Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering
Faults represent important analytical targets for the identification of perceptual ground motions and associated seismic hazards. In particular, during oil production, important data such as the path and flow rate of fluid flows can be obtained from information on fault location and their connectivi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/18/8734 |
| _version_ | 1797520354902540288 |
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| author | Minki Kim Jeongmin Yu Nyeon-Keon Kang Byoung-Yeop Kim |
| author_facet | Minki Kim Jeongmin Yu Nyeon-Keon Kang Byoung-Yeop Kim |
| author_sort | Minki Kim |
| collection | DOAJ |
| description | Faults represent important analytical targets for the identification of perceptual ground motions and associated seismic hazards. In particular, during oil production, important data such as the path and flow rate of fluid flows can be obtained from information on fault location and their connectivity. Seismic attributes are conventional methods used for fault detection, whereby information obtained from seismic data are analyzed using various property processing methods. The analyzed data eventually provide information on fault properties and imaging of fault surfaces. In this study, we propose an efficient workflow for fault detection and extraction of requisite information to construct a fault surface model using 3D seismic cubes. This workflow not only improves the ability to detect faults but also distinguishes the edges of a fault more clearly, even with the application of fewer attributes compared to conventional workflows. Thus, the computing time of attribute processing is reduced, and fault surface cubes are generated more rapidly. In addition, the reduction in input variables reduces the effect of the interpreter’s subjective intervention on the results. Furthermore, the clustering method can be applied to the azimuth and dip of the fault to be extracted from the complexly intertwined fault faces and subsequently imaged. The application of the proposed workflow to field data obtained from the Vincentian oil field in Australia resulted in a significant reduction in noise compared to conventional methods. It also led to clearer and continuous edge detection and extraction. |
| first_indexed | 2024-03-10T07:55:35Z |
| format | Article |
| id | doaj.art-e422b8cef8eb47f2837b90a9d4ad1249 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T07:55:35Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-e422b8cef8eb47f2837b90a9d4ad12492023-11-22T11:57:25ZengMDPI AGApplied Sciences2076-34172021-09-011118873410.3390/app11188734Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation ClusteringMinki Kim0Jeongmin Yu1Nyeon-Keon Kang2Byoung-Yeop Kim3Schlumberger Digital & Integration Division, Seoul 03056, KoreaPetroleum & Marine Research Division, Korea Institute of Geoscience and Mineral Resources, Daejeon 34132, KoreaPetroleum & Marine Research Division, Korea Institute of Geoscience and Mineral Resources, Daejeon 34132, KoreaPetroleum & Marine Research Division, Korea Institute of Geoscience and Mineral Resources, Daejeon 34132, KoreaFaults represent important analytical targets for the identification of perceptual ground motions and associated seismic hazards. In particular, during oil production, important data such as the path and flow rate of fluid flows can be obtained from information on fault location and their connectivity. Seismic attributes are conventional methods used for fault detection, whereby information obtained from seismic data are analyzed using various property processing methods. The analyzed data eventually provide information on fault properties and imaging of fault surfaces. In this study, we propose an efficient workflow for fault detection and extraction of requisite information to construct a fault surface model using 3D seismic cubes. This workflow not only improves the ability to detect faults but also distinguishes the edges of a fault more clearly, even with the application of fewer attributes compared to conventional workflows. Thus, the computing time of attribute processing is reduced, and fault surface cubes are generated more rapidly. In addition, the reduction in input variables reduces the effect of the interpreter’s subjective intervention on the results. Furthermore, the clustering method can be applied to the azimuth and dip of the fault to be extracted from the complexly intertwined fault faces and subsequently imaged. The application of the proposed workflow to field data obtained from the Vincentian oil field in Australia resulted in a significant reduction in noise compared to conventional methods. It also led to clearer and continuous edge detection and extraction.https://www.mdpi.com/2076-3417/11/18/8734directional fault detectionfault extractionseismic attributesant trackingedge evidenceorientation clustering |
| spellingShingle | Minki Kim Jeongmin Yu Nyeon-Keon Kang Byoung-Yeop Kim Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering Applied Sciences directional fault detection fault extraction seismic attributes ant tracking edge evidence orientation clustering |
| title | Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering |
| title_full | Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering |
| title_fullStr | Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering |
| title_full_unstemmed | Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering |
| title_short | Improved Workflow for Fault Detection and Extraction Using Seismic Attributes and Orientation Clustering |
| title_sort | improved workflow for fault detection and extraction using seismic attributes and orientation clustering |
| topic | directional fault detection fault extraction seismic attributes ant tracking edge evidence orientation clustering |
| url | https://www.mdpi.com/2076-3417/11/18/8734 |
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