Determination and analysis of leak estimation parameters in two-phase flow pipelines using OLGA multiphase software

Abstract

Pipeline leakage incidents have led to serious environmental concerns, prompting the development of various methods to detect leakage in pipelines. Hence, there is a justified need for early leakage detection as well as leakage prediction system. Many of the leak detection techniques are based on computational intelligence techniques such as artificial neural networks, support vector machine, and fuzzy systems. This paper focuses on determining leak detection parameters such as mass flow rate, temperature, and pressure with and without a leak in pipelines evaluated using OLGA multiphase software. An OLGA-based computerized model is used in leak simulation for analyzing inlet and outlet parameters such as mass flow rate, temperature, and pressure over the flow inside the pipeline. The leak sizes were varied from 0% to 50 % leak opening and the inlet and outlet parameters were measured and studied. The pressure and mass flow rates are observed to decrease with increasing leak size, while temperature decreases with leak size until 25 % and later increases. Mass flow rate is observed to be the most important parameter in detecting a leak and localizing it. The maximum percentage of variation in mass flow rate was observed to be 33.6 % for 50 % leak openings, for a single leak, and 32.4 % for multi-leak scenario.