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Virtual multi-offset reflection profiling with interferometric imaging for borehole radar

delete2017-03-01
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Lanbo Liu *
DOI:10.1016/j.sigpro.2016.06.028delete
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摘要

摘要

En 中文
Interferometry is one of the most advanced signal-processing and imaging techniques. It is widely used in geophysical detection and remote sensing. Application of interferometric processing significantly improves the resolution in geophysical imaging. This paper reports the application of an interferometric imaging approach to cross-hole multi-offset transmission (CHMOT) borehole radar data to generate a virtual single-hole, multi-offset reflection (SHMOR) profile with the validation of a real SHMOR data set. In subsurface material property imaging, SHMOR is an effective technique for interface and fracture detection. However, borehole radar survey in SHMOR fashion is not practical for most cases. Transforming cross-hole transmission mode radar data to virtual single-hole, multi-offset reflection data using a wave interferometric virtual source (WIVS) approach was proposed previously but not fully validated with real SHMOR data. In this study, we compare WIVS-derived virtual SHMOR to real SHMOR profiles using data sets acquired in two boreholes (SIMA1 and SIMA2) drilled into crystalline igneous bedrocks. As the calibration and validation, the reflection from borehole S1MA2 (as the known object) is clearly imaged by both the real and WIVS-derived virtual SHMOR profiles in SIMA1. The diffractions and amplitude decay from sharp stratigraphic change also registered at both the real and WIVS-derived virtual SHMOR profiles. The results of this study demonstrate the potential of the WIVS approach to improve structural imaging in bedrocks for hydrogeological, geothermal, and petroleum reservoir development applications. (C) 2016 Elsevier B.V. All rights reserved.
Keyword:
Borehole radar
Wave interferometric virtual source
Multi-offset reflection
Cross-hole
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期刊

Signal Processing 封面图
Signal Processing
IF:
3.6
论文数:
10.0K
被引数:
1.7W

机构

U
University of Connecticut
学者数:
2.4W
论文数: 2.2W
被引数: 2.5W
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