Geophysics and Geophysical Exploration (지구물리와물리탐사)

Korean Society of Earth and Exploration Geophysicists (한국지구물리·물리탐사학회)
권호 표지
DOI QR코드

DOI QR Code

Introduction to Useful Attributes for the Interpretation of GPR Data and an Analysis on Past Cases

GPR 자료 해석에 유용한 속성들 소개 및 적용 사례 분석

  • Yu, Huieun (Department of Energy and Mineral Resources Engineering, Sejong University) ;
  • Joung, In Seok (Department of Energy and Mineral Resources Engineering, Sejong University) ;
  • Lim, Bosung (Korea National Oil Corporation) ;
  • Nam, Myung Jin (Department of Energy and Mineral Resources Engineering, Sejong University)
  • 유희은 (세종대학교 에너지자원공학과) ;
  • 정인석 (세종대학교 에너지자원공학과) ;
  • 임보성 (한국석유공사) ;
  • 남명진 (세종대학교 에너지자원공학과)
  • Received : 2021.05.14
  • Accepted : 2021.08.30
  • Published : 2021.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

Recently, ground-penetrating radar (GPR) surveys have been actively employed to obtain a large amount of data on occurrences such as ground subsidence and road safety. However, considering the cost and time efficiency, more intuitive and accurate interpretation methods are required, as interpreting a whole survey data set is a cost-intensive process. For this purpose, GPR data can be subjected to attribute analysis, which allows quantitative interpretation. Among the seismic attributes that have been widely used in the field of exploration, complex trace analysis and similarity are the most suitable methods for analyzing GPR data. Further, recently proposed attributes such as edge detecting and texture attributes are also effective for GPR data analysis because of the advances in image processing. In this paper, as a reference for research on the attribute analysis of GPR data, we introduce the useful attributes for GPR data and describe their concepts. Further, we present an analysis of the interpretation methods based on the attribute analysis and past cases.

지반 침하, 도로 안전성과 같은 사회적 이슈로 지하 공동 분포를 조사하기 위한 지표투과레이더(ground penetrating radar, GPR) 탐사가 활발히 진행되면서 자료의 양도 함께 증가하고 있다. 하지만 비용과 시간의 효율성을 고려해보았을 때, 모든 자료를 해석할 수 없기 때문에 더욱 직관적이고 정확한 판단이 가능한 해석법이 필요하다. 이러한 문제를 개선하기 위해 정량적 해석이 가능한 속성 분석법이 제안되고 있다. 탄성파 해석에서 많이 사용해온 속성 분석 중 GPR 자료에 적용할 수 있는 속성으로는 복소 트레이스(complex trace)와 유사성(similarity)이 대표적이다. 또한, 최근 영상처리 기술의 발달로 개발된 새로운 속성인 모서리탐지 속성, 이미지 질감 속성 등도 적용성이 있다. 이 논문에서는 GPR 자료 속성분석 연구의 기초를 마련하기 위해, GPR에 적용할 수 있는 속성 분석들을 소개하고 이들의 개념에 대해 기술한 뒤, 속성분석에 기초한 해석법과 다양한 분야에서 활용한 사례를 분석하고자 한다.

Keywords

Acknowledgement

본 연구는 환경부 재원의 지중환경오염·위해관리기술개발사업(No. 2018002440005)과 과학기술정보통신부의 재원으로 한국연구재단(No. 2020M2C7A1A02078235)의 지원을 받아 수행된 연구입니다.

References

  1. Atekwana, E. A., Sauck, W. A., and Werkema Jr, D. D., 2000, Investigations of geoelectrical signatures at a hydrocarbon contaminated site, Journal of Applied Geophysics, 44(2-3), 167-180, https://scholar.google.co.kr/citations?view_op=view_citation&hl=ja&user=gRmYp8QAAAAJ&citation_for_view=gRmYp8QAAAAJ:u5HHmVD_uO8C https://doi.org/10.1016/S0926-9851(98)00033-0
  2. Atekwana, E. A., Sauck, W. A., Abdel Aal, G. Z., and Werkema Jr, D. D., 2002, Geophysical investigation of vadose zone conductivity anomalies at a hydrocarbon contaminated site: implications for the assessment of intrinsic bioremediation, Journal of Environmental & Engineering Geophysics, 7(3), 103-110, https://scholar.google.com/citations?view_op=view_citation&hl=en&user=YL5VtkMAAAAJ&citation_-for_view=YL5VtkMAAAAJ:9vf0nzSNQJEC https://doi.org/10.4133/jeeg7.3.103
  3. Anstey, N., 2005, Attributes in color: the early years, CSEG Recorder, 30(3), 12-15, https://csegrecorder.com/articles/view/attributes-in-color-the-early-years
  4. Bahorich, M., and Farmer, S., 1995, 3-D seismic discontinuity for faults and stratigraphic features: The coherence cube, The Leading Edge, 14(10), 1053-1058, https://scholar.google.com/citations?view_op=view_citation&hl=en&user=Qn8DojsAAAAJ&citation_for_view=Qn8DojsAAAAJ:eQOLeE2rZwMC https://doi.org/10.1190/1.1437077
  5. Baker, G. S., Steeples, D. W., Schmeissner, C., Pavlovic, M., and Plumb, R., 2001, Near-surface imaging using coincident seismic and GPR data, Geophysical Research Letters, 28(4), 627-630, https://www.researchgate.net/publication/248813691_Near-surface_imaging_using_coincident_seismic_and_GPR_data https://doi.org/10.1029/2000gl008538
  6. Bodine, J. H., 1984, Waveform analysis with seismic attributes. In SEG Technical Program Expanded Abstracts 1984 (505-509). Society of Exploration Geophysicists, https://library.seg.org/doi/abs/10.1190/1.1894172
  7. Boeniger, U., and Tronicke, J., 2010, Improving the interpretability of 3D GPR data using target-specific attributes: application to tomb detection, Journal of Archaeological Science, 37(2), 360-367, DOI: 10.1016/j.jas.2010.01.013
  8. Chopra, S., and Alexeev, V., 2006, Applications of texture attribute analysis to 3D seismic data, The Leading Edge, 25(8), 934-940, https://doi.org/10.1190/1.2335155
  9. Chopra, S., and Marfurt, K. J., 2005, Seismic attributes-A historical perspective, Geophysics, 70(5), 3SO-28SO, https://doi.org/10.1190/1.2098670
  10. Chopra, S., and Marfurt, K. J., 2007, Seismic attributes for prospect identification and reservoir characterization, Society of Exploration Geophysicists and European Association of Geoscientists and Engineers, https://doi.org/10.1190/1.9781560801900
  11. Davis, J. L., and Annan, A. P., 1989, Ground-penetrating radar for high-resolution mapping of soil and rock stratigraphy 1, Geophysical Prospecting, 37(5), 531-551, https://doi.org/10.1111/j.1365-2478.1989.tb02221.x
  12. De Rooij, M., and Tingdahl, K., 2002, Meta-attributes-the key to multivolume, multiattribute interpretation, The Leading Edge, 21(10), 1050-1053, http://dx.doi.org/10.1190/1.1518445
  13. Dossi, M., Forte, E., and Pipan, M., 2015, Auto-picking and phase assessment by means of attribute analysis applied to GPR pavement inspection, 2015 8th International Workshop on Advanced Ground Penetrating Radar (IWAGPR), 1-4, http://dx.doi.org/10.1109/IWAGPR.2015.7292637
  14. Dubois, L. H., and Nuzzo, R. G., 1992, Synthesis, structure, and properties of model organic surfaces, Annual Review of Physical Chemistry, 43(1), 437-463, https://doi.org/10.1146/annurev.pc.43.100192.002253
  15. Fisher, E., McMechan, G. A., and Annan, A. P., 1992, Acquisition and processing of wide-aperture ground-penetrating radar data, Geophysics, 57(3), 495-504, https://doi.org/10.1190/1.1443265
  16. Forte, E., and Pipan, M., 2008, Integrated seismic tomography and ground-penetrating radar (GPR) for the high-resolution study of burial mounds (tumuli), Journal of Archaeological Science, 35(9), 2614-2623, https://doi.org/10.1016/j.jas.2008.04.024
  17. Gao, D., 2003, Volume texture extraction for 3D seismic visualization and interpretation, Geophysics, 68(4), 1294-1302, https://doi.org/10.1190/1.1598122
  18. Gao, D., 2011, Latest developments in seismic texture analysis for subsurface structure, facies, and reservoir characterization: A review, Geophysics, 76(2), 1-13, http://dx.doi.org/10.1190/1.3553479
  19. Haralick, R. M., Shanmugam, K., and Dinstein, I. H., 1973, Textural features for image classification, IEEE Transactions on Systems, Man, and Cybernetics, 6, 610-621, https://doi.org/10.1109/TSMC.1973.4309314
  20. Harris, C. G., and Stephens, M., 1988, A combined corner and edge detector, Alvey Vision Conference, 10-5244, http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.1604
  21. Hwang, Y. K., Endres, A. L., Piggott, S. D., and Parker, B. L., 2008, Long-term ground penetrating radar monitoring of a small volume DNAPL release in a natural groundwater flow field, Journal of Contaminant Hydrology, 97(1-2), 1-12, https://doi.org/10.1016/j.jconhyd.2007.11.004
  22. Kim, B., Seol, S. J., and Byun, J., 2017, Application of image processing techniques to GPR data for the reliability improvement in subsurface void analysis, Geophysics and Geophysical Exploration, 20(2), 61-7 (in Korean with English abstract), https://doi.org/10.7582/GGE.2017.20.2.061
  23. Liu, L., and Oristaglio, M., 1998, May GPR signal analysis: Instantaneous parameter estimation using the wavelet transform, In Proceedings of the 7th International Conference on Ground Penetrating Radar (219-224), https://www.semanticscholar.org/paper/GPR-SIGNAL-ANALYSIS-%3AINSTANTANEOUS-PARAMETER-USING-Liu/3e874328741f9178b5b43fec150b0c9ce4cba5e1
  24. Love, P. L., and Simaan, M., 1984, Segmentation of stacked seismic data by the classification of image texture, SEG Technical Program Expanded Abstracts 1984 (480-482), Society of Exploration Geophysicists, https://doi.org/10.1190/1.1894051
  25. Lu, Q., Wang, Y., and Li, H., 2021, GPR attribute analysis for the detection of LNAPL contaminated soils, IOP Conference Series: Earth and Environmental Science, 660(1), 12-33, https://iopscience.iop.org/article/10.1088/1755-1315/660/1/012033/meta
  26. Marfurt, K. J., Kirlin, R. L., Farmer, S. L., and Bahorich, M. S., 1998, 3-D seismic attributes using a semblance-based coherency algorithm, Geophysics, 63(4), 1150-1165, https://doi.org/10.1190/1.1444415
  27. Morris, I., Abdel-Jaber, H., and Glisic, B., 2019, Quantitative attribute analyses with ground penetrating radar for infrastructure assessments and structural health monitoring, Sensors, 19(7), 1637, https://doi.org/10.3390/s19071637
  28. Nuzzo, L., Leucci, G., Negri, S., Carrozzo, M. T., and Quarta, T., 2002, Application of 3D visualization techniques in the analysis of GPR data for archaeology, Annals of Geophysics, http://hdl.handle.net/2122/721
  29. Patterson, J. E., and Cook, F. A., 2000, Application of complex trace analysis for improved target identification in gemtourmaline-bearing pegmatites in the Himalaya mine, San Diego County, California, 8th International Conference on Ground Penetrating Radar, 653-657, https://doi.org/10.1117/12.383537
  30. Taner, M. T., and Sheriff, R. E., 1977, Application of amplitude, frequency, and other attributes to stratigraphic and hydrocarbon determination: Section 2. Application of seismic reflection configuration to stratigraphic interpretation, American Association of Petroleum Geologists, https://archives.datapages.com/data/specpubs/seismic1/data/a165/a165/0001/0300/0301.htm
  31. Taner, M. T., Koehler, F., and Sheriff, R. E., 1979, Complex seismic trace analysis, Geophysics, 44(6), 1041-1063, https://doi.org/10.1190/1.1440994
  32. Taner, M. T., 2001, Seismic attributes, CSEG Recorder, 26(7), 49-56, https://csegrecorder.com/articles/view/seismic-attributes
  33. Tillard, S., and Dubois, J. C., 1995, Analysis of GPR data: Wave propagation velocity determination, Journal of Applied Geophysics, 33(1-3), 77-91, https://doi.org/10.1016/0926-9851(95)90031-4
  34. Ursin, B., 1983, Review of elastic and electromagnetic wave propagation in horizontally layered media, Geophysics, 48(8), 1063-1081, https://doi.org/10.1190/1.1441529
  35. Young, R. A., Deng, Z., Marfurt, K. J., and Nissen, S. E., 1997, 3-D dip filtering and coherence applied to GPR data: A study, The Leading Edge, 16(6), 921-928, https://doi.org/10.1190/1.1437699
  36. Zhao, W. K., Tian, G., Wang, B. B., Shi, Z. J., and Lin, J. X., 2012, Application of 3D GPR attribute technology in archaeological investigations, Applied Geophysics, 9(3), 261-269, https://doi.org/10.1007/s11770-012-0336-2
  37. Zhao, W., Forte, E., Pipan, M., and Tian, G., 2013, Ground penetrating radar (GPR) attribute analysis for archaeological prospection. Journal of Applied Geophysics, 97, 107-117, https://doi.org/10.1016/j.jappgeo.2013.04.010
  38. Zhao, W., Forte, E., and Pipan, M., 2016a, Texture attribute analysis of GPR data for archaeological prospection, Pure and Applied Geophysics, 173(8), 2737-2751, https://doi.org/10.1007/s00024-016-1355-3
  39. Zhao, W. K., Forte, E., Dossi, M., and Pipan, M., 2016b, Integrated attribute analysis for improved GPR data interpretation, 6th International Conference on Ground Penetrating Radar (GPR) (1-5), DOI: 10.1109/ICGPR.2016.7572678