Publications

Low-frequency shadow zone, associated with presence of hydrocarbon,, provide useful information for reservoir characterization. The attenuation of high-frequency energy in the reservoir is predicted as the main factor affecting the low frequency anomaly, which shifts the dominant frequency to the low-frequency range and commonly occurs at or beneath the reservoir level. Time-frequency decomposition, the so-called spectral decomposition of a seismic signal, aims to characterize the time-dependent frequency response of subsurface rocks and reservoirs. One of the methods for computing a time-frequency map for non-stationary signals is the continuous-wavelet transform (CWT). It produces a time-frequency map in which the amplitudes of individual frequencies (rather than frequency bands) are represented. This method provides good frequency resolution at low frequencies, and is therefore effective in detecting low-frequency shadows. We have conducted time-frequency analyses with post-stack data sets from South Sumatra Basin. Comparison of individual frequency magnitude from such a 3D volume with a close correlation with well production performance can help detect low-frequency shadows - possibly caused by hydrocarbon reservoirs. Seismic data shows bright amplitudes in several reservoir locations, indicating recognised hydrocarbon zones. Our time-frequency analysis indicates that slicing of magnitude with a frequency of 20 Hz is optimal to map the low frequency shadow zone associated with hydrocarbon reservoirs.Key words: CWT, Low-frequency shadow, and reservoir