Early Recognition of Liquid Loading in Gas Wells Using Neural Networks

Publikationen: Thesis / Studienabschlussarbeiten und HabilitationsschriftenMasterarbeit

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Early Recognition of Liquid Loading in Gas Wells Using Neural Networks. / Ouarda, Mohamed Amine.
2017.

Publikationen: Thesis / Studienabschlussarbeiten und HabilitationsschriftenMasterarbeit

Harvard

Ouarda, MA 2017, 'Early Recognition of Liquid Loading in Gas Wells Using Neural Networks', Dipl.-Ing., Montanuniversität Leoben (000).

APA

Ouarda, M. A. (2017). Early Recognition of Liquid Loading in Gas Wells Using Neural Networks. [Masterarbeit, Montanuniversität Leoben (000)].

Bibtex - Download

@mastersthesis{05bd4752930a4bd8b6f44eaed8fe76d9,
title = "Early Recognition of Liquid Loading in Gas Wells Using Neural Networks",
abstract = "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.",
keywords = "Neural Networks, Liquid Loading, Gas, Liquid Loading, Neural Networks, Gas",
author = "Ouarda, {Mohamed Amine}",
note = "embargoed until 23-08-2022",
year = "2017",
language = "English",
school = "Montanuniversitaet Leoben (000)",

}

RIS (suitable for import to EndNote) - Download

TY - THES

T1 - Early Recognition of Liquid Loading in Gas Wells Using Neural Networks

AU - Ouarda, Mohamed Amine

N1 - embargoed until 23-08-2022

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Neural Networks

KW - Liquid Loading

KW - Gas

KW - Liquid Loading

KW - Neural Networks

KW - Gas

M3 - Master's Thesis

ER -