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Introduction to Denoising and Data Gap Filling of Seismic Reflection Data

  • R. K. Tiwari
  • R. Rekapalli
Chapter
  • 16 Downloads

Abstract

Seismic data is a mixture of several wanted (reflections, refractions) and unwanted (ground roll, diffractions, airwave etc.) signals. Different wave fields recorded by the seismic receiver can be seen from Fig. 1.1. Separation of wanted signal from such unwanted noises is therefore fundamental in geophysical signal processing. Especially, it is very difficult for a visual inspection to completely distinguish primary reflections and noise in the raw data of active seismic experiment for the interpretation of subsurface layers and their discontinuities. The primary reflections in the raw seismic data are always hindered by the wave fields arising from several unwanted sources such as: diffractions, ground roll, airwave etc. and unknown random signals. Separation of signal from the noise is an important task in geophysical signal processing industry. The accuracy of seismic data interpretation mainly depends on the quality of the data i.e., Signal-to-Noise Ratio (S/N). Therefore, separation of unwanted signals from the seismic field data is almost essential and a challenging task in seismic industry for accurate and geologically consistent physical interpretation of primary reflections for understanding the study area. In the following section, we begin with the basic classification of different kinds of noises based on their statistical and spectral characteristics before proceeding to discuss about denoising techniques used in seismic industry.

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© Capital Publishing Company 2020

Authors and Affiliations

  • R. K. Tiwari
    • 1
  • R. Rekapalli
    • 1
  1. 1.CSIR-NGRIHyderabadIndia

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