Fuzzy C-means Clustering for 3D Seismic Parameters Processing

  •  Fuqun Zhao    
  •  Liang Le    


3D seismic parameters can reflect the features of petroleum reservoir from different profiles. By analizing the
3D seismic parameters, we can assess the parameters of the reservoir characterization, such as deposition,
structure and growth history, fluid saturation and so on. The traditional clustering methods can’t capture the
degree of similarity between reservoir parameters very well, so we introduced in this paper the application of
fuzzy C-means (FCM) clustering for the processing of 3D seismic parameters. It begins with the analizing the
relationship between 3D seismic parameters and reservoir characterization parameters, and then we process the
3D seismic parameters with FCM and assess the parameters of reservoir characterization. The testing results
show that FCM can classify the 3D parameters more accurately and provide a good evidence for the research
of petroleum reservoir.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1916-9779
  • ISSN(Online): 1916-9787
  • Started: 2009
  • Frequency: semiannual

Journal Metrics

(The data was calculated based on Google Scholar Citations)

Google-based Impact Factor (2018): 11.90

h-index (January 2018): 17

i10-index (January 2018): 36

h5-index (January 2018): 13

h5-median(January 2018): 15