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Analysis of porosity, stratigraphy, and structural delineation of a Brazilian carbonate field by machine learning techniques; a case study

Michelle Chaves Kuroda, Alexandre Campane Vidal and Joao Paulo Papa
Analysis of porosity, stratigraphy, and structural delineation of a Brazilian carbonate field by machine learning techniques; a case study
Interpretation (Tulsa) (August 2016) 4 (3): T347-T358

Abstract

The upscaling of well logs has many challenges, especially for carbonate rocks. Primary among them is the suitable choice of seismic attributes to be integrated with well information, whose random combination can produce artifacts of rock properties. To solve this problem, we have developed an alternative hybrid method to estimate well-log data from seismic attributes, associating the seismic attributes choices with the genetic algorithm and artificial neural network multilayer perceptron ability to predict neutron porosity. Thirty-seven seismic attributes were extracted along 12 wellbores from an Albian offshore carbonate reservoir of the Campos Basin. From these attributes, three were selected: 3D mix, structure-oriented median-filtered amplitude, and acoustic impedance. From this set of seismic data, we used the first two attributes to estimate neutron porosity in the reservoir seismic area. As a result, we obtained a 3D map of well-log information at the seismic scale. In the 3D map, it is possible to identify the main structural and architectural elements of the field. These results corroborate the interpretation of bioconstruction, lagoons, and carbonate shoals, and the delimitation of a tidal channel at the top of a reservior, using neutron porosity.


ISSN: 2324-8858
EISSN: 2324-8866
Serial Title: Interpretation (Tulsa)
Serial Volume: 4
Serial Issue: 3
Title: Analysis of porosity, stratigraphy, and structural delineation of a Brazilian carbonate field by machine learning techniques; a case study
Affiliation: University of Campinas, Institute of Geosciences, Sao Paulo, Brazil
Pages: T347-T358
Published: 201608
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 36
Accession Number: 2017-002801
Categories: Economic geology, geology of energy sourcesApplied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. sects., 2 tables, sketch maps
S34°00'00" - N05°15'00", W74°00'00" - W34°00'00"
Secondary Affiliation: Sao Paulo State University, BRA, Brazil
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2017, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 201703
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