Physics-Constrained Automated Well-to-Seismic Tie Based on Time-Frequency Key Feature Point Matching

The high-resolution characterization of subsurface hydrocarbon reservoirs critically depends on the integration of seismic and well log data. However, the precision of well-to-seismic tie procedures is often compromised by inaccuracies in time-depth conversion curves, stemming from imprecise migration velocity errors, scale discrepancy, and the inherent domain disparity between seismic data (time domain) and well log data (depth domain). Traditional methods rely on iterative wavelet estimation and manual adjustments, leading to wavelet-depth curve coupling problems, reduced accuracy, and significant time consumption. To address these limitations, we propose a novel automated time-depth conversion curve correction method. This approach leverages key feature matching in the time-frequency domain of well log reflection coefficients and borehole-side seismic traces, incorporating dual constraints: stratigraphic constraints in the time domain and spectral notch points in the frequency domain. By directly aligning with well log reflection coefficients, this time-frequency joint analysis eliminates the need for wavelet estimation as well as iterative and interactive processes. Experiments performed using both synthetic and field data demonstrate the validity and effectiveness of the proposed method compared with traditional iterative matching methods and interactive commercial software.