1. Constructing high-resolution stratigraphic frameworks by the application of signal analysis techniques: Example of Balbuena IV sequence, Yacoraite formation, Salta Basin.
- Author
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Oliveira Santos, José Arthur, Uhlein, Alexandre, Dantas, Márcio, de Morais Coutinho, Gabriel, Spier, Thomás Jung, Masse Vieira, Kaio Henrique, Trindade Prado, Alan Cabral, Macharet, Douglas, Uhlein, Gabriel Jubé, Novo, Tiago, Reis, Humberto, Farias, Felipe Alves, Freire, Ednilson Bento, and Carnier Fragoso, Daniel Galvão
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PYTHON programming language , *SEQUENCE stratigraphy , *WAVELET transforms , *FLUID flow , *MARKOV processes - Abstract
One of the most essential and valuable applications of high-resolution sequence stratigraphy is reservoir zonation and characterization. Establishing a hierarchical chronostratigraphic framework comprising sequences at multiple scales is crucial to identify main reservoir heterogeneities that compartmentalize the fluid flow in the subsurface. In this context, this paper proposes a workflow that integrates different signal analysis techniques to identify sequences of multiple hierarchies from a series of stratigraphic data. The Continuous Wavelet Transform (CWT), Detrend Error Log (DTEL), and Integrated Detrend Error Log (INDTEL) techniques are utilized to process gamma-ray data obtained from outcrops of the Yacoraite Formation, which are conventionally employed as analogs for reservoir characterization. Our results suggest that CWT fits better with higher frequency cycles, while INDTEL shows a good fit with medium frequency cycles. In addition to these techniques, Hidden Markov Models were also applied, predicting T-R cycles as hidden states from the facies transition matrix and possible occurrence of missed beats. All these methods were scripted in the Python programming language, enabling the generation of fast and interactive outputs. This approach brings parameters that can guide the construction of stratigraphic models by automated processes. • Multifrequency transgressive-regressive cycles were obtained from spectral decompositional techniques on Gamma-Ray proxies. • High-Frequency output curve from Continuous Wavelet Transform has direct relationship with high-frequency transgressive-regressive cycles. • INDTEL method is a powerful tool to detect hidden trends and well correlation. • Hidden-Markov Models show high-frequency transgressive-regressive cycles as hidden states from facies transition • The integrated aplication of the methods proves to be a promising tool to help detect missed-beats. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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