Knowledge of Q is desirable for improving seismic resolution through inverse Q filtering, facilitating amplitude analysis and seismic interpretation. However, the question of reliable Q estimation remains, especially in case of unfavorable signal-to-noise ratio (SNR). In addition, estimating Q from VSP data or even reflection data in presence of moderate noise with sufficient accuracy is still very challenging. To address this problem, a matchfilter method for Q estimation is proposed and

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... ted using synthetic 1D, 2D data and field data in this paper. Given two narrow time windows as might be used in the spectral-ratio method, we compute minimum phase equivalent wavelets for each window and then, by direct search over a broad Q range, we find the optimal forward Q filter that best matches the shallow wavelet to the deeper one. Testing results show that the proposed method is, compared to the spectral-ratio method, more robust to noise and more suitable for the Q estimation from reflection data, and has the potential to indentify a localized low Q zone of the subsurface, which can be used as a gas indicator.