In the last two decades, spectral decomposition as a dynamic analysis method for seismic and prediction of effective thicknesses has been firmly established in the geological ex-ploration workflow. The reason for this is high efficiency in forecasting in conditions of high lateral and vertical variabil-ity of reservoir properties. However, the existing methods for interpreting the results of spectral decomposition have disadvantages. In our study, we tried to solve these disad-vantages and created a new technique for interpreting spec-tral decomposition, which was called “clustering of spectral curves”.

Presentation Date: Tuesday, October 13, 2020

Session Start Time: 8:30 AM

Presentation Time: 8:55 AM

Location: 362D

Presentation Type: Oral

Keywords:
reservoir characterization, clustering algorithm, interpretation summary, seg international exposition, machine learning, frequency, cluster center, exploration geophysicist 10, upstream oil & gas, disadvantage
Subjects:
Reservoir Characterization, Seismic processing and interpretation
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2020. Society of Exploration Geophysicists
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