Machine learning-based seismic spectral attribute analysis to delineate a tight-sand reservoir in the Sulige gas field of central Ordos Basin, western China

Volume: 113, Pages: 104136 - 104136
Published: Mar 1, 2020
Abstract
We propose a machine learning-based seismic spectral attribute (SSA) analysis to delineate the thickness of a tight-sand reservoir in the Sulige gas field of central Ordos Basin, western China. In our workflow, we first implement the seismic spectral decomposition by using the continuous wavelet transform (CWT) with the generalized Morse wavelets (GMWs). The best parameters of generalized Morse wavelets (GMWs) are obtained by using a geological...
Paper Details
Title
Machine learning-based seismic spectral attribute analysis to delineate a tight-sand reservoir in the Sulige gas field of central Ordos Basin, western China
Published Date
Mar 1, 2020
Volume
113
Pages
104136 - 104136
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.