A Method of Perforation Depth Investigation Using Borehole Acoustic Logging

Utilizing perforating method to achieve final completion is the main means to develop oil well. The perforation depth determines its precision and accuracy, which is of great significance in ensuring the quality of the perforation. High-quality perforation can largely reduce the damage of drilling to the reservoir and make the well production capacity desirable. However, detecting the perforation depth faces the challenges of formation complexity and measurement technology limitations. Many logging tools have limited spatial resolution and may not be able to accurately measure small variations in perforation depth. When using electromagnetism for measurements, metal structures and formations in the downhole environment may interfere and attenuate the signal. Compared to electromagnetic waves, acoustic waves provide better penetration into the formation, offer higher vertical resolution, and can be used in the wellbore environment without the effects of electromagnetic interference. This paper presents a new data processing method that extracts sufficient detail from acoustic logging data to accurately reflect changes in the perforation depth. The presence of perforations alters the formation structure, causing Stoneley waves to interact with them and generate multiple reflected waves. This method utilizes the propagation characteristics of Stoneley waves in wellbore fluids to study the wavefield of Stoneley wave reflections. Through slowness-time coherence (STC) processing combined with wavefield separation techniques, the reflected Stoneley waves from the top and bottom regions of the perforations are isolated. The transformation from the time domain to the time- slowness domain amplifies the characteristics of Stoneley waves affected by perforations, which can be used to evaluate the perforation depth. The proposed method is validated by means of a finite element simulation example. The model with steel casing, cement, formation and perforation is built, and the acoustic time-domain signals with different perforation cluster depths from 0.5 m to 2.66 m are obtained by simulation. As the perforation depth increases, the time delay between the primary and secondary reflected waves increases, which are reflected in the STC map. The accurate inversion results validate the effectiveness of the method in distinguishing the weak reflection signals affected by the perforation. Thus, the technique provides a new method for amplifying weakly reflected signals, accurately reflecting the characteristics of signals affected by perforation depth, and obtaining reliable depth estimates.