An autocorrelation localization method based on a multi-scale physically constrained wavelet transform for tubing leakage

Tubing leakage in gas wells poses a critical risk to wellbore integrity and production safety. Localizing these leaks using wellhead acoustic signals, without requiring a shutdown, offers a promising solution. This study proposes an automatic tubing leakage localization method based on multi-scale physically constrained wavelet transform (PCWT) and an autocorrelation localization technique. This approach transforms the conventional manual extraction of characteristic peaks into an automatic, physics-guided decision process for characteristic delays. First, a low-frequency branch provides anchor constraints, and a composite level score (CR), which considers multiple influencing factors, is introduced to evaluate the decomposition levels of the wavelet transform. Subsequently, candidate level fusion and a cross-scale negative peak density prompting mechanism are constructed to suppress spurious time-delay characteristic peaks and valleys. The method was evaluated using 50 acoustic records collected at 5 leakage positions on a full-size wellbore leakage experimental device. It was compared against four representative methods and 4 ablation variants. PCWT achieved a failure rate of 4.0%, with position-level average relative errors of 3.67% for leakage-location estimation and 0.63% for annulus-length estimation. These results demonstrate that the proposed method can facilitate the transition of tubing leakage localization from manual interpretation to automatic identification, offering a novel technical approach for leakage monitoring and integrity management in complex wellbore conditions.