Soft Computing Approach to Detecting Discontinuities: Seismic Analysis and Beyond

Authors

Solymar Ayala Cortez, The University of Texas at El PasoFollow
Aaron A. Velasco, The University of Texas at El PasoFollow
Vladik Kreinovich, The University of Texas at El PasoFollow

Publication Date

4-2017

Comments

Technical Report: UTEP-CS-17-36a

Published in Proceedings of the IEEE Conference on Systems, Man, and Cybernetics SMC'2017, Banff, Canada, October 5-8, 2017, pp. 363-366.

Abstract

Starting from Newton, the main equations of physics are differential equations -- which implicitly implies that all the corresponding processes are differentiable -- and thus, continuous. However, in practice, we often encounter processes or objects that change abruptly in time or in space. In physics, we have phase transitions when the properties change abruptly. In geosciences, we have sharp boundaries between different layers and discontinuing representing faults. In many such situations, it is important to detect these discontinuities. In some cases, we know the equations, but in many other cases, we do not know the equations, we only know that the corresponding process is discontinuous. In this paper, we show that by applying the soft computing techniques to translate this imprecise knowledge into a precise strategy, we can get an efficient algorithm for detecting discontinuities; its efficiency is shown on the example of detecting a fault based on the seismic signals.