Fault detection using neural network

Elistia Liza Namigo
2017 Journal of Physics Theories and Applications  
<p class="Abstract">Fault detection technique using neural networks have been successfully applied to a seismic data volume. This technique is basically creating a volume that highlights faults by combining the information from several fault indicators attributes (i.e. similarity, curvature and energy) into fault occurrence probability. This is performed by training a neural network on two sets of attributes extracted at sample locations picked manually - one set represents the fault class and
more » ... he other represents the non-fault class. The next step is to apply the trained artificial neural network on the seismic data. Result indicates that faults are more highlighted and have better continuity since the surrounding noise are mostly suppressed.</p>
doi:10.20961/jphystheor-appl.v1i1.4718 fatcat:g3rwolj6nzbxnb54qpcihydy44