Sequence stratigraphy of clastic and carbonate successions: applications for exploration and production of natural resources

• Autor(a) principal: Magalhães,Antonio Jorge Campos
• Data de Publicação: 2021
• Outros Autores: Fragoso,Daniel Galvão Carnier, Gabaglia,Guilherme Pederneiras Raja, Terra,Gerson Jose Salamoni, Melo,Anderson Henrique de, Andrade,Peryclys Raynyere de Oliveira, Guadagnin,Felipe, Lima-Filho,Francisco Pinheiro
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Journal of Geology
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-48892021000400800
• topic: sequence stratigraphy; natural resource exploration; natural resource production; clastic succession; carbonate succession

Abstract Sequence stratigraphy is a method that unravels the evolution of sedimentation through time and space within sedimentary basins. Nowadays, the exploration and production of natural resources generated by or related to sedimentary processes depend on constructing a chronostratigraphic framework to identify sequences of distinct hierarchies. In clastic and carbonate successions, exploratory studies focus on higher-rank sequences to evaluate the potential of natural resources and to make discoveries. Conversely, lower-rank (i.e. high-frequency) sequences characterize and highlight the spatial and temporal occurrence of natural resource deposits and heterogeneities, necessary for optimizing production. For instance, high-resolution sequence stratigraphic surfaces may indicate the location of placer deposits or coal seams. In the petroleum industry, high-resolution sequence stratigraphy is applied in reservoir zonation and characterization, which are the stratigraphic essence of 3D geological and fluid flow models. Thus, this methodology can guide reservoir management, forecast and optimize production, and increase the ultimate recovery factor. Recent technological innovations such as virtual outcrop models and Ground Penetration Radar have promoted a significant advance in the visualization of surfaces and stacking patterns, making stratigraphic analysis more accurate and efficient than the traditional use of analogs.