Quantitative seismic fracture characterization of a sandstone reservoir; Decatur, Illinois Basin

The Illinois Basin Decatur Project, a carbon capture and sequestration task, was undertaken to sequester 1 million tonnes of CO (sub 2) into a sandstone reservoir. A 3D seismic survey was conducted to characterize the reservoir. A geomodel was developed from seismic data, inversion results, and well data to geostatistically map the storage potential of the reservoir. However, no fracture model was created or utilized in this exercise. Fractures inherently influence the porosity and permeability of a reservoir. Ignoring them in reservoir characterization is not an optimal reservoir management practice. The image-log interpretation from a few vertical wells drilled in the area shows the bedding plane dips, but no fracture has been identified. However, the lack of fracture crossings in a few vertical wells does not imply that a formation is devoid of fractures altogether. Hence, seismic fracture characterization (leveraging the dense 3D seismic data) is necessary for a reservoir characterization exercise. We utilized the publicly available Decatur 3D seismic data set to run a seismic fracture characterization workflow to delineate potential fracture corridors present in the reservoir. We calculated three edge detection attributes (structural tensor, structure-oriented semblance, and structural dip) in combination to delineate the fracture lineaments. Our workflow extracts several quantitative measures of the seismic lineaments such as dip, azimuth, area, and length, which can be analyzed statistically. The principal focus of this work is to find a way forward to integrate the fractures from seismic data in a geologic model that can be utilized in simulations. Based on our interpretation of seismic fractures, we created a discrete fracture network that can be a building block for creating a finer-resolution fracture model. We also explored the fractal characteristics of seismic-derived fracture lineaments as a way forward for generating discrete fracture networks.