Experimental study on identifying anomaly azimuth based on acoustic vector array of borehole acoustic reflection imaging

Abstract

Accurate anomaly azimuth identification is a major challenge in borehole acoustic reflection imaging. We propose an azimuth estimation method using an acoustic vector array to address this issue. This method was rigorously tested through a physical simulation experiment in a water-filled tank using a monopole acoustic source and an acoustic receiver station comprised of eight azimuthal elements. The proposed method involves the synthesis of multiazimuth acoustic pressure waveforms recorded by the receiver into multicomponent particle velocity waveforms. These waveforms are paired and subjected to coordinate conversion, yielding multiple groups of orthogonal component particle velocity waveforms. Each group underwent polarization analysis to obtain the direction of particle polarization on the horizontal plane and isolate the principal component particle velocity waveform. Using the particle polarization direction, the amplitude of the multiazimuth acoustic pressure waveform, and the type of echo mode, we accurately determined the azimuth of the anomaly, facilitating the creation of a spatial distribution image of the anomaly. Further validation of this method was conducted through a large-scale physical simulation experiment in a deep-water lake using a borehole acoustic reflection imaging instrument. The obtained experimental data were used to validate the effectiveness of this method. Finally, considering an actual logging environment, the feasibility of this method in a borehole environment was verified using numerical simulations and field data of acoustic detection of nearby wells. The present findings demonstrate that this novel method considerably enhances the accuracy and stability of the measurement of anomaly azimuth based on the particle polarization direction. In addition, this method effectively harnesses both acoustic pressure and particle velocity in borehole acoustic reflection imaging, exhibiting superior noise robustness, mitigating noise, and improving the signal-to-noise ratio of the echoes.