Zhen Wang, Z. Long, G. Al-Regib, Asjad Amin, Mohamed Deriche
{"title":"Automatic fault tracking across seismic volumes via tracking vectors","authors":"Zhen Wang, Z. Long, G. Al-Regib, Asjad Amin, Mohamed Deriche","doi":"10.1109/ICIP.2014.7026182","DOIUrl":null,"url":null,"abstract":"The identification of reservoir regions has a close relationship with the detection of faults in seismic volumes. However, only relying on human intervention, most fault detection algorithms are inefficient. In this paper, we present a new technique that automatically tracks faults across a 3D seismic volume. To implement automation, we propose a two-way fault line projection based on estimated tracking vectors. In the tracking process, projected fault lines are integrated into a synthesized line as the tracked fault line, through an optimization process with local geological constraints. The tracking algorithm is evaluated using real-world seismic data sets with promising results. The proposed method provides comparable accuracy to the detection of faults explicitly in every seismic section, and it also reduces computational complexity.","PeriodicalId":6856,"journal":{"name":"2014 IEEE International Conference on Image Processing (ICIP)","volume":"12 1","pages":"5851-5855"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2014.7026182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
The identification of reservoir regions has a close relationship with the detection of faults in seismic volumes. However, only relying on human intervention, most fault detection algorithms are inefficient. In this paper, we present a new technique that automatically tracks faults across a 3D seismic volume. To implement automation, we propose a two-way fault line projection based on estimated tracking vectors. In the tracking process, projected fault lines are integrated into a synthesized line as the tracked fault line, through an optimization process with local geological constraints. The tracking algorithm is evaluated using real-world seismic data sets with promising results. The proposed method provides comparable accuracy to the detection of faults explicitly in every seismic section, and it also reduces computational complexity.