  Borehole resistivity measurements are routinely inverted in real-time during
geosteering operations. The inversion process can be efficiently performed with
the help of advanced artificial intelligence algorithms such as deep learning.
These methods require a large dataset that relates multiple earth models with
the corresponding borehole resistivity measurements. In here, we propose to use
an advanced numerical method --refined isogeometric analysis (rIGA)-- to
perform rapid and accurate 2.5D simulations and generate databases when
considering arbitrary 2D earth models. Numerical results show that we can
generate a meaningful synthetic database composed of 100,000 earth models with
the corresponding measurements in 56 hours using a workstation equipped with
two CPUs.
