Petrologically-constrained thermo-chemical modelling of cratonic upper mantle consistent with elevation, geoid, surface heat flow, seismic surface waves and MT data

Abstract:

The Earth comprises a single physio-chemical system that we interrogate from its surface and/or from space making observations related to various physical and chemical parameters. A change in one of those parameters affects many of the others; for example a change in velocity is almost always indicative of a concomitant change in density, which results in changes to elevation, gravity and geoid observations. Similarly, a change in oxide chemistry affects almost all physical parameters to a greater or lesser extent. We have now developed sophisticated tools to model/invert data in our individual disciplines to such an extent that we are obtaining high resolution, robust models from our datasets. However, in the vast majority of cases the different datasets are modelled/inverted independently of each other, and often even without considering other data in a qualitative sense.

The LitMod framework of Afonso and colleagues presents integrated inversion of geoscientific data to yield thermo-chemical models that are petrologically consistent and constrained. Input data can comprise any combination of elevation, geoid, surface heat flow, seismic surface wave (Rayleigh and Love) data and receiver function data, and MT data. The basis of LitMod is characterization of the upper mantle in terms of five oxides in the CFMAS system and a thermal structure that is conductive to the LAB and convective along the adiabat below the LAB to the 410 km discontinuity. Candidate solutions are chosen from prior distributions of the oxides. For the crust, candidate solutions are chosen from distributions of crustal layering, velocity and density parameters. Those candidate solutions that fit the data within prescribed error limits are kept, and are used to establish broad posterior distributions from which new candidate solutions are chosen.

Examples will be shown of application of this approach fitting data from the Kaapvaal Craton in South Africa and the Rae Craton in northern Canada. I will show that the MT data are the most discriminatory, requiring many millions of candidate solutions to be tested in order to sufficiently establish posterior distributions. In particular, the MT data require layered lithosphere, whereas the other data can be fit with a single lithosphere, and the MT data are particularly sensitive to the depth to the LAB.