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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
DOI: 10.1306/10261818055
Unsupervised
seismic
facies classification applied to a presalt carbonate reservoir, Santos Basin, offshore Brazil
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Danilo Jotta Ariza Ferreira,1 Wagner Moreira Lupinacci,2 Igor de Andrade Neves,3 João Paulo Rodrigues Zambrini,4 André Luiz Ferrari,5 Luiz Antonio Pierantoni Gamboa,6 and Maria Olho Azul7
1Department of Geology and Geophysics, Universidade Federal Fluminense, Brazil; [email protected]
2Department of Geology and Geophysics, Universidade Federal Fluminense, Brazil; [email protected]
3Department of Geology and Geophysics, Universidade Federal Fluminense, Brazil; [email protected]
4Department of Geology and Geophysics, Universidade Federal Fluminense, Brazil; [email protected]
5Department of Geology and Geophysics, Universidade Federal Fluminense, Brazil; [email protected]
6Department of Geology and Geophysics, Universidade Federal Fluminense, Brazil; [email protected]
7Petrogal Brasil; [email protected]
ABSTRACT
Mapping of seismic
and lithological facies is a very complex process, especially in regions with low
seismic
resolution caused by extensive salt layers, even when only an exploratory view of the distribution of the reservoir facies is required. The aim of this study was to apply multi-
attribute
analysis using an unsupervised classification algorithm to map the carbonate facies of an exploratory presalt area located in the Outer high region of the Santos Basin. The interval of interest is the Barra Velha Formation, deposited during the Aptian, which represents an intercalation of travertines, stromatolites, grainstones and spherulitic packstones, mudstones, and authigenic shales, which were deposited under hypersaline lacustrine conditions during the sag phase. A set of
seismic
attributes, calculated from a poststack
seismic
amplitude volume, was used to characterize geological and structural features of the study area. We applied k-means clustering in an approach for unsupervised
seismic
facies classification. Our results show that at least three
seismic
facies can be differentiated, representing associations of buildup lithologies, aggradational or progradational carbonate platforms, and debris facies. We quantitatively evaluated the
seismic
facies against petrophysical properties (porosity and permeability) from available well logs.
Seismic
patterns associated with the lithologies helped identify new exploration targets.
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