Multispectral Phase-Based Geosteering Coherence Attributes for Deep Stratigraphic Feature Characterization

Abstract

The deep exploration has become the focus of attention in the field of earth sciences. Coherence is a routine measure to identify structural and stratigraphic anomalies, such as faults, channels, and fractures in subsurface. However, deep seismic data typically suffer from a low signal-to-noise ratio and a weak reflection amplitude, thus it may not provide a better insight for seismic attribute analysis. The phase information has the ability to detect subtle changes in subsurface but it is sensitive to noise, thereby masking some stratigraphic features in the full-bandwidth data. To address these two issues, we propose a multispectral phase-based geosteering coherence method by combining coherence and spectral decomposition for deep stratigraphic feature characterization. The proposed method can effectively select and utilize the phase components of favorable spectral bands, which can detect different scale geologic discontinuities and reduce or avoid the effect of random noise in deep seismic data. Furthermore, corendering the coherence images of three different frequency components using red–green–blue blending can detect more geologic details in subsurface. The examples including 3-D physical modeling data and real seismic data set of carbonate reservoir from western deep formation are employed to demonstrate the effectiveness of the proposed method. The coherence attributes obtained from the proposed method can detect the weak or hidden geologic details clearer than the geosteering coherence calculated from the broadband seismic data, and it may serve as a future tool for detecting the distribution of geologic abnormalities in deep exploration.