• Geophysics and Geophysical Exploration
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• v.12 no.2
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• pp.192-198
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• 2009

Side scan sonar and SBP (sub-bottom profiler) play a very important role in the survey for seafloor imaging and sub-bottom profiling. In this study, we have acquired side scan sonar and SBP data from the artificial reef area. We applied digital image processing techniques to side scan sonar data in order to improve an image quality. For the enhancement of data quality and image resolution, we applied the typical seismic data processing sequence including gain recovery, muting, spectrum analysis, predictive deconvolution, migration to SBP data. We could easily estimate if artificial reef structures were settled properly and their distribution on the seafloor from the integrated interpretation of side scan sonar and SBP data. From the sampling analysis of seabed sediments, texture filtering of side scan sonar data and SBP data interpretation, we could evaluate the sediment type, distribution and thickness of seafloor sediments in detail.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.