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Increasing the Efficiency of Seismic Data Acquisition via Compressive Sensing

机译:通过压缩传感提高地震数据采集的效率

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Optimal selection of locations for sensors in a seismic survey has been a long-standing issue for geophysicists.If we could sample the earth at two points per wavelength or better in all dimensions according to Nyquist sampling theory,design would not be an issue.The reality of limited access and funding requires us to make do with orders of magnitude fewer sampling points than Nyquist theory would dictate.The field of Compressive Sensing(CS)provides a new theory for non-uniform sampling that allows for using significantly fewer sensors than current practice in seismic exploration.We describe the application of CS concepts to seismic survey design.
机译:在地震调查中的传感器中的最佳选择是地球物理学家的长期问题。如果我们可以根据奈奎斯特采样理论在每个波长的两个点或更好地在所有尺寸下对地球进行样本,但设计不会是一个问题。获取和资金的现实要求我们做出比奈奎斯特理论更少的采样点的顺序。压缩传感(CS)的领域为非均匀采样提供了新的理论,其允许比当前更少的传感器更少的传感器地震勘探实践。我们描述了CS概念在地震调查设计中的应用。

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