کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4965410 | 1448283 | 2017 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-waveform classification for seismic facies analysis
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Seismic facies analysis provides an effective way to delineate the heterogeneity and compartments within a reservoir. Traditional method is using the single waveform to classify the seismic facies, which does not consider the stratigraphy continuity, and the final facies map may affect by noise. Therefore, by defining waveforms in a 3D window as multi-waveform, we developed a new seismic facies analysis algorithm represented as multi-waveform classification (MWFC) that combines the multilinear subspace learning with self-organizing map (SOM) clustering techniques. In addition, we utilize multi-window dip search algorithm to extract multi-waveform, which reduce the uncertainty of facies maps in the boundaries. Testing the proposed method on synthetic data with different S/N, we confirm that our MWFC approach is more robust to noise than the conventional waveform classification (WFC) method. The real seismic data application on F3 block in Netherlands proves our approach is an effective tool for seismic facies analysis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Geosciences - Volume 101, April 2017, Pages 1-9
Journal: Computers & Geosciences - Volume 101, April 2017, Pages 1-9
نویسندگان
Chengyun Song, Zhining Liu, Yaojun Wang, Xingming Li, Guangmin Hu,