Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/64133
Title: Geological Interpretation by Peak Spectral Decomposition Envelope Attribute
Authors: Gritsadapong Leaungvongpaisan
Pisanu Wongpornchai
Siriporn Chaisri
Authors: Gritsadapong Leaungvongpaisan
Pisanu Wongpornchai
Siriporn Chaisri
Issue Date: 2018
Publisher: Science Faculty of Chiang Mai University
Abstract: Spectral decomposition has set a mainstream for seismic interpretation workflow over past several years. It is used for capturing the stratal thickness using Red Green Blue (RGB) blending with three defined spectral decomposition frequencies. Each three different frequencies is a representative of specific thickness, where other thicknesses remain untouched in RGB blending. A new method of Peak Spectral Decomposition Envelope (PSDE) attribute takes all frequencies into account to resolve for all thicknesses. The PSDE attribute eliminates the conventional frequency selection process for spectral decomposition. Synthetic seismic wedge models and 3D seismic datasets from different geological settings were tested with PSDE attribute. The apparent thickness and true thickness were analyzed for the resolution analysis in the synthetic models. The PSDE attribute offers a finer seismic resolution over the synthetic seismic wedge model. The finest resolution is 4.5 ms in a time domain; however, the actual resolution in a depth domain is related to the frequency content and time-depth conversion by velocity data. The shifted attributes and RGB blending help the PSDE attribute to enhance geological features, such as channels, fans and faults in seismic datasets. This method could be universally applied to any seismic survey for geological identifications, as the improved geological understanding could have a significant impact on the reserve calculation and the economic analysis for oil and gas business.
URI: http://it.science.cmu.ac.th/ejournal/dl.php?journal_id=9160
http://cmuir.cmu.ac.th/jspui/handle/6653943832/64133
ISSN: 0125-2526
Appears in Collections:CMUL: Journal Articles

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