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Pitfalls and implementation of data conditioning, attribute analysis, and self-organizing maps to 2D data; application to the Exmouth Plateau, north Carnarvon Basin, Australia

Thang N. Ha, Kurt J. Marfurt, Bradley C. Wallet and Bryce Hutchinson
Pitfalls and implementation of data conditioning, attribute analysis, and self-organizing maps to 2D data; application to the Exmouth Plateau, north Carnarvon Basin, Australia
Interpretation (Tulsa) (August 2019) 7 (3): SG23-SG42

Abstract

Recent developments in attribute analysis and machine learning have significantly enhanced interpretation workflows of 3D seismic surveys. Nevertheless, even in 2018, many sedimentary basins are only covered by grids of 2D seismic lines. These 2D surveys are suitable for regional feature mapping and often identify targets in areas not covered by 3D surveys. With continuing pressure to cut costs in the hydrocarbon industry, it is crucial to extract as much information as possible from these 2D surveys. Unfortunately, much if not most modern interpretation software packages are designed to work exclusively with 3D data. To determine if we can apply 3D volumetric interpretation workflows to grids of 2D seismic lines, we have applied data conditioning, attribute analysis, and a machine-learning technique called self-organizing maps to the 2D data acquired over the Exmouth Plateau, North Carnarvon Basin, Australia. We find that these workflows allow us to significantly improve image quality, interpret regional geologic features, identify local anomalies, and perform seismic facies analysis. However, these workflows are not without pitfalls. We need to be careful in choosing the order of filters in the data conditioning workflow and be aware of reflector misties at line intersections. Vector data, such as reflector convergence, need to be extracted and then mapped component-by-component before combining the results. We are also unable to perform attribute extraction along a surface or geobody extraction for 2D data in our commercial interpretation software package. To address this issue, we devise a point-by-point attribute extraction workaround to overcome the incompatibility between 3D interpretation workflow and 2D data.


ISSN: 2324-8858
EISSN: 2324-8866
Serial Title: Interpretation (Tulsa)
Serial Volume: 7
Serial Issue: 3
Title: Pitfalls and implementation of data conditioning, attribute analysis, and self-organizing maps to 2D data; application to the Exmouth Plateau, north Carnarvon Basin, Australia
Affiliation: University of Oklahoma, Norman, OK, United States
Pages: SG23-SG42
Published: 201908
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 44
Accession Number: 2020-011109
Categories: Economic geology, geology of energy sourcesApplied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Annotation: Part of a special section on Working with 2D seismic data, edited by Herron, D.; includes appendices
Illustration Description: illus.
S27°00'00" - S21°00'00", E114°30'00" - E116°00'00"
Secondary Affiliation: Aramco Services Company, USA, United StatesNoble Energy, USA, United States
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2020, American Geosciences Institute.
Update Code: 202008
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