Regional mantle viscosity constraints for North America reveal upper mantle strength differences across the continent

We present regional constraints of mantle viscosity for North America using a local Bayesian joint inversion of mantle flow and glacial isostatic adjustment (GIA) models. Our localized mantle flow model uses new local geoid kernels created via spatio-spectral localization using Slepain basis functions, convolved with seismically derived mantle density to calculate and constrain against the regional free-air gravity field. The joint inversion with GIA uses two deglaciation of ice sheet models (GLAC1D-NA and ICE-6G-NA) and surface relative sea level data. We solve for the local 1D mantle viscosity structure for the entire North America (NA) region, the eastern region including Hudson Bay, and the western region of North America extending into the Pacific plate. Our results for the entire NA region show one order of magnitude viscosity jump at the 670 km boundary using a high seismic density scaling parameter (e.g., δlnp/δlnvs = 0.3). Seismic scaling parameter demonstrates significant influence on the resulting viscosity profile. However, when the NA region is further localized into eastern and western parts, the scaling factor becomes much less important for dictating the resulting upper mantle viscosity characteristics. Rather the respective local mantle density heterogeneities provide the dominate control on the upper mantle viscosity. We infer local 1D viscosity profiles that reflect the respective tectonic settings of each region's upper mantle, including a weak and shallow asthenosphere layer in the west, and deep sharp viscosity jumps in the eastern transition zone, below the suggested/proposed depth range of the eastern continental root.

Joint Inversion of Rayleigh and Love Dispersion Curves Extracted from Ambient Seismic Noise Based on Secular Function

Traditional multi-mode dispersion curve inversion requires correct mode discrimination. However, when the stratum contains complex structures such as low-speed soft interlayer or high-speed hard interlayer, the dispersion curve may show phenomena such as “mode kissing” and “mode jumping”, which can easily cause mode misjudgment and lead to erroneous inversion results. Based on the “secular function”, this paper constructs a new type of objective function applied to the inversion of dispersion curve. This objective function does not require prior mode discrimination, which effectively solves the “mode misjudgment” problem of multi-mode dispersion curve inversion. The joint inversion of Rayleigh and Love dispersion curves extracted from ambient seismic noise is used to improve the constraint of the inversion and avoid the inversion falling into a local minimum in the case of a large-scale search of parameters. Finally, a numerical simulation was performed to verify the feasibility of the new inversion method.

Joint inversion of gravity and gravity gradient data: A systematic evaluation

Gravity and gravity gradiometry measurements are commonly used to map density variations in the subsurface. Gravity measurements can characterize gravitational anomalies at both long and short wavelengths effectively, but the cost of collecting a sufficiently spatially dense survey to characterize the short wavelengths can be prohibitive. Gravity gradient data can be quickly collected with short wavelength information at a low noise level, but have decreasing sensitivity to longer wavelengths. We describe a method to jointly invert gravity and gravity gradient data that takes advantage of the differing frequency contents and noise levels of the two methods to create an improved image of the subsurface. Previous work simply treated the inversion as a multiple component gravity inversion, however this can cause unintended errors in the recovered models because each data set is not guaranteed to be fit within its noise level. Our joint inversion methodology ensures that both the gravity and gravity gradient data sets are fit to within their individual noise levels by incorporating a relative weighting parameter, and we describe how to find that parameter. This method can also be used to create an improved broadband gravity anomaly map that has a reduced noise level at long wavelengths using a joint equivalent source reconstruction. We first build a synthetic model using a Minecraft world editor, that has different wavelength anomalies, and show the improvement with joint inversion. These results are also confirmed using a real world example at the R. J. Smith test range in Kauring, Australia.