A SIMULATION TOOL FOR PREDICTING AN OPTIMUM PIGGING SCHEDULE IN A GAS TRANSMISSION PIPELINE

摘要

The presence of condensates is a problem that often arises in gas transmission pipelines. This is not the only problem that influences the industry production process, but it is one that ensures that pigging as a process to clean up condensates in gas pipelines is one of high cost to the company. In this paper, a model has been developed to simulate and to identify the presence of condensate as well as to predict the optimum pigging schedule. The model uses three methods; Flow Index Ratio, Flow Efficiency Analysis and a statistical method, known as the Sequential Probability Ratio Test (SPRT). The presence of condensate can be detected by observing changes in the pressure drop along the pipeline and its flow efficiency. A case study using real field data is simulated to represent the implementation of the method used to identify the presence of condensate and to predict the optimum pigging schedule in gas transmission pipelines. Validation of pressure drop and gas flow rate along with pigging data in the field shows that the method may be considered as a viable alternative approach to identify the presence of condensate in gas transmission pipelines. In addition, the method may also be considered as a means to predict the optimum pigging schedule.