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.

In coal seam gas (CSG) wells, water is periodically removed from the wellbore in order to keep the bottom-hole flowing pressure at low levels, facilitating the desorption of methane gas from the coal bed. In order to calculate gas flow rate and further optimize well performance, it is necessary to accurately monitor the liquid level in real-time. This paper presents a novel method based on autocorrelation function (ACF) analysis for determining the liquid level in CSG wells under intense noise conditions. The method involves the calculation of the acoustic travel time in the annulus and processing the autocorrelation signal in order to extract the weak echo under high background noise. In contrast to previous works, the non-linear dependence of the acoustic velocity on temperature and pressure is taken into account. To locate the liquid level of a coal seam gas well the travel time is computed iteratively with the non-linear velocity model. Afterwards, the proposed method is validated using experimental laboratory investigations that have been developed for liquid level detection under two scenarios, representing the combination of low pressure, weak signal, and intense noise generated by gas flowing and leakage. By adopting an evaluation indicator called Crest Factor, the results have shown the superiority of the ACF-based method compared to Fourier filtering (FFT). In the two scenarios, the maximal measurement error from the proposed method was 0.34% and 0.50%, respectively. The latent periodic characteristic of the reflected signal can be extracted by the ACF-based method even when the noise is larger than 1.42 Pa, which is impossible for FFT-based de-noising. A case study focused on a specific CSG well is presented to illustrate the feasibility of the proposed approach, and also to demonstrate that signal processing with autocorrelation analysis can improve the sensitivity of the detection system.