Abstract
Accurate seismic fault interpretation is critical to understanding the structural framework of the subsurface and mitigating potential hazards such as induced seismicity or potential fluid migration outside the target reservoir that might affect other formations such as shallow aquifers. In general, faults are identified by mapping discontinuities in the seismic amplitudes or edge-enhancing seismic attributes. However, detecting small-offset faults is challenging due to the lack of clear discontinuities. In this study, we apply volumetric aberrancy and multispectral coherence to (1) delineate faults that exhibit little to no offsets on a seismic volume acquired for carbon capture and storage in the Illinois Basin – Decatur Project and (2) correlate them with the microseismic activity during supercritical CO2 injection. We first apply spectral balancing to improve the vertical resolution of the seismic amplitudes volume. Although spectral balancing improves the resolution, not all improved spectral components aid in delineating subtle faults. Therefore, we only choose the spectral components that best enhance fault offsets to compute the multispectral coherence and quantify discontinuities. We also compute volumetric aberrancy to quantify flexures and their azimuths given by lateral changes in curvature. We find that these seismic attributes are helpful in delineating small-offset faults in the study area. We use a postconditioning workflow called fault enhancement to improve the resolution of the multispectral coherence and quantify the faults’ dip and azimuth. Based on the azimuth estimations, we extract faults aligned with or close to the maximum horizontal stress field. We observe that several of the extracted faults correlate well with the microseismic events, whereas other faults do not match any event, possibly due to the lack of pore pressure variations during injection, stratigraphic and structural variabilities, or because multispectral coherence and volumetric aberrancy do not directly measure fractures in seismic data.