1887

Abstract

Summary

Clustering and pattern recognition within the seismic data, lead to generating seismic facies maps which they are associated with changes in the geological characteristic. Seismic facies analysis would be performed using the supervised and unsupervised methods, each of them has its own advantages and disadvantages. Generally, seismic data analysis has always a degree of imprecise with itself, due to the uncertainty nature of seismic data. In this paper, it will be presented which the choice of suitable attribute and interactive use of the supervised and unsupervised methods, which have a high power to deal with the imprecision property of seismic data, can provide better results for facies analysis. Afterwards, we use some data mining methods to choose the proper seismic attribute. Besides, well log clustering data and evaluation cluster indices help to obtain the number of seismic facies for analysis. With appropriate seismic attributes and predetermined facies number, in this paper, it will be shown that the seismic facies maps would be produced using fuzzy and ANFIS methods. Results show the approach of the paper has the ability to deal with seismic data uncertainty and find channel patterns in the seismic facies map.

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/content/papers/10.3997/2214-4609.201700917
2017-06-12
2024-03-29
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