Pressure, temperature and lithological dependence of seismic and magnetic susceptibility anisotropy in amphibolites and gneisses from the central Scandinavian Caledonides

As a petrofabric indicator, anisotropy of magnetic susceptibility (AMS) can potentially be used to infer seismic properties of rocks, and in particular seismic anisotropy. To evaluate the link between AMS and seismic anisotropy we present laboratory measurements of elastic wave velocities and anisotropy of magnetic susceptibility (AMS) for eight samples from the deep drilling investigation forming a part of the Collisional Orogeny in the Scandinavian Caledonides (COSC) project. The samples consist of a representative suite of mid crustal, deformed rock types, namely felsic and biotite-rich gneisses, and amphibolites (mafic gneisses). Compressional (P) and shear (S) waves were measured at confining pressures from ambient to 600 MPa and temperature from room condition to 600 °C. Seismic anisotropy changes with increasing temperature and pressure, where the effect of pressure is more significant than temperature. Increasing pressure results in an increase in mean wave speed values from 4.52 to 7.86 km/s for P waves and from 2.75 to 4.09 km/s for S waves. Biotite gneiss and amphibolite exhibit the highest anisotropy with P wave velocity anisotropy (AVp) in the ranges of ~9% to ~20%, and maximum S- wave anisotropy exceeds 10%. In contrast, Felsic gneisses are significantly less anisotropic, with AVp of <7% and AVs of <6%. Up to 20% anisotropy may be generated by microcracks at 600 MPa and 600 °C, which is likely originating from thermal expansion of anisotropic minerals. An agreement is found between AMS and seismic anisotropy, although this is only a case if mean magnetic susceptibility (kmean) ranges between ~1 × 10−5 to ~1 × 10−3 [SI]. Such kmean values are common in rocks dominated by paramagnetic matrix minerals. Based on our results we propose that such samples are the most likely to be useful for the prediction of seismic anisotropy based on their AMS data