Abstract

Shales are widespread in the Earth's crust, and organic-rich shales have become an important energy resource. Geophysical data are becoming increasingly important for characterizing shale reservoirs to find zones of good quality, typically characterized by high kerogen and low clay content. Away from well control, most geophysical characterization of shale reservoirs are based on the effects of kerogen on the elastic properties of the shale rock. However, both clay and kerogen act to reduce the stiffness of shale rocks, and their effects might be inseparable using seismic properties alone. A combination of the elastic and electrical properties of organic-rich shales might improve our ability to locate zones of good quality by decoupling the effects of kerogen and clay. Kerogen is considerably more resistive than clay and should, in theory, increase the bulk resistivity of the shale when present. The effects of shale composition on the joint elastic-electrical properties of shales can be explored using a combination of suitable well data and rock physics modeling. A comprehensive suite of well data could be used to observe trends, with a joint model aiding trend analysis. Effective medium models lend themselves well to estimating joint effective properties of a heterogeneous composite. This is because using the same approach for both the elastic and electrical properties would ensure an equivalent microstructure for both properties, as would be expected in practice. In this study, a joint effective medium model was calibrated and constrained using well data, achieving good correlation with elastic and electrical well log data from two wells. The results show that both kerogen and clay tend to reduce the stiffness of shales as expected, however; kerogen plays a significant role in increasing the bulk electrical resistivity of shales, whereas clay has the opposite effect. This joint elastic-electrical approach could potentially help discriminate kerogen-rich from clay-rich shales, in addition to constraining each individual property.

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