Título: | HYBRID OPTIMIZATION SYSTEM FOR THE CONTROL STRATEGIES OF INTELLIGENT WELLS UNDER UNCERTAINTIES | ||||||||||||||||||||||||||||||||||||||||
Autor: |
LUCIANA FALETTI ALMEIDA |
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Colaborador(es): |
MARLEY MARIA BERNARDES REBUZZI VELLASCO - Orientador MARCO AURELIO CAVALCANTI PACHECO - Orientador |
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Catalogação: | 23/NOV/2007 | Língua(s): | PORTUGUESE - BRAZIL |
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Tipo: | TEXT | Subtipo: |
THESIS
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Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=10863&idi=1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=10863&idi=2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.10863 | ||||||||||||||||||||||||||||||||||||||||
Resumo: | |||||||||||||||||||||||||||||||||||||||||
The reservoir management is an important task that aims at
the
optimization of oil reservoir exploitation. To support this
challenging mission, the
oil and gas industry has been developing new technologies
such as intelligent
wells. The purpose of these wells is to reduce costs of the
most common
restoring operations by control of their actuators. Thus,
this work deals with
intelligent fields development and presents a decision
support system able to
optimize, by using evolutionary algorithms, the intelligent
wells technology control
process considering geological and technical uncertainties.
In addition, the
system gives support for the decision of rather to use or
not intelligent wells,
given a reservoir ready to be explored or to receive
expansion investments. The
control of Intelligent Wells Technology (IWT), as applied
in this study, refers to
the opening and closing operations of valves in these types
of wells. An
optimization based on genetic algorithms is used to produce
a pro-active control
strategy, that is, one that anticipates the actions to be
taken in present time in
order to achieve better results in the future. Such a
strategy proposes a valve
configuration that will be able to: delay the water cut on
producer wells, advance
the oil production or benefit the oil recuperation. As a
result, the obtained
configuration leads to a maximization of the NPV (Net
Present Value). The usage
of control strategies that aim to benefit completion
identifies the oil field as
intelligent. Other works also deal with valve control
optimization problems in
intelligent wells. However, they use classical optimization
methods; these
methods limit the number of valves or optimize strategies
without considering
time. The evolutionary model, based on genetic algorithm,
applied in this study,
can formulate a control strategy for all valves in a
certain production
configuration, for any desired time interval, according to
the economical criteria of
NPV maximization. In order to support the decision making
for the use or not of
intelligent wells, technical and geological uncertainties
are considered. The
proposed model was evaluated in three oil reservoirs. The
first one is a synthetic
reservoir, simple and not real; the other two are more
complex with close to real characteristics. The results
obtained indicate that the proposed model allows
good control strategies that increase the NPV. The main
contribution of this work
is the conception and implementation of a system based on
intelligent techniques
that is able to support the development and management of
intelligent oil
reservoirs considering uncertainties.
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