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Aykırı değerler içeren VLF verilerinin süzgeçlenmesinde budanmış ortalama, Empirik Mod Ayrışımı ve dayanıklı regresyon yöntemlerinin karşılaştırılması

Year 2022, , 7 - 18, 17.01.2022

Anisya B.tekkeli , Mehmet Ali Üge , Mehmet Safa Arslan

https://doi.org/10.21205/deufmd.2022247002

Abstract

Çok Düşük Frekans (VLF) elektromanyetik yöntem , yeraltının sığ iletkenlik dağılımının belirlenmesi için sıklıkla uygulanır. Toplanan VLF verileri genelde aperiyodiktir ve bu nedenle doğrusal olmayan süzgeçleme yöntemleri VLF verilerinin gürültüden arındırılması için sıklıkla uygulanmaktadır. Bu çalışmada, aykırı değerler içeren verilerin değerlendirilmesinde daha başarılı yöntemlerin belirlenmesi için farklı doğrusal olmayan süzgeçler kuramsal ve gürültülü arazi verilerine uygulanmıştır. Kuramsal verilerin aksine, arazi verilerinde gerçek yeraltı modeli bilinemediği için, aynı ölçüm hattı üzerinde farklı zamanda toplanmış VLF-R ve Elektrik Rezistivie Tomografisi verileri değerlendirilmiştir ve sonuçları yeraltının daha doğru bir temsili olarak kabul edilmiştir. Kuramsal ve arazi verileri üzerinde gerçekleştirilen uygulamalarda, aykırı değerler içeren verilerde dayanıklı regresyonun diğer yöntemlere göre daha başarılı olduğunu göstermiştir.

Keywords

VLF Empirik Mod Ayrışımı dayanıklı regresyon budanmış ortalama ters çözüm

Supporting Institution

İstanbul Üniversitesi-Cerrahpaşa Bilimsel Araştırma Projeleri Koordinasyon Birimi

Project Number

BYP-2019-34096

References

  • Bayrak, M., Şenel, L., 2012. Two-dimensional resistivity imaging in the Kestelek boron area by VLF and DC resistivity methods. Journal of applied geophysics, Cilt. 82, 1-10. https://doi.org/10.1016/j.jappgeo.2012.03.010
  • Drahor, M.G., Berge, M.A., 2006. Geophysical investigations of the Seferihisar geothermal area, Western Anatolia, Turkey. Geothermics, Cilt. 35, 302-320.https://doi.org/10.1016/j.geothermics.2006.04.001
  • Olesen, O., Henkel, H., Lile, O.B., Mauring, E., Ronning, J.S., 1992. Geophysical inverstigations of the Stuoragurra postglacial fault, Finnmark, northern Norway. Journal of Applied Geophysics., Cilt. 29, 95-118. https://doi.org/10.1016/0926-9851(92)90001-2
  • Yamaguchi, S., Murakami, S., Inokuchi, H., 2001., Resistivity mapping using the VLF-MT method around surface fault ruptures of the 1995 Hyogo-ken Nanbu earthquake, Japan. The Island Arc, Cilt.. 10, 296–305. https://doi.org/10.1111/j.1440-1738.2001.00328.x
  • Gürer, A., Bayrak, M., Gürer, Ö.F., 2009. A VLF survey using current gathering phenomena for tracing buried faults of Fethiye–Burdur Fault Zone, Turkey. Journal of Applied Geophysics, Cilt. 68, 437-447. https://doi.org/10.1016/j.jappgeo.2009.03.011
  • Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., Yen, N. C., Tung, C. C., Liu, H. H. , 1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: mathematical, physical and engineering sciences, 454(1971), 903-995. https://doi.org/10.1098/rspa.1998.0193
  • Jeng, Y., Lin, M. J., Chen, C. S., & Wang, Y. H., 2007. Noise reduction and data recovery for a VLF-EM survey using a nonlinear decomposition method. Geophysics, Cilt. 72(5), F223-F235. https://doi.org/10.1190/1.2752561
  • Bahri, A. S., Warnana, D. D., Santos, F. A. M., & Santosa, B. J., 2014. Fast, simultaneous and robust VLF-EM data denoising and reconstruction via multivariate empirical mode decomposition. Computers & Geosciences, Cilt. 67, 125-138. https://doi.org/10.1016/j.cageo.2014.03.007
  • Bahri, A. S., & Santosa, B. J., 2015. Application of Multivariate EMD to Improve Quality VLF-EM Data: Synthetic and Fields Data. Applied Mechanics and Materials, Cilt. 771, 170-173, Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/AMM.771.170
  • Verardi, V., & Croux, C., 2009. Robust regression in Stata. The Stata Journal, Cilt. 9(3), 439-453. https://doi.org/10.1177/1536867X0900900306
  • Ebrahimi, A., Sundararajan, N., & Babu, V. R., 2019. A comparative study for the source depth estimation of very low frequency electromagnetic (VLF-EM) signals. Journal of Applied Geophysics, Cilt. 162, 174-183. https://doi.org/10.1016/j.jappgeo.2019.01.007
  • Karcıoğlu, G., 2019. Near-surface resistivity structure near avcilar landslide in Istanbul, Turkey by 2D inversion of VLF data. Journal of Applied Geophysics, Cilt. 163, 73-83. https://doi.org/10.1016/j.jappgeo.2019.02.012
  • Kumar, S., Pal, S. K., & Guha, A., 2020. Very low frequency electromagnetic (VLF-EM) study over Wajrakarur kimberlite Pipe 6 in Eastern Dharwar Craton, India. Journal of Earth System Science, Cilt. 129(1), 1-10. https://doi.org/10.1007/s12040-020-1367-3
  • Sungkono, Santosa, B. J., Bahri, A. S., Santos, F. M., & Iswahyudi, A., 2017. Application of Noise-Assisted Multivariate Empirical Mode Decomposition in VLF-EM Data to Identify Underground River. Advances in Data Science and Adaptive Analysis, Cilt. 9(01), 1650011. https://doi.org/10.1142/S2424922X1650011X
  • Candansayar, M. E., 2008. Two‐dimensional inversion of magnetotelluric data with consecutive use of conjugate gradient and least‐squares solution with singular value decomposition algorithms. Geophysical Prospecting, Cilt. 56(1), 141-157. https://doi.org/10.1111/j.1365-2478.2007.00668.x
  • Özyıldırım, Ö., Candansayar, M. E., Demirci, İ., & Tezkan, B., 2017. Two-dimensional inversion of magnetotelluric/radiomagnetotelluric data by using unstructured mesh. Geophysics, Cilt. 82(4), E197-E210. https://doi.org/10.1190/geo2016-0378.1
  • Özyıldırım, Ö., Demirci, İ., Gündoğdu, N. Y., & Candansayar, M. E., 2020. Two dimensional joint inversion of direct current resistivity and radiomagnetotelluric data based on unstructured mesh. Journal of Applied Geophysics, Cilt. 172, 103885. https://doi.org/10.1016/j.jappgeo.2019.103885
  • Triggs B., McLauchlan P.F., Hartley R.I., Fitzgibbon A.W., 2000. Bundle Adjustment — A Modern Synthesis. In: Triggs B., Zisserman A., Szeliski R. (eds) Vision Algorithms: Theory and Practice. IWVA 1999. Lecture Notes in Computer Science, vol 1883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44480-7_21
  • Stromberg, A., 2004. Why write statistical software? The case of robust statistical methods. Journal of Statistical Software, Cilt. 10(5), 1-8.
  • Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Jarrod Millman, K., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C., Polat, İ., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., ..., van Mulbregt, P., and SciPy 1.0 Contributors, 2020. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nat. Methods, 17, 261–272. https://doi.org/10.1038/s41592-019-0686-2
  • Constable, S. C., Parker, R. L., & Constable, C. G., 1987. Occam’s inversion: A practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics, Cilt. 52(3), 289-300. doi: 10.1190/1.1442303
  • de Groot-Hedlin, C., & Constable, S., 1990. Occam’s inversion to generate smooth, two-dimensional models from magnetotelluric data. Geophysics, Cilt. 55(12), 1613-1624. doi: 10.1190/1.1442813

Comparison of trimmed mean, Empiric Mode Decomposition and robust regression methods for filtering VLF data with outliers

Year 2022, , 7 - 18, 17.01.2022

Anisya B.tekkeli , Mehmet Ali Üge , Mehmet Safa Arslan

https://doi.org/10.21205/deufmd.2022247002

Abstract

Very Low Frequency (VLF) electromagnetic method is widely implemented to determine shallow conductivity distribution of subsurface. Collected VLF data are usually aperiodic and consequently non-linear filtering techniques are often used for eliminating noise in VLF data. In this study, several non-linear filtering methods are implemented on synthetic and field data to determine methods performing better in case of outliers in data. In contrary of synthetic studies, the true subsurface model is unknown for the field data. Hence, VLF-R and Electrical Resistivity Tomography data, which are also collected over the same measuring profile, are also interpreted and their results are assumed as better representations of the subsurface. Applications on noisy synthetic and field datasets showed that the robust regression performs better than the other techniques in case of data with outliers.

Keywords

VLF Empiric Mode Decomposition robust regression trimmed mean inversion

Project Number

BYP-2019-34096

References

  • Bayrak, M., Şenel, L., 2012. Two-dimensional resistivity imaging in the Kestelek boron area by VLF and DC resistivity methods. Journal of applied geophysics, Cilt. 82, 1-10. https://doi.org/10.1016/j.jappgeo.2012.03.010
  • Drahor, M.G., Berge, M.A., 2006. Geophysical investigations of the Seferihisar geothermal area, Western Anatolia, Turkey. Geothermics, Cilt. 35, 302-320.https://doi.org/10.1016/j.geothermics.2006.04.001
  • Olesen, O., Henkel, H., Lile, O.B., Mauring, E., Ronning, J.S., 1992. Geophysical inverstigations of the Stuoragurra postglacial fault, Finnmark, northern Norway. Journal of Applied Geophysics., Cilt. 29, 95-118. https://doi.org/10.1016/0926-9851(92)90001-2
  • Yamaguchi, S., Murakami, S., Inokuchi, H., 2001., Resistivity mapping using the VLF-MT method around surface fault ruptures of the 1995 Hyogo-ken Nanbu earthquake, Japan. The Island Arc, Cilt.. 10, 296–305. https://doi.org/10.1111/j.1440-1738.2001.00328.x
  • Gürer, A., Bayrak, M., Gürer, Ö.F., 2009. A VLF survey using current gathering phenomena for tracing buried faults of Fethiye–Burdur Fault Zone, Turkey. Journal of Applied Geophysics, Cilt. 68, 437-447. https://doi.org/10.1016/j.jappgeo.2009.03.011
  • Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., Yen, N. C., Tung, C. C., Liu, H. H. , 1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: mathematical, physical and engineering sciences, 454(1971), 903-995. https://doi.org/10.1098/rspa.1998.0193
  • Jeng, Y., Lin, M. J., Chen, C. S., & Wang, Y. H., 2007. Noise reduction and data recovery for a VLF-EM survey using a nonlinear decomposition method. Geophysics, Cilt. 72(5), F223-F235. https://doi.org/10.1190/1.2752561
  • Bahri, A. S., Warnana, D. D., Santos, F. A. M., & Santosa, B. J., 2014. Fast, simultaneous and robust VLF-EM data denoising and reconstruction via multivariate empirical mode decomposition. Computers & Geosciences, Cilt. 67, 125-138. https://doi.org/10.1016/j.cageo.2014.03.007
  • Bahri, A. S., & Santosa, B. J., 2015. Application of Multivariate EMD to Improve Quality VLF-EM Data: Synthetic and Fields Data. Applied Mechanics and Materials, Cilt. 771, 170-173, Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/AMM.771.170
  • Verardi, V., & Croux, C., 2009. Robust regression in Stata. The Stata Journal, Cilt. 9(3), 439-453. https://doi.org/10.1177/1536867X0900900306
  • Ebrahimi, A., Sundararajan, N., & Babu, V. R., 2019. A comparative study for the source depth estimation of very low frequency electromagnetic (VLF-EM) signals. Journal of Applied Geophysics, Cilt. 162, 174-183. https://doi.org/10.1016/j.jappgeo.2019.01.007
  • Karcıoğlu, G., 2019. Near-surface resistivity structure near avcilar landslide in Istanbul, Turkey by 2D inversion of VLF data. Journal of Applied Geophysics, Cilt. 163, 73-83. https://doi.org/10.1016/j.jappgeo.2019.02.012
  • Kumar, S., Pal, S. K., & Guha, A., 2020. Very low frequency electromagnetic (VLF-EM) study over Wajrakarur kimberlite Pipe 6 in Eastern Dharwar Craton, India. Journal of Earth System Science, Cilt. 129(1), 1-10. https://doi.org/10.1007/s12040-020-1367-3
  • Sungkono, Santosa, B. J., Bahri, A. S., Santos, F. M., & Iswahyudi, A., 2017. Application of Noise-Assisted Multivariate Empirical Mode Decomposition in VLF-EM Data to Identify Underground River. Advances in Data Science and Adaptive Analysis, Cilt. 9(01), 1650011. https://doi.org/10.1142/S2424922X1650011X
  • Candansayar, M. E., 2008. Two‐dimensional inversion of magnetotelluric data with consecutive use of conjugate gradient and least‐squares solution with singular value decomposition algorithms. Geophysical Prospecting, Cilt. 56(1), 141-157. https://doi.org/10.1111/j.1365-2478.2007.00668.x
  • Özyıldırım, Ö., Candansayar, M. E., Demirci, İ., & Tezkan, B., 2017. Two-dimensional inversion of magnetotelluric/radiomagnetotelluric data by using unstructured mesh. Geophysics, Cilt. 82(4), E197-E210. https://doi.org/10.1190/geo2016-0378.1
  • Özyıldırım, Ö., Demirci, İ., Gündoğdu, N. Y., & Candansayar, M. E., 2020. Two dimensional joint inversion of direct current resistivity and radiomagnetotelluric data based on unstructured mesh. Journal of Applied Geophysics, Cilt. 172, 103885. https://doi.org/10.1016/j.jappgeo.2019.103885
  • Triggs B., McLauchlan P.F., Hartley R.I., Fitzgibbon A.W., 2000. Bundle Adjustment — A Modern Synthesis. In: Triggs B., Zisserman A., Szeliski R. (eds) Vision Algorithms: Theory and Practice. IWVA 1999. Lecture Notes in Computer Science, vol 1883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44480-7_21
  • Stromberg, A., 2004. Why write statistical software? The case of robust statistical methods. Journal of Statistical Software, Cilt. 10(5), 1-8.
  • Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Jarrod Millman, K., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C., Polat, İ., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., ..., van Mulbregt, P., and SciPy 1.0 Contributors, 2020. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nat. Methods, 17, 261–272. https://doi.org/10.1038/s41592-019-0686-2
  • Constable, S. C., Parker, R. L., & Constable, C. G., 1987. Occam’s inversion: A practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics, Cilt. 52(3), 289-300. doi: 10.1190/1.1442303
  • de Groot-Hedlin, C., & Constable, S., 1990. Occam’s inversion to generate smooth, two-dimensional models from magnetotelluric data. Geophysics, Cilt. 55(12), 1613-1624. doi: 10.1190/1.1442813
There are 22 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Anisya B.tekkeli 0000-0001-9402-2689

Mehmet Ali Üge 0000-0002-5631-7133

Mehmet Safa Arslan This is me 0000-0002-1233-963X

Project Number BYP-2019-34096
Publication Date January 17, 2022
Published in Issue Year 2022

Cite

APA B.tekkeli, A., Üge, M. A., & Arslan, M. S. (2022). Aykırı değerler içeren VLF verilerinin süzgeçlenmesinde budanmış ortalama, Empirik Mod Ayrışımı ve dayanıklı regresyon yöntemlerinin karşılaştırılması. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi, 24(70), 7-18. https://doi.org/10.21205/deufmd.2022247002
AMA B.tekkeli A, Üge MA, Arslan MS. Aykırı değerler içeren VLF verilerinin süzgeçlenmesinde budanmış ortalama, Empirik Mod Ayrışımı ve dayanıklı regresyon yöntemlerinin karşılaştırılması. DEUFMD. January 2022;24(70):7-18. doi:10.21205/deufmd.2022247002
Chicago B.tekkeli, Anisya, Mehmet Ali Üge, and Mehmet Safa Arslan. “Aykırı değerler içeren VLF Verilerinin süzgeçlenmesinde budanmış Ortalama, Empirik Mod Ayrışımı Ve dayanıklı Regresyon yöntemlerinin karşılaştırılması”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi 24, no. 70 (January 2022): 7-18. https://doi.org/10.21205/deufmd.2022247002.
EndNote B.tekkeli A, Üge MA, Arslan MS (January 1, 2022) Aykırı değerler içeren VLF verilerinin süzgeçlenmesinde budanmış ortalama, Empirik Mod Ayrışımı ve dayanıklı regresyon yöntemlerinin karşılaştırılması. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi 24 70 7–18.
IEEE A. B.tekkeli, M. A. Üge, and M. S. Arslan, “Aykırı değerler içeren VLF verilerinin süzgeçlenmesinde budanmış ortalama, Empirik Mod Ayrışımı ve dayanıklı regresyon yöntemlerinin karşılaştırılması”, DEUFMD, vol. 24, no. 70, pp. 7–18, 2022, doi: 10.21205/deufmd.2022247002.
ISNAD B.tekkeli, Anisya et al. “Aykırı değerler içeren VLF Verilerinin süzgeçlenmesinde budanmış Ortalama, Empirik Mod Ayrışımı Ve dayanıklı Regresyon yöntemlerinin karşılaştırılması”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi 24/70 (January 2022), 7-18. https://doi.org/10.21205/deufmd.2022247002.
JAMA B.tekkeli A, Üge MA, Arslan MS. Aykırı değerler içeren VLF verilerinin süzgeçlenmesinde budanmış ortalama, Empirik Mod Ayrışımı ve dayanıklı regresyon yöntemlerinin karşılaştırılması. DEUFMD. 2022;24:7–18.
MLA B.tekkeli, Anisya et al. “Aykırı değerler içeren VLF Verilerinin süzgeçlenmesinde budanmış Ortalama, Empirik Mod Ayrışımı Ve dayanıklı Regresyon yöntemlerinin karşılaştırılması”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi, vol. 24, no. 70, 2022, pp. 7-18, doi:10.21205/deufmd.2022247002.
Vancouver B.tekkeli A, Üge MA, Arslan MS. Aykırı değerler içeren VLF verilerinin süzgeçlenmesinde budanmış ortalama, Empirik Mod Ayrışımı ve dayanıklı regresyon yöntemlerinin karşılaştırılması. DEUFMD. 2022;24(70):7-18.

Dokuz Eylül Üniversitesi, Mühendislik Fakültesi Dekanlığı Tınaztepe Yerleşkesi, Adatepe Mah. Doğuş Cad. No: 207-I / 35390 Buca-İZMİR.