TY - GEN
T1 - Instantaneous spectral analysis
T2 - 20th Symposium on the Application of Geophysics to Engineering and Environmental Problems: Geophysical Investigation and Problem Solving for the Next Generation, SAGEEP 2007
AU - Bradford, John H.
AU - Wu, Yafei
PY - 2007
Y1 - 2007
N2 - In recent years it has been demonstrated that time-frequency analysis, or spectral decomposition, can differentiate small-scale features associated with hydrocarbon reservoirs in seismic reflection data. Similar reflectivity anomalies are sometimes induced in ground-penetrating radar (GPR) data by electric property variations caused by groundwater contaminants that are often below the conventional resolution of the signal. Isolating and mapping discreet components of the time-frequency spectrum using spectral decomposition can highlight details of a contaminant distribution. The windowed fourier transform was an early approach to spectral decomposition, however wavelet based approaches have superior time localization properties. Here, we give the wavelet matching spectral decomposition algorithm we developed at the Houston Advanced Research Center in the mid 1990s. In a 3D GPR dataset acquired at the former Wurtsmith AFB, MI, the time-frequency attributes image details of a hydrocarbon plume not resolved by conventional instantaneous attributes or GPR AVO attributes.
AB - In recent years it has been demonstrated that time-frequency analysis, or spectral decomposition, can differentiate small-scale features associated with hydrocarbon reservoirs in seismic reflection data. Similar reflectivity anomalies are sometimes induced in ground-penetrating radar (GPR) data by electric property variations caused by groundwater contaminants that are often below the conventional resolution of the signal. Isolating and mapping discreet components of the time-frequency spectrum using spectral decomposition can highlight details of a contaminant distribution. The windowed fourier transform was an early approach to spectral decomposition, however wavelet based approaches have superior time localization properties. Here, we give the wavelet matching spectral decomposition algorithm we developed at the Houston Advanced Research Center in the mid 1990s. In a 3D GPR dataset acquired at the former Wurtsmith AFB, MI, the time-frequency attributes image details of a hydrocarbon plume not resolved by conventional instantaneous attributes or GPR AVO attributes.
UR - https://www.scopus.com/pages/publications/84867271743
M3 - Conference contribution
AN - SCOPUS:84867271743
SN - 9781604239546
T3 - Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP
SP - 1133
EP - 1142
BT - Environmental and Engineering Geophysical Society - 20th SAGEEP 2007
Y2 - 1 April 2007 through 5 April 2007
ER -