Revealing the Strike-slip Fault Planes in the Persian Gulf

Semi-automatic approach was applied for revealing strike-slip fault planes within Mid-Miocene Mishan Formation in eastern part of Persian Gulf. The fault planes revealing provides with neural network technology that analyzes data with integrations of selected attributes. The neural network was used for transforming the selected attributes into a new volume attribute, which attributes extracted at a set of sample locations. The fault volume reveals clearly showing a number of continuous fault planes, as concluded from low homogeneous responses joined to generate the fault planes. The more important attribute of the fault volume that seem to give the highest contributions of the faults contrasting is trace to trace similarity, which is low similar response along the fault planes. The fault volume is in general faulting more continuity than the similarity attribute. The inhomogeneous response of the fault planes change stronger along the fault volume than along dip-steered similarity attributes. Comparing the similarity attributes for the fault volume, the contrast at the fault planes is even better than similarities which have a noisier background level. The obtained results show that this faults with small displacements, is normal fault zones and strike-slip movement with NE-SW trend.