Inversion of geophysical data set (e.g., gravity, gravity gradiometry, magnetics, DC, IP, MT, EM, seismic traveltime) constrained by geological prior information.; Joint inversion of multiple geophysical data sets based on structural similarity and prior petrophysical measurements; Sparse inversion using L1 and L0 norm regularization; Magnetization vector inversion with clustering constraints; Machine learning, such as neural networks and deep learning, applied to geophysical problems; Sparse signal processing of geophysical data.