A Real-Time Slowness Picking and Tracking Method for Borehole Acoustic Logging

Summary Slowness estimation is a most basic task for array acoustic logging, and practical demands for its realtime applications is ever increasing for wellsite evaluations of near wellbore geology. This paper presents a time-efficient solution that can derive robust slowness estimates even under unfavorable conditions related to borehole and the data. To handle practical issues (e.g., DC components, noises), a pre-whitening STC calculation is applied to the time-differentials of original waveform, which in return remarkably enhances the ability in capturing and characterizing coherent wave characteristics. On this basis, we introduce the exponential moving averaging (EMA) technique to drive real-time slowness estimation process, and it plays a crucial role in compensating blurred slowness features and screening out unreasonable and wrong slowness picks. As demonstrated by examples in this paper, the proposed method can derive simultaneous slowness estimation for compressional and shear wave (in hard formation), generally within 40 milli-seconds for each logging depth. Moreover, by tuning EMA parameter β and confining the application scope, the method is proven adaptable to accommodate cases with rapid slowness variations.