Pipeline leaks are of major concern to natural gas industry. They can result in loss of revenue, potential danger to public, and environmental damage. To ensure pipeline safety and reliability, a ground surveillance program to detect leaks is conducted on annual basis. Considering the number of miles of natural gas pipeline, this method is time consuming and expensive. There has been interest in developing other methods for rapid survey of natural gas pipelines. The visual aerial surveys, which rely on the identification of dead vegetation to detect a leak source, have a very limited application. The use of infrared technology to detect a leak based on thermal differences between the leaked pipeline gas and surrounding area has not been developed to the point to be reliable. An effective aerial pipeline leak detection system has been developed recently. The system utilizes an aircraft, which is equipped with flame ionization hydrocarbon detector. The hydrocarbon detector can analyze the samples taken during the flight over the pipeline right-of-way. Presence of natural gas anomalies, that are larger than natural gas background levels, represent a potential leak source. The accuracy and reliability of the aerial surveys however remains questionable. This paper reports the results of the both modeling studies and field tests conducted to evaluate the accuracy and reliability of the aerial surveys.

Buoyant plume rise and dispersion has been studied extensively because it is the primary mechanism for dispersing stack gases to the environment. A jet plume model that predicts the trajectory and dilution of vertically oriented gas jet was considered for this study. The model was then modified to develop user-friendly (Windows-based) input and output interfaces. The plume rise model was then utilized for sensitivity analysis in order to design a field test. The modeling results were utilized to determine the optimum flight plan. A pipeline leak was simulated by release of the natural gas during the field test. The model predictions were compared to the measured gas concentration to evaluate the predictability of the model. The measured gas concentrations were generally found to be in agreement with the predicted values. The results indicated that model can be used for the design of the flight plan and the analysis of the field data.

You can access this article if you purchase or spend a download.