A technique of LLE-based attribute dimensionality reduction and its application

Offset and azimuth attributes have obvious advantages in detecting complex geological anomalies such as faults and channels. To improve information mining and result presentation, we carry out the study of Locally Linear Embedding(LLE)-based dimensionality reduction and technical process for prestack seismic attributes based on the fundamentals and technical features of the classic non-linear dimensionality reduction algorithm, LLE. Using the LLE algorithm, prestack seismic attributes in a high-dimension space extracted from partial stacks will be mapped into a dimension-reduction attribute volume in 3D space. As per a case study in Bakken field, the LLE non-linear technique is superior to Principal Component Analysis (PCA), a linear algorithm, in dimensionality reduction and feature preservation. Another practical application shows that the LLE technique can realize dimensionality reduction and fusion of prestack seismic attributes for accurate identification and characterization of geological anomalies.