Banca de DEFESA: SAMUEL DA SILVA OLIVEIRA

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : SAMUEL DA SILVA OLIVEIRA
DATE: 13/02/2023
TIME: 15:00
LOCAL: Online
TITLE:

Parallelized Superiorization Method for History Matching Problems Using Seismic Priors and Smoothness in Parts

KEY WORDS:

History Matching, Superiorization Method, Parallelism, Seismics,
Smoothness.

PAGES: 81
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SPECIALTY: Processamento Gráfico (Graphics)
SUMMARY:

History Matching is a very important process used in managing oil and gas
production since it aims to adjust a reservoir model until it closely reproduces
the past behavior of a actual reservoir, so it can be used to predict future
production. This work proposes to use an iterative method with constraints
to optimize a reservoir production model, called superiorization to solve this
problem. The superiorization method is an approach that uses two optimization
criteria, the first being the production result and the second being the smooth-
ness by parts of the reservoir, where this second criterion seeks to optimize its
function without negatively affecting the optimization of the first criterion. A
genetic algorithm was chosen as a comparative approach to the tabu search
algorithm using the superiorization method, given that this technique is widely
used in the literature for solving history matching, in addition to being tested
with the tabu search algorithm, it has the superiorization approach. Both
techniques are iterative and use population-based approaches. As the prob-
lem addressed is an inverse problem often severely underdetermined, several

possible solutions may exist for its resolution. Due to this, we also propose
the use of seismic data from the reservoirs, through these data, to verify the
faults present in the reservoir so that we can use values of smoothness by
parts to then reduce the number of possible results through a regularization
relevant to the second optimization criterion of the superior version of the tabu
search algorithm. Another critical factor in the history matching process is the
simulation time, which is generally high. Thus, we also propose investigating
parallelism in the solution using the CPU. The experiments are carried out
in a 3D reservoir model to find correspondence for the gas, oil, and water
yield values. The results obtained during the research show that the parallel
approach decreases the execution time by up to more than 70%. As for the
result’s precision, the genetic approach obtained better values. However, the
tabu search and the superiorization method produced very similar values but
more stable results.

COMMITTEE MEMBERS:
Presidente - 2177445 - BRUNO MOTTA DE CARVALHO
Interno - 1694485 - MARCIO EDUARDO KREUTZ
Interna - 2859606 - SILVIA MARIA DINIZ MONTEIRO MAIA
Externo à Instituição - EDGAR GARDUNO ANGELES - UNAM
Externo à Instituição - ISLAME FELIPE DA COSTA FERNANDES - UFBA