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CHARACTERIZATION OF HETEROGENEITIES AND MODELING OF RESERVOIR ANALOGUES IN FLUVIAL AND EOLIAN DEPOSITS

Abstract

The study of hydrocarbon reservoir analogues in outcrops is applied, in the oil industry, as a powerful tool to acquire information in sub-seismic scale, enabling the construction of detailed reservoir models. The method is used to study sedimentary body dimensions and geometries and their spatial relationships, as well as sedimentary structures and bounding surfaces that can not be imaged in subsurface reservoirs due to the limitations in vertical and horizontal resolution of seismic data and well data, respectively. In this way, data from analogue outcrops bring valuable information on the heterogeneity distribution, which varies greatly in the various lithofacies and archiectural elements in a given reservoir. Therefore, analogue outcrop data is a key information to be inputed in reservoir modeling softwares, enabling the planing of explaration and development well in different stages of the exploration of a given oil field. In this context, recent studies by our research group in fluvial successions of the São Sebastião and Marizal formations (Eocretáceo, Tucano Basin), resulted in the recognition of a sistematic distinction between fluvial bar-top facies associations and the other channel belt associations. This distinction can potentially be used as a predictive tool of petrophysical properties in subsurface reservoirs, with major implications for reservoir modeling and production projects. In this context, this proposal focus on studying fluvio-eolian outcrop reservoir analogues from sedimentary basins of varied age and tectonic context. The aim is to characterize sedimentary and petrophycal heterogeneities in unit of similar sedimentary environment, and also to build predictive models for sedimentary and petrophysical properties and their relations with architectural elements of these successions. In order to do that, specific studies in fluvio-eolian successions deposited in cratonic sags, rifts and post-rift settings will be undertaken, aiming at the establishment of predictive tools for the sedimentary and petrophysical characteristics in these successions deposited in similar environments but different basin types. (AU)

Scientific publications (5)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
JANIKIAN, LILIANE; DE ALMEIDA, RENATO PAES; GALEAZZI, CRISTIANO PADALINO; TAMURA, LARISSA NATSUMI; ARDITO, JULIO CESAR; CARRARI CHAMANI, MARLEY ANTONIO. Variability of fluvial architecture in a poorly vegetated Earth: Silurian sheet-braided and meandering ancestor river deposits recorded in northeastern Brazil. TERRA NOVA, v. 32, n. 3 DEC 2019. Web of Science Citations: 0.
TAMURA, LARISSA N.; ALMEIDA, RENATO P.; GALEAZZI, CRISTIANO P.; FREITAS, BERNARDO T.; IANNIRUBERTO, MARCO; PRADO, ARIEL H. Upper-bar deposits in large Amazon rivers: Occurrence, morphology and internal structure. SEDIMENTARY GEOLOGY, v. 387, p. 1-17, JUN 1 2019. Web of Science Citations: 0.
DO PRADO, ARIEL HENRIQUE; DE ALMEIDA, RENATO PAES; TAMURA, LARISSA NATSUMI; GALEAZZI, CRISTIANO PADALINO; IANNIRUBERTO, MARCO. Interpretation software applied to the evaluation of shallow seismic data processing routines in fluvial deposits. BRAZILIAN JOURNAL OF GEOLOGY, v. 49, n. 2 2019. Web of Science Citations: 0.
GOMES, JR., CLEBER PERALTA; FOSSEN, HAAKON; DE ALMEIDA, RENATO PAES; SALMONI, BRUNO. Subseismic deformation in the Vaza-Barris Transfer Zone in the Cretaceous Reconcayo-Tucano-Jatoba rift system, NE Brazil. JOURNAL OF STRUCTURAL GEOLOGY, v. 117, p. 81-95, DEC 2018. Web of Science Citations: 1.
FREITAS, BERNARDO T.; ALMEIDA, RENATO P.; CARRERA, SIMONE C.; FIGUEIREDO, FELIPE T.; TURRA, BRUNO B.; VAREJAO, FILIPE G.; ASSINE, MARIO L. Aptian sedimentation in the Reconcavo-Tucano-Jatoba Rift System and its tectonic and paleogeographic significance. Journal of South American Earth Sciences, v. 80, p. 460-481, DEC 2017. Web of Science Citations: 4.

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