Reducing Gas Well Uncertainties by Predicting Liquid Loading Using Artificial Neural Network
Publish place: First National Iranian Petroleum Conference
Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
NIPC01_114
تاریخ نمایه سازی: 28 فروردین 1393
Abstract:
Liquid loading is an important issue caused by fluid accumulation in the tubing of gas wells when the gas kinetic energy is not sufficient to carry liquid slugs to the surface. This problem has influences onproduction capacity of gas wells; For example, in high-pressure wells, it disturbs well production byslugging and churning or in low-pressure wells, it may kill the well. Moreover, in reservoir engineering, the liquid loading may cause uncertainties in well test data. Despite the fact that there aresolutions for liquid loading such as gas lift or pumping, preventing it eliminates load up costs. Thebest way is to continue gas production at a flow rate above a critical value to prevent liquid loading. In this paper, we present a new method to estimate the critical flow rate as accurate as possible to predict the occurrence of loading in a gas well. In our approach, we use artificial neural network as afast, easy to learn, and reliable method to provide the results for production engineers. The developed network is trained and tested with available data from different gas wells. Our results are in good agreement with the field data and show less than 2.5% error in liquid loading prediction
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Authors
Reza mohebbi
Department of Petroleum engineering, Faculty of Engineering, Shahid Bahonar University of Kerman
Seyed Mohammad Mahdi Hashemi Karooei
Allameh Tabatabaii University of Tehran
Peyman Pourafshary
University of Tehran
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