[논문]GPR 자료 해석에 유용한 속성들 소개 및 적용 사례 분석

유희은; 정인석; 임보성; 남명진

doi:10.7582/gge.2021.24.3.113

GPR 자료 해석에 유용한 속성들 소개 및 적용 사례 분석
Introduction to Useful Attributes for the Interpretation of GPR Data and an Analysis on Past Cases 원문보기

지구물리와 물리탐사 = Geophysics and geophysical exploration, v.24 no.3, 2021년, pp.113 - 130

유희은 (세종대학교 에너지자원공학과) , 정인석 (세종대학교 에너지자원공학과) , 임보성 (한국석유공사) , 남명진 (세종대학교 에너지자원공학과)

초록
AI-Helper

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.

Abstract ▼ AI-Helper

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.

주제어

표/그림 (18)

그림 Fig. 1. Conventional seismic attributes. The gray highlights indicate the attributes that are highly applicable to ground-penetrating radar data (modified from SEG Wiki).
그림 Fig. 2. Real and imaginary parts of a complex trace and the complex trace with time.
그림 Fig. 3. (a) Shpaes of the real and imaginary parts and (b) cosine of the instantaneous phase with (-1, 1).
그림 Fig. 4. (a) Real and imaginary parts of the trace, (b) instantaneous amplitude with (a), (c) instantaneous phase, and (d) instantaneous frequency. Red circles indicate reverse instantaneous phase with a negative instantaneous frequency. Green circles indicate instantaneous phase changing without reversal with a positive instantaneous frequency.
그림 Fig. 5. Three-dimensional visualization by means of the isoamplitude surfaces of the complex trace amplitude using difference thresholds of (a) 50% and (b) 40%; an arrow denotes a linear anomaly due to a ditch in the bedrock (Nuzzo et al., 2002).
그림 Fig. 6. (a) Prerelease of light nonaqueous phase liquid (b) image after 2 weeks, showing a high amplitude because of nonconductive light non aqueous phase liquid (LNAPL) and (c) image after 66 months, showing a low-amplitude zone (shadow zone) created because of biodegradation (Hwang et al., 2008).
그림 Fig. 7. (a) Ground-penetrating radar survey result from the light nonaqueous phase liquid spilled sand box, (b) instantaneous amplitude, (c) similarity slice of three-dimensional data at a depth of 0.05 m, and (d) cross section of (c) (Lu et al., 2021).
그림 Fig. 8. (a) Ground-penetrating radar profile received from a contaminated area to a noncontaminated area. The white box indicates the shadow zone created as the effect of a gasoline (light nonaqueous phase liquid) contamination, (b) and (c) are the instantaneous amplitudes from noncontaminated areas (trace 450-461) and contaminated area (trace 800-811), and (d) and (e) are instantaneous frequency from the same area with (b) and (c), respectively (Liu and Oristaglio, 1998).
그림 Fig. 9. (a) Plan view of the explored bridge with different strengths. (b) Maximum amplitude and (c) maximum absolute amplitude for the centers of each deck, where blue indicates the SE leg and red shows the NE leg (Morris et al., 2019).
그림 Fig. 10. At gem-bearing zones in the Himalaya pegmatite mine: (a) the ground-penetrating radar amplitude to identify gems that have not been excavated and the (b) instantaneous amplitude, (c) instantaneous phase, and (d) instantaneous frequency of the area corresponding to (a) (Patterson and Cook, 2000).
그림 Fig. 12. For an ancient kiln, (a) the root-mean-squared amplitude is high and (b) the maximum peak time is also high. For the ancient tomb, the (c) average peak amplitude of demarcated by the white dashed line is higher than the other area and (d) a continuous event at the instantaneous phase determines the boundary (Zhao et al., 2012).
그림 Fig. 11. (a) Amplitude time-slice overlays instantaneous amplitude with (b) homogeneity and (c) energy. Green triangles indicate that the block may be associated with the building foundation, the almost continuous features marked by white triangles are probably related to wall remains, and the cyan triangles can be interpreted as ancient roads/passageways. Then, the main structures can be interpreted as shown in (d) (Zhao et al., 2016a).
그림 Fig. 13. (a) Ground-penetrating radar amplitude and the arrows (a, b, c, and d) show examples of reflection at different locations, (b) cosine of the instantaneous phase, with the dashed white line indicating the transitional zone between discontinuous shallow structures, and (c) the similarity attribute calculated for the cosine of the instantaneous phase (Zhao et al., 2013).
그림 Fig. 14. (a) Processed amplitude profile, (b) corresponding cosine phase profile, (c) picked horizons, (d) and those horizons identified as the second phases of reflections with at least two recognized phases (the five main reflectors are marked H1-H5). Positive amplitudes are marked in green, and negative amplitudes are shown in red using 500 MHz antenna (Dossi et al., 2015).
그림 Fig. 15. (a) First derivative of the amplitude, (b) instantaneous frequency, (c) similarity, (d) homogeneity by gray level cooccurrence matrix (GLCM) from Mt. Nanin in the Alps and the boundary between the firn and debris are quite distinct (Zhao et al., 2016b).
그림 Fig. 17. Results of a two-dimensional texture analysis of an archeological profile: (a) reflection amplitude, (b) contrast, (c) entropy, (d) homogeneity, and (e) interpretation (Zhao et al., 2016a).
그림 Fig. 16. (a) Amplitude profile, (b) entropy, and (c) homogeneity from an archeological site (Zhao et al., 2016b).
그림 Fig. 18. (a) Ground-penetrating radar data reflected from the cavity and (b) edge detection (Kim et al., 2017).

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저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

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