Arctangent function-based third derivative attribute for characterisation of faults
文献类型：期刊论文
| 作者 | Yu, Jingbo1; Li, Zhong1,2 |
| 刊名 | GEOPHYSICAL PROSPECTING
 |
| 出版日期 | 2017-07-01 |
| 卷号 | 65期号:4页码:913-925 |
| 关键词 | Arctangent function Third derivative Fault characterization Subtle faults Seismic attribute |
| ISSN号 | 0016-8025 |
| DOI | 10.1111/1365-2478.12462 |
| 文献子类 | Article |
| 英文摘要 | Using seismic attributes such as coherence and curvature to characterise faults not only can improve the efficiency of seismic interpretation but also can expand the capability to detect faults. The coherence and curvature have been widely applied to characterising faults for years. These two methods detect faults based on the similarity of seismic waveforms and shapes of the reflectors, respectively, and they are complementary to each other and both have advantages and disadvantages in fault characterisation. A recent development in fault characterisation based on reflector shapes has been the use of the rate of change of curvature. Through an application to the seismic data from Western Tazhong of the Tarim Basin, China, it was demonstrated that the rate of change of curvature is more capable of detecting subtle faults having quite small throws and heaves. However, there often exist multiple extreme values indicating the same fault when applying the rate of change of curvature, which significantly degrades the signal-to-noise ratio of the computation result for multiple extrema interfering with each other. To resolve this problem, we propose the use of a linear combination of arctangent and proportional functions as the directrix of a cylindrical surface to fit the fault model and calculate its third derivative, which can then be used to characterise the fault. Through an application to the 3D seismic data from Western Tazhong of the Tarim Basin, the results show that the proposed method not only retains the same capability to detect subtle faults having small throws as the curvature change rate but also greatly improves the signal-to-noise ratio of the calculated result. |
| WOS关键词 | 3D SEISMIC DATA ; FRACTURE CHARACTERIZATION ; CURVATURE ; ALGORITHM ; DIP |
| WOS研究方向 | Geochemistry & Geophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:000403017400002 |
| 出版者 | WILEY |
| 资助机构 | National Natural Science Foundation of China(41372120) ; National Natural Science Foundation of China(41372120) ; National Science and Technology Major Project of China(2011ZX05008-003) ; National Science and Technology Major Project of China(2011ZX05008-003) ; National Natural Science Foundation of China(41372120) ; National Natural Science Foundation of China(41372120) ; National Science and Technology Major Project of China(2011ZX05008-003) ; National Science and Technology Major Project of China(2011ZX05008-003) ; National Natural Science Foundation of China(41372120) ; National Natural Science Foundation of China(41372120) ; National Science and Technology Major Project of China(2011ZX05008-003) ; National Science and Technology Major Project of China(2011ZX05008-003) ; National Natural Science Foundation of China(41372120) ; National Natural Science Foundation of China(41372120) ; National Science and Technology Major Project of China(2011ZX05008-003) ; National Science and Technology Major Project of China(2011ZX05008-003) |
| 源URL | [http://ir.iggcas.ac.cn/handle/132A11/52884]  |
| 专题 | 地质与地球物理研究所_岩石圈演化国家重点实验室 |
| 通讯作者 | Li, Zhong |
| 作者单位 | 1.Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100029, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Jingbo,Li, Zhong. Arctangent function-based third derivative attribute for characterisation of faults[J]. GEOPHYSICAL PROSPECTING,2017,65(4):913-925. |
| APA | Yu, Jingbo,&Li, Zhong.(2017).Arctangent function-based third derivative attribute for characterisation of faults.GEOPHYSICAL PROSPECTING,65(4),913-925. |
| MLA | Yu, Jingbo,et al."Arctangent function-based third derivative attribute for characterisation of faults".GEOPHYSICAL PROSPECTING 65.4(2017):913-925. |
入库方式： OAI收割
来源：地质与地球物理研究所
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