Abstract
Abstract When seismic waves propagate through oil and gas reservoirs, significant energy attenuation occurs, which affects the resolution of post-stack imaging data. High-resolution processing of post-stack data through attenuation compensation is theoretically significant and has practical industrial applications. In this study, two attenuation compensation methods with different principles, namely inverse Q filtering and curvelet transform, were selected for investigation. The advantages and disadvantages of the two methods in terms of resilience and compensation effect were analyzed using both models and actual data. The inverse Q-filtering method can achieve satisfactory results with clear physical significance and accurate Q values. It excels in accurately suppressing high-frequency noise by incorporating gain control into the compensation factor. On the other hand, the curvelet transform leverages the multi-scale decomposition of seismic signals, facilitating high-frequency recovery through mathematical operations, and exhibits stronger frequency extension capabilities. However, the curvelet transform lacks an effective means for precise noise suppression. The comparative analysis results in this study can provide a basis and guidance for practitioners in choosing between these two methods.
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