Connectionist expert system for seismic interpretations

Kou-Yuan Huang*, H. Z. Yang, C. M. Lin

*Corresponding author for this work

Research output: Contribution to conferencePaper

Abstract

This paper presents a connectionist expert system designed to assist the seicmic interpreter in oil or gas exploration. The system is a learning-based model, not an analytic one which conventional rule-based systems usually belong to. We use multilayered neural network and the back-propagation algorithm as the learning strategy. While learning, a prototype input list of seismic phenomena is fed into the network as input and with an expert's decision together as its desired output, then weights get adjust. After repeated cycles, the knowledge will be distributed all over the network so taht a set of weighted interconnections constitutes an implicit decision criteria. When learning completes, user presents a list of seismic phenomena to this system to get a decision about oil or gas existence.

Original languageEnglish
Pages310-312
Number of pages3
StatePublished - 1 Jan 1990
Event1990 Society of Exploration Geophysicists Annual Meeting - San Francisco, United States
Duration: 23 Sep 199027 Sep 1990

Conference

Conference1990 Society of Exploration Geophysicists Annual Meeting
CountryUnited States
CitySan Francisco
Period23/09/9027/09/90

Fingerprint Dive into the research topics of 'Connectionist expert system for seismic interpretations'. Together they form a unique fingerprint.

  • Cite this

    Huang, K-Y., Yang, H. Z., & Lin, C. M. (1990). Connectionist expert system for seismic interpretations. 310-312. Paper presented at 1990 Society of Exploration Geophysicists Annual Meeting, San Francisco, United States.