• Title/Summary/Keyword: bootstrapped differential semblance (BDS)

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Automatic Velocity Analysis by using an High-resolution Bootstrapped Differential Semblance Method (고해상도 Bootstrapped Differential Semblance를 이용한 자동 속도분석)

  • Choi, Hyungwook;Byun, Joongmoo
    • Geophysics and Geophysical Exploration
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    • v.16 no.4
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    • pp.225-233
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    • 2013
  • The accuracy of the automatic NMO velocity analysis, which is used for an effective and objective NMO velocity analysis, is highly affected by the velocity resolution of the velocity spectrum. In this study, we have developed an automatic NMO velocity algorithm, where the velocity spectra are created using high-resolution bootstrapped differential semblance (BDS), and the velocity analysis on CMP gathers is performed in parallel with MPI. We also compared the velocity models from the developed automatic NMO velocity algorithm with high-resolution BDS to those from BDS. To verify the developed automatic velocity analysis module we created synthetic seismic data from a velocity model including horizon layers. We confirmed that the developed automatic velocity analysis module estimated velocity more accurately. In addition, NMO velocity which yielded a CMP stacked section, where the coherency of the events were improved, was estimated when the developed module was applied to a marine field data set.

Automatic velocity analysis using bootstrapped differential semblance and global search methods (고해상도 속도스펙트럼과 전역탐색법을 이용한 자동속도분석)

  • Choi, Hyung-Wook;Byun, Joong-Moo;Seol, Soon-Jee
    • Geophysics and Geophysical Exploration
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    • v.13 no.1
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    • pp.31-39
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    • 2010
  • The goal of automatic velocity analysis is to extract accurate velocity from voluminous seismic data with efficiency. In this study, we developed an efficient automatic velocity analysis algorithm by using bootstrapped differential semblance (BDS) and Monte Carlo inversion. To estimate more accurate results from automatic velocity analysis, the algorithm we have developed uses BDS, which provides a higher velocity resolution than conventional semblance, as a coherency estimator. In addition, our proposed automatic velocity analysis module is performed with a conditional initial velocity determination step that leads to enhanced efficiency in running time of the module. A new optional root mean square (RMS) velocity constraint, which prevents picking false peaks, is used. The developed automatic velocity analysis module was tested on a synthetic dataset and a marine field dataset from the East Sea, Korea. The stacked sections made using velocity results from our algorithm showed coherent events and improved the quality of the normal moveout-correction result. Moreover, since our algorithm finds interval velocity ($\nu_{int}$) first with interval velocity constraints and then calculates a RMS velocity function from the interval velocity, we can estimate geologically reasonable interval velocities. Boundaries of interval velocities also match well with reflection events in the common midpoint stacked sections.