Geophysics
We present a multimodal machine learning (MML) workflow to assimilate and simultaneously predict the 3d distribution of numeric and categorical features along a groundwater-geothermal continuum. Success of the MML workflow relies on a…
Underground duct banks carrying power cables dissipate heat to the surrounding soil. The amount of heat dissipated determines the current rating of cables, which in turn affects the sizing of the cables. The dissipation of heat through the…
The data-driven Marchenko method is able to redatum wavefields to arbitrary locations in the subsurface, and can, therefore, be used to isolate zones of specific interest. This creates a new reflection response of the target zone without…
Interference tests are used in shale reservoirs to evaluate the strength of connectivity between wells. The results inform engineering decisions about well spacing. In this paper, we propose a new procedure for interpreting interference…
Bed load transport is the movement of particles along the top of a bed through rolling, saltation, and suspension created by turbulent lift above the bed surface. In recent years, there has been a resurgence of interest in the idea that bed…
The massive cost of 3D acquisition calls for methods to reduce the number of receivers by designing optimal receiver sampling masks. Recent studies on 2D seismic showed that maximizing the spectral gap of the subsampling mask leads to…
Hydraulic geometry parameters describing river hydrogeomorphic is important for flood forecasting. Although well-established, power-law hydraulic geometry curves have been widely used to understand riverine systems and mapping flooding…
The circulation in Europa's ocean determines the degree of thermal, mechanical and chemical coupling between the ice shell and the silicate mantle. Using global direct numerical simulations, we investigate the effect of heterogeneous tidal…
Recent studies have shown that deep learning (DL) models can skillfully predict the El Ni\~no-Southern Oscillation (ENSO) forecasts over 1.5 years ahead. However, concerns regarding the reliability of predictions made by DL methods persist,…
A novel multiphysics-decision tree learning algorithm is presented for (1) estimating transport properties in the variably saturated subsurface governed by explicitly coupled equations for water, heat, and solute transport; and (2)…
We first report that the seismic time-sequence data from around the world, excluding major earthquakes, consistently yield the power spectral density inversely proportional to the frequency f. This is the 1/f fluctuation that appears…
We present dynamos computed using a hybrid QG-3D numerical scheme in a thick spherical shell geometry. Our model is based on a quasi-geostrophic convection code extended with a 3D treatment of heat transport and magnetic induction. We find…
We invert for motions at the surface of Earth's core under spatial and temporal constraints that depart from the mathematical smoothings usually employed to ensure spectral convergence of the flow solutions. Our spatial constraints are…
We jointly invert for magnetic and velocity fields at the core surface over the period 1997-2017, directly using ground-based observatory time series and measurements from the CHAMP and Swarm satellites. Satellite data are reduced to the…
We present investigations of rapidly-rotating convection in a thick spherical shell geometry relevant to planetary cores, comparing results from Quasi-Geostrophic, 3D and hybrid QG-3D models. The 170 reported calculations span Ekman…
This paper is devoted to the study of the interaction between two distinct forms of non-stationary processes, which we will refer to as non-stationarity of first and second kind. The non-stationarity of first kind is caused by…
While computer science has seen remarkable advancements in foundation models, which remain underexplored in geoscience. Addressing this gap, we introduce a workflow to develop geophysical foundation models, including data preparation, model…
Recreating complex, high-dimensional global fields from limited data points is a grand challenge across various scientific and industrial domains. Given the prohibitive costs of specialized sensors and the frequent inaccessibility of…
Accurate simulation of granular flow dynamics is crucial for assessing various geotechnical risks, including landslides and debris flows. Granular flows involve a dynamic rearrangement of particles exhibiting complex transitions from…
Geochemical data are compositional in nature and are subject to the problems typically associated with data that are restricted to the real non-negative number space with constant-sum constraint, that is, the simplex. Geochemistry can be…