Parametric Analysis of Acoustic Sand Detectors in Multiphase Flow Pipelines

Summary Acoustic sand detectors (ASDs) are critical for monitoring sand production in oil and gas pipelines. ASDs capture the noise caused by the flow as well as the noise caused by sand hitting the pipe walls. The lowest sand rate at which detectors fail to differentiate flow or background noise from sand impact noise is known as the threshold sand rate (TSR). While existing studies rely on ASDs to capture sand-wall impact noise, a gap persists in systematically predicting TSR under varied operational configurations. This study introduces a novel AI-driven method to determine TSR by analyzing ASD background noise, validated through large-scale multiphase flow experiments (pipe diameters: 50.8–101.6 mm; sand size: 150 μm) covering annular, slug-churn, and dispersed-bubble flows (gas velocity: 7–35 m/s; liquid velocity: 0.09–3.35 m/s). Another finding of the study is to examine the critical installation parameters of ASDs which can affect the performance of ASDs. Key findings reveal that ASD placement downstream of elbows enhances sand noise detection compared with upstream positions, while a 12 o’clock sensor orientation outperforms 3 o’clock. Additionally, interference between sand impacts in closely spaced (2D) metallic elbows reduces measurement accuracy, unlike configurations with nonmetallic or distanced (7D) elbows. These insights enable operators to optimize ASD installation locations and predict TSR from background noise, directly addressing well integrity challenges caused by sand erosion. Future work will validate this method across diverse field environments to bridge laboratory and real-world performance.