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Sonification of geophysical data through time–frequency analysis: theory and applications
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ABSTRACTIn this paper, we introduce a new method of geophysical data interpretation based on simultaneous analysis of images and sounds. The final objective is to expand the interpretation workflow through multimodal (visual–audio) perception of the same information. We show how seismic data can be effectively converted into standard formats commonly used in digital music. This conversion of geophysical data into the musical domain can be done by applying appropriate time–frequency transforms. Using real data, we demonstrate that the Stockwell transform provides a very accurate and reliable conversion. Once converted into musical files, geophysical datasets can be played and interpreted by using modern computer music tools, such as sequencers. This approach is complementary and not substitutive of interpretation methods based on imaging. It can be applied not only to seismic data but also to well logs and any type of geophysical time/depth series. To show the practical implications of our integrated visual–audio method of interpretation, we discuss an application to a real seismic dataset in correspondence of an important hydrocarbon discovery.
Title: Sonification of geophysical data through time–frequency analysis: theory and applications
Description:
ABSTRACTIn this paper, we introduce a new method of geophysical data interpretation based on simultaneous analysis of images and sounds.
The final objective is to expand the interpretation workflow through multimodal (visual–audio) perception of the same information.
We show how seismic data can be effectively converted into standard formats commonly used in digital music.
This conversion of geophysical data into the musical domain can be done by applying appropriate time–frequency transforms.
Using real data, we demonstrate that the Stockwell transform provides a very accurate and reliable conversion.
Once converted into musical files, geophysical datasets can be played and interpreted by using modern computer music tools, such as sequencers.
This approach is complementary and not substitutive of interpretation methods based on imaging.
It can be applied not only to seismic data but also to well logs and any type of geophysical time/depth series.
To show the practical implications of our integrated visual–audio method of interpretation, we discuss an application to a real seismic dataset in correspondence of an important hydrocarbon discovery.
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