Early Recognition of Liquid Loading in Gas Wells Using Neural Networks
Research output: Research › Master's Thesis
During the mature stage in the lifetime of a gas well, production volumes decrease along with its bottom-hole flowing pressure which may lead to the “loading of liquids” inside the wellbore. The continuous buildup of these liquids can cause significant problems to the gas production and can also lead to the killing of the well. Artificial intelligence is increasingly implemented to deal with the challenges faced in the oil and gas industry. Neural networks are suitable to identify the trends in the production data and to recognize the patterns that describe this phenomenon early on and the problem easier to resolve.
|Award date||15 Dec 2017|
|State||Published - 2017|