Inverse-forward method for heat flow estimation: case study for the Arctic region

Abstract

The heat flow data are important in many aspects including interpretation of various geophysical observations, solutions of important engineering problems, modelling of the ice dynamics, and related environmental assessment. However, the distribution of the direct measurements is quite heterogeneous over the Earth. Different methods have been developed during past decades to create continuous maps of the geothermal heat flow (GHF). Most of them are based on the principle of similarity of GHF values for the lithosphere with comparable age and tectonic history or inversion of magnetic field data. Probabilistic approach was also used to realize this principle. In this paper, we present a new method for extrapolating the GHF data, based on the inversion of a geophysical data set using optimization problem solution. We use the results of inversion of seismic and magnetic field data into temperature and data from direct heat flow measurements. We use the Arctic as the test area because it includes the lithosphere of different ages, types, and tectonic settings. In result, the knowledge of GHF is important here for various environmental problems. The resulting GHF map obtained well fits to the observed data and clearly reflects the lithospheric domains with different tectonic history and age. The new GHF map constructed in this paper reveals some significant features that were not identified earlier. In particular, these are the increased GHF zones in the Bering Strait, the Chukchi Sea and the residual GHF anomaly in the area of the Mid-Labrador Ridge. The latter was active during the Paleogene.

A Set of Geophysical Fields for Modeling of the Lithosphere Structure and Dynamics in the Russian Arctic Zone

“…Seismic tomography models provide consistent images of the mantle, but usually with low resolution [19]. Furthermore, variations of seismic velocities could be associated with both thermal and compositional anomalies, for which effects cannot be divided without additional information [20,21]. Heat flow determinations are also very sparse and unevenly distributed.…”

“…To fill these gaps, we used theoretical models for global heat flux [51,52], which are based on interpolating measured data to account for the structure of the lithosphere (Figure 8A,B). Then, a method was developed for estimating the surface heat flux using inversion of seismic and magnetic data, supported by direct measurements [21]. This approach allows for using all available indirect data on the thermal structure of the lithosphere to build a thermal model by the optimization method and minimize errors arising from the uncertainty of input data.…”