Melt extraction from partially molten peridotites

Abstract

We measured the rate of melt extraction from partially molten olivine aggregates into a porous reservoir as a function of melt content (ϕ), melt viscosity, grain size, and pressure difference. Samples were prepared using mixtures of olivine and either lithium silicate, MORB glass, or albite glass to obtain a range in melt viscosities. Experiments were conducted at 1473 K with a confining pressure (Pc) of 300 MPa. The melt pressure (Pm) was controlled using a pore fluid actuator to adjust the pressure of Ar gas (Pf) in contact with the melt. Compaction rates decrease with decreasing ϕ and increase linearly with the pressure difference ΔP = Pc − Pf. For the two lower viscosity melts, no gradients in melt fraction were observed in samples with melt fractions as low as 0.03. By contrast, the melt fraction increases with distance away from the reservoir for samples with the highest viscosity albitic melt. These observations indicate that the compaction length for the lower viscosity melt experiments (i.e., olivine + MORB and olivine + Li‐silicate) was greater than the sample length. However, the compaction rates of these samples were limited by two different processes. Melt transport is relatively easy in the coarse‐grained Li‐silicate samples where melt viscosity is lower. In this case, melt extraction is limited by viscous compaction of the solid matrix. In the olivine + MORB samples, the fine grain size and higher melt viscosity inhibits melt transport and limits extraction rates. The olivine + MORB data constrain the permeability of the partially molten samples. Permeability is proportional to ϕ3 for melt fractions from 0.05 to 0.35. In addition, assuming that permeability scales with the square of the grain size, the magnitude of the permeability compares very well with that measured for Fontainebleau sandstone and fine‐grained quartz aggregates with similar pore‐space topology. Calculations of the compaction length using previously published continuum models agree with the estimates derived from the experiments.