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Adaptive Sampling of Potential-Field Data: A Direct Approach to Compressive Inversion

Authors
Leon Foks (Colorado School of Mines) | Richard Krahenbuhl (Colorado School of Mines) | Yaoguo Li (Colorado School of Mines)
Document ID
SEG-2012-1584
Publisher
Society of Exploration Geophysicists
Source
2012 SEG Annual Meeting, 4-9 November, Las Vegas, Nevada
Publication Date
2012
Document Type
Conference Paper
Language
English
Copyright
2012. Society of Exploration Geophysicists
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23 since 2007
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Price: USD 21.00
SUMMARY

In this paper, we present a direct and reliable approach to the adaptive down-sampling of potential-field data for large inversion problems. In contrast to traditional down-sampling methods, the approach significantly reduces the number of data parameters in relatively smooth/quiet regions of the data, while preserving the signal anomalies that contain the relevant target information. This allows for a simple and effective approach for compressive inversion of large datasets, without the need for large computing power, while maintaining the resolution of the recovered structures. The formulation has the flexibility to decimate large data sets for an optimal balance between data number and signal shape, or data can be decimated more conservatively if desired. We first present the data adaptive down-sampling technique, and then demonstrate the approach, applied to both synthetic and field data.
File Size  3 MBNumber of Pages   5

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