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Aplicação de Redes Neurais (NN) com gerador de modelos através de workflow integrado com Full Waveform Inversion (FWI) para predição de alvos para armazenamento geológico de CO2

Authors: Zuniga, Nelson;

Aplicação de Redes Neurais (NN) com gerador de modelos através de workflow integrado com Full Waveform Inversion (FWI) para predição de alvos para armazenamento geológico de CO2

Abstract

O armazenamento geológico de CO2 é incentivado pelo IPCC (Painel Intergovernamental de Mudanças Climáticas) para conter o aumento da temperatura média do planeta em relação à era pré-industrial. Este projeto visa avaliar a viabilidade de implementação da tecnologia de armazenamento de CO2 na região sudeste do Brasil, onde se concentram as principais fontes estacionárias de emissão no país. Será proposto um sistema integrado e automatizado para realizar o imageamento das estruturas alvo por meio da combinação de técnicas de aprendizado de máquinas e Full-Waveform Inversion. A caracterização dos potenciais reservatórios para armazenamento do CO2 será feita usando técnicas de inteligência artificial fara delimitar os horizontes e as posições de estruturas mais complexas, enquanto a caracterização destas geometrias será realizada por meio de técnicas de Full-Waveform Inversion. Esse projeto está vinculado ao Projeto Temático 2020/15230-5, Acordos de Cooperação / BG E&P Brasil (Shell) / BG E&P Brasil (Shell) - CPE - Centro de Pesquisa para Inovação em Gás - Chamada de Propostas (2020), constituindo parte integrante da linha de pesquisa sobre armazenamento geológico de CO2.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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