This paper presents a novel acoustic wave-based method for the detection of leakage in downhole tubing of offshore gas wells. The localization model is developed on the basis of analyzing the propagation model of leakage acoustic waves and the critical factors in localization. The proposed method is validated using experimental laboratory investigations that are conducted to locate tubing leakage by setting five holes at different positions on the tubing wall. A detection system is developed for the leakage acoustic waves in the tubing-casing annulus, where one acoustic sensor is installed at the annulus top. Laboratory experimental results show that the depth of downhole leakage can be effectively located by using the proposed localization model. The localization errors are kept at a very low level, and are mainly generated from extracting the characteristic time and calculating annular acoustic velocity. A case study focusing on an offshore gas well is presented to illustrate the feasibility of the proposed method, and to demonstrate that the proposed model can locate the liquid level and leakage points under field conditions. The test can be performed without interrupting the production of gas wells.Energies 2018, 11, 3454 2 of 21 by each sensor. The instrument does not move in the tubing. The test precision is relatively improved by the distributed sensor array. However, the results greatly rely on the reliability of the instrument and the efficiency of signal processing. The current implementation of logging and distributed sensor arrays requires the instrument to be placed in the tubing, and the well needs to be shut down during testing. This process usually entails large costs and risk. Therefore, detecting tubing leakage without interrupting well production is necessary.Tubing leakage will cause pressure changes in the tubing-casing annulus. Zhu et al. have introduced a calculation model of tubing leak depth based on the pressure balance principle when investigating the prediction model of annulus pressure in the CO 2 injection well [11]. Wu et al. further studied this principle and extended it to production gas wells [12,13]. The Bayesian inference is introduced to handle the uncertainties in leakage location forecasting that are caused by variations in reservoir conditions and measurement errors. Meanwhile, an annulus pressure monitoring system is developed to assist diagnosis. This method is theoretically feasible, and does not affect the well production. However, the accuracy of results greatly relies on the wellbore fluid calculation and production status. The locating process needs the production and annulus pressure to be kept stable. This method also requires accurate liquid level information in the annulus, and is not suitable for a well that leaks at an excessive inclination or horizontal sections. Zhang et al. presented a method based on the application of a He tracer [14]. The tracers are injected from the annulus and detected at the choke. The leak depth is calculated by using the flowing tim...