High-Resolution Processing Technology for Restoring Weak Signals Based on Harmonic Decomposition
Improving the resolution of seismic data processing is an effective means for predicting thin reservoirs.The primary objective of high-resolution processing is to effectively recover high-and low-frequency information of seismic data,broaden frequency bandwidth,and maintain signal-to-noise ratio and fidelity of seismic data.Using the high-resolution processing technology for restoring weak signals through harmonic decomposition,and based on compressed wavelet transform,the high-and low-frequency weak seismic signals were re-stored according to harmonic components.Firstly,the seismic signals within effective frequency bands were decomposed into various base-band signals by using the compressed wavelet transform.Then,the high-order and low-order harmonics of each baseband signal were calcu-lated and added to the wavelet transform coefficients.Finally,inverse wavelet transform was performed to restore the high-and low-frequen-cy weak signals.In this process,only the baseband signals within the effective frequency band are estimated,which helps to maintain the signal-to-noise ratio.The wavelet transform coefficients of seismic signals are consistent with the stratum reflection coefficients,verifying that the technology has high fidelity and good relative amplitude preservation.The actual application of the high-resolution processing tech-nology shows that it can maintain the signal-to-noise ratio and significantly widen the seismic bandwidth,resulting in clearer seismic profile breakpoints,higher resolution,and better identification of thin reservoirs of about 40 m thick at the depth below 6 000 m.
万方数据
维普
