The Galápagos Archipelago, which lies less than 200 km south of the Galápagos Spreading Center (GSC), provides a novel setting to study how mantle plumes, spreading centers, and the lithosphere interact. Numerous geophysical, geochemical, and petrologic studies have defined variations in mantle temperature and composition, as well as magma flux of the ridge-plume system. What these characteristics imply about upper-mantle rheology and plume-to-ridge mass and heat transfer is not well understood.
To address this issue, Ito and Bianco (2014) provide two models of plume flow at the Galápagos Archipelago that account for realistic ridge geometry of the GSC and varying mantle structure. The first model represents a plume with low viscosity due to temperature-dependent mantle rheology. Fed by a narrow plume stem, plume mantle ponds below the thermal lithosphere and is channeled up to and along the ridge by the sloping lithosphere. The second model represents a plume with high viscosity in the upper mantle due to added dependence on water content, simulating extraction of water by partial melting. A wide plume stem creates a thick plume pond that accumulates under a deeper, dehydrated compositional lithosphere.
To determine the sensitivity of teleseismic data to different patterns of mantle flow, this study will generate a synthetic anisotropic seismic dataset of P and S arrivals from these two models and compare the absolute traveltime differences. Anisotropy will account for lattice-preferred orientation (LPO) of olivine crystals, which are highly anisotropic in seismic velocity and tend to align in the direction of plastic flow. Due to LPO, mantle flow creates a strong anisotropic pattern that needs to be accounted for in seismic imaging problems.
The geometry of the Marine IGUANA (2024) experiment, consisting of 53 broadband ocean bottom seismometers deployed for 15 months, will be used as the synthetic teleseismic array. This study will demonstrate how the two models of plume flow can be distinguished through their seismic signature to inform the interpretation of the observed Marine IGUANA seismic data.
We will also explore multiple imaging techniques and their capabilities: Linear inverse method tomography, and Bayesian inverse method tomography.