Abstract
The Parzen probabilistic network which is based on the Bayes theorem was developed using three wells in gas reservoir F3 to estimate porosity distribution. It used seismic attributes of similarity, instantaneous amplitude and energy rather than the conventional post-stack volume. The conditional probabilities involved in the Parzen probabilistic network should be adjusted based on an appropriate smoothing parameter which was calculated by cross validation approach. When the testing dataset was used, total accuracy was obtained as 0.7578 for the developed algorithm. The obtained results indicated that the adjusted Parzen probabilistic network characterized the discontinuities of F3 reservoir as fault structures and gas chimney and also estimated the porosity distribution.
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 callDisclaimer: 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.
