LI Hongwei, BAI Xuelian, CUI Jingbin, WAN Zhonghong, YUAN Shihong, CHU Wanchang. Fault identification technology of ant attribute optimization[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(6): 174-179. DOI: 10.3969/j.issn.1001-1986.2019.06.026
Citation: LI Hongwei, BAI Xuelian, CUI Jingbin, WAN Zhonghong, YUAN Shihong, CHU Wanchang. Fault identification technology of ant attribute optimization[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(6): 174-179. DOI: 10.3969/j.issn.1001-1986.2019.06.026

Fault identification technology of ant attribute optimization

  • In the field of seismic geological exploration, the ant attributes is more and more widely used for rapid identification of fault system, and in the process of practical application, ant attributes based on 3D seismic data extraction are displayed either along strata slice(plan) or in section, the features of fault system and distribution characteristics of seismic events is not corresponding to the actual situation, the application effect is poorer, fault interpretation work is given priority to with manual interpretation backbone profile, unable to realize fault automatic tracking. In view of this widespread situation, this paper studies and analyzes the actual data and finds that simply extracting the attribute of ant body for fault interpretation cannot ensure the accuracy of fault identification. Therefore, a set of techniques for rapid fault identification of ant body was developed. First of all, according to the geological target optimization of ant attribute of termination criteria, application of the thin ant body of binarization technology makes the ant pheromone focus and converge, and then the fault surface and angle were analyzed by automatic fault separation, the rule of fault surface and the relationship between fault surfaces were effectively generated and defined, the final use of 3D visualization plane-solid simultaneous interpretation technology determined directly the rationality of the spatial distribution of fault system in the study area, sections were carefully edited and adjusted refiningly, fault edge was extracted automatically according to the needed intervals, so as to realize the automatic tracking of fault interpretation. Through the application of this series of techniques, good results have been achieved in the identification of fault systems in the study area, especially in the rapid automatic tracking of large-scale faults, and the framework for fault interpretation in the study area has been quickly and accurately established. The application of ant attributes to fault identification is a series of techniques. It is the key to test and optimize the calculation parameters using typical profiles. In order to obtain effective fault recognition results, the ant attributes in the whole area were calculated in accordance with this idea.
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