Liquid loading is a persistent challenge in onshore and offshore gas wells, particularly at low gas rates. Empirical correlations are used commonly to detect liquid loading, but this method often lacks precision in field applications because of oversimplified assumptions regarding liquid behavior and flow‑regime consistency. In the complete paper, the authors introduce a data‑driven approach for liquid-loading detection and prediction (LLDP) that harnesses high-frequency gas-rate and tubinghead‑pressure measurements to identify the onset of liquid loading and use it to correct critical rates computed by empirical methods.
Introduction
Leveraging commonly available surface gas-rate and tubinghead-pressure measurements collected at high frequency, the proposed LLDP method computes diagnostic statistical proxy features indicative of flow instability. Upon detection, subsequent adjustment to gas rates using feedback control facilitates the determination of corrected critical rate by calibration of empirical correlations continuously.
