Hadiloo, Saeed, Mirzaei, Saeid, Hashemi, Hosein, Beiranvand, Bijan. (1396). Comparison Between Unsupervised and Supervise Fuzzy Clustering Method in Interactive Mode to Obtain the Best Result for Extract Subtle Patterns from Seismic Facies Maps. , 8(1), 27-34. doi: 10.22059/geope.2017.240099.648346
Saeed Hadiloo; Saeid Mirzaei; Hosein Hashemi; Bijan Beiranvand. "Comparison Between Unsupervised and Supervise Fuzzy Clustering Method in Interactive Mode to Obtain the Best Result for Extract Subtle Patterns from Seismic Facies Maps". , 8, 1, 1396, 27-34. doi: 10.22059/geope.2017.240099.648346
Hadiloo, Saeed, Mirzaei, Saeid, Hashemi, Hosein, Beiranvand, Bijan. (1396). 'Comparison Between Unsupervised and Supervise Fuzzy Clustering Method in Interactive Mode to Obtain the Best Result for Extract Subtle Patterns from Seismic Facies Maps', , 8(1), pp. 27-34. doi: 10.22059/geope.2017.240099.648346
Hadiloo, Saeed, Mirzaei, Saeid, Hashemi, Hosein, Beiranvand, Bijan. Comparison Between Unsupervised and Supervise Fuzzy Clustering Method in Interactive Mode to Obtain the Best Result for Extract Subtle Patterns from Seismic Facies Maps. , 1396; 8(1): 27-34. doi: 10.22059/geope.2017.240099.648346

Comparison Between Unsupervised and Supervise Fuzzy Clustering Method in Interactive Mode to Obtain the Best Result for Extract Subtle Patterns from Seismic Facies Maps

Geopersia
مقاله 3، دوره 8، شماره 1 - شماره پیاپی 22287825، 2018، صفحه 27-34    اصل مقاله (645.43 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/geope.2017.240099.648346
نویسندگان
Saeed Hadiloo1؛ Saeid Mirzaei* 2؛ Hosein Hashemi* 3؛ Bijan Beiranvand4
1Research Institute of Applied Sciences, (ACECR), Shahid Beheshti University,Tehran,Iran
2Research Institute of Applied Sciences (ACECR), Shahid Beheshti University, Tehran, Iran
3Institute of Geophysics, University of Tehran,Iran
4Research Institute of Petroleum Industry, Tehran, Iran
چکیده
Pattern recognition on seismic data is a useful technique for generating seismic facies maps that capture changes in the geological depositional setting. Seismic facies analysis can be performed using the supervised and unsupervised pattern recognition methods. Each of these methods has its own advantages and disadvantages. In this paper, we compared and evaluated the capability of two unsupervised methods Fuzzy c-means (FCM) and Gustafson Kessel (GK) and one supervised method Adaptive Neuro-Fuzzy Inference Systems (ANFIS) at revealing the presence of a channel system. The process is performed in an interactive scheme in the SeisART software to obtain the best output. The seismic facies analysis was conducted on a 3D seismic data set acquired at North Sea block F3. Based on the results, the GK method outperformed the other two methods in delineating the channel pattern.
کلیدواژه‌ها
Seismic facies analysis؛ seismic attributes؛ fuzzy c-means؛ Gustafson Kessel؛ Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
مراجع
آمار
تعداد مشاهده مقاله: 1,378
تعداد دریافت فایل اصل مقاله: 1,088