A borehole azimuthal acoustic-reflection imaging logging tool is equipped with several acoustic receiver stations evenly placed along the axial axis, each containing several azimuthal receiver elements evenly distributed around the circumference. These elements can obtain acoustic-waveform data from different source-receiver distances and azimuths in downhole measurements, which can be used to evaluate geologic structures within tens of meters from a well. Current imaging methods often suffer from widespread artifacts in the circumferential direction when imaging anomalies exist near the well, leading to low accuracy in azimuthal measurements, low value of the imaging signal-to-noise ratio (S/N), and difficulty in meeting the field application needs. We develop a 3D imaging technique based on the acoustic pressure-particle-velocity correlation. We comprehensively use more measurement information and the directional sensitivity of particle-velocity sensors to improve the target azimuthal detection performance and imaging S/N. Our technique is comprehensively described based on waveform data obtained through finite-difference numerical simulation. Then, this technique is applied to experimental testing when there is a target well near the measurement well, and good verification results are obtained. Finally, we apply the technique to process field logging data, obtaining azimuthal and spatial-position information about geologic structures in the formation surrounding the measurement well. The obtained imaging results are compared with logging data processing results obtained using borehole dipole S-wave reflection imaging and microresistivity imaging. The results indicate that compared with 3D spatial-scanning imaging using acoustic-pressure-waveform similarity coefficients, our technique suppresses widespread artifacts of false azimuths and exhibits better azimuthal detection performance for anomalies near the well. Thus, the comprehensive use of acoustic pressure and particle-velocity information in borehole acoustic fields offers improved noise immunity and imaging S/Ns, which is beneficial for detecting weak waveform signals.