作者: A Naseri , J Mohammadzadeh , M , H Tabatabaei , S
DOI: 10.1088/1742-2132/12/2/227
关键词:
摘要: This paper deals with the application of ant colony algorithm (AC) to a seismic dataset from Dezful Embayment in southwest region Iran. The objective approach is generate an accurate representation faults and discontinuities assist pertinent matters such as well planning field optimization. AC analyzed all spatial attributes which features were extracted. True fault information was detected by many artificial ants, whereas noise remains reflectors eliminated. Furthermore, fracture enhancement procedure conducted three steps on data area. In first step several chaos, variance/coherence dip deviation taken into account; resulting maps indicate high-resolution contrast for variance attribute. Subsequently, performed finally elimination non-faulting events carried out simulating behavior colonies. After considering stepwise attribute optimization, focusing chaos particular, fusion generated used algorithm. map displayed highest performance feature detection along main structural trend, confined NW–SE direction. Thus, optimized might be greater confidence network more accuracy resolution. order assess detection, cross validate reliability method used, fuzzy c-means clustering (FCMC) employed same dataset. Comparing illustrates effectiveness preference due its high resolution compared FCMC method. Accordingly, 3D planes discontinuity determined distribution fractures planning. Results revealed that impedance location probability related area vicinity faults, whilst low probably could zones permeability flow conduits. Analysis under present study suggests orientation magnitude exhibiting trend susceptible stimulation likely open fluid flow.