In the past decades, machine learning algorithms have been developed for accelerating the seismic interpretation process. For this purpose, benchmark availability for algorithm improvement in computational geophysics is imperative. However, in geosciences, the supply of open benchmark datasets is very limited. The purpose of our study was to evaluate a CNN algorithm response in comparison to an OpendTect tool for seismic horizon interpolation, and besides, offer a benchmark dataset for further algorithms evaluations.

Presentation Date: Tuesday, October 13, 2020

Session Start Time: 1:50 PM

Presentation Time: 2:15 PM

Location: 362C

Presentation Type: Oral

Keywords:
artificial intelligence, benchmark dataset, zealand, reservoir characterization, upstream oil & gas, seismic interpretation, neural network, new zealand, semi-automatic seismic interpretation, amplitude
Subjects:
Reservoir Characterization, Information Management and Systems, Seismic processing and interpretation, Artificial intelligence
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2020. Society of Exploration Geophysicists
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