Reservoir prediction using multi-wave seismic attributes
Ye Yuan1, 2, Yang Liu1, 2, Jingyu Zhang1, 2, Xiucheng Wei3, Tiansheng Chen3
1 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China 2 CNPC Key Laboratory of Geophysical Prospecting, China University of Petroleum, Beijing 102249, China 3 Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China
Reservoir prediction using multi-wave seismic attributes
Ye Yuan1, 2, Yang Liu1, 2, Jingyu Zhang1, 2, Xiucheng Wei3, Tiansheng Chen3
1 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China 2 CNPC Key Laboratory of Geophysical Prospecting, China University of Petroleum, Beijing 102249, China 3 Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China
摘要The main problems in seismic attribute technology are the redundancy of data and the uncertainty of attributes, and these problems become much more serious in multi-wave seismic exploration. Data redundancy will increase the burden on interpreters, occupy large computer memory, take much more computing time, conceal the effective information, and especially cause the “curse of dimension”. Uncertainty of attributes will reduce the accuracy of rebuilding the relationship between attributes and geological significance. In order to solve these problems, we study methods of principal component analysis (PCA), independent component analysis (ICA) for attribute optimization and support vector machine (SVM) for reservoir prediction. We propose a flow chart of multi-wave seismic attribute process and further apply it to multi-wave seismic reservoir prediction. The processing results of real seismic data demonstrate that reservoir prediction based on combination of PP- and PS-wave attributes, compared with that based on traditional PP-wave attributes, can improve the prediction accuracy.
Abstract：The main problems in seismic attribute technology are the redundancy of data and the uncertainty of attributes, and these problems become much more serious in multi-wave seismic exploration. Data redundancy will increase the burden on interpreters, occupy large computer memory, take much more computing time, conceal the effective information, and especially cause the “curse of dimension”. Uncertainty of attributes will reduce the accuracy of rebuilding the relationship between attributes and geological significance. In order to solve these problems, we study methods of principal component analysis (PCA), independent component analysis (ICA) for attribute optimization and support vector machine (SVM) for reservoir prediction. We propose a flow chart of multi-wave seismic attribute process and further apply it to multi-wave seismic reservoir prediction. The processing results of real seismic data demonstrate that reservoir prediction based on combination of PP- and PS-wave attributes, compared with that based on traditional PP-wave attributes, can improve the prediction accuracy.
基金资助:China Important National Science & Technology Specific Projects (No. 2011ZX05019-008) and National Natural Science Foundation of China (No. 40839901)
通讯作者:
Yang Liu
E-mail: cuply72@yahoo.com.cn
引用本文:
Ye Yuan, Yang Liu, Jingyu Zhang, Xiucheng Wei, Tiansheng Chen. Reservoir prediction using multi-wave seismic attributes[J]. 《地震学报》英文版, 2011, 24(4): 373-389.
Ye Yuan, Yang Liu, Jingyu Zhang, Xiucheng Wei, Tiansheng Chen. Reservoir prediction using multi-wave seismic attributes. Earthquake Science, 2011, 24(4): 373-389.
