophysics, 53(1):17–29.
47. Zhang, S. X., Chan, L. S., and Xia, J., 2004, The Selection of Field Acquisition Parameters for Dispersion Images from Multichannel Surface Wave Data: Pure appl. Geophysics, 161, 185–201.