Abstract

Stratigraphic hydrocarbon traps commonly result in very subtle changes in seismic reflection waveforms, making their detection difficult using ordinary processing techniques. This paper describes the implementation of a Bayes classifier using a multimodal estimate of the conditional class probability density function. Also, a relaxation labeling procedure is presented which is used to reclassify the initial Bayes results using a priori contextual information extracted from the training data. Processing synthetic data with 20% additive noise resulted in 84.8% correct using only 3 features.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.