Seismic imaging is a linearized inversion problem relying on the minimization of a least‐
squares misfit functional as a function of the medium perturbation. The success of this …

Many seismic exploration techniques rely on the collection of massive data volumes that are
mined for information during processing. This approach has been extremely successful, but …

Waveform inversion is the method of choice for determining a highly heterogeneous
subsurface structure. However, conventional waveform inversion requires that the wavefield …

We explore the use of stochastic optimization methods for seismic waveform inversion. The
basic principle of such methods is to randomly draw a batch of realizations of a given misfit …

For some acquisition geometries, the cost of Full Waveform Inversion (FWI) can be
considerably reduced by inverting simultaneously encoded shots. Encoded‐shot strategies …

Full-waveform inversion (FWI) can be formulated as a nonlinear least-squares optimization
problem. This nonconvex problem can be computationally expensive because it requires …

Images obtained from seismic data are used by the oil and gas industry for geophysical
exploration. Cutting-edge methods for transforming the data into interpretable images are …

Full waveform inversion (FWI) is an extremely important velocity-model-building method.
However, it involves a large amount of calculation, which hindsers its practical application …

Seismic imaging relies on the collection of multi-experimental data volumes in combination
with a sophisticated back-end to create high-fidelity inversion results. While significant …

A set of second-order differential equations describing the space− time behaviour of
derivatives of displacement with respect to model parameters (ie waveform sensitivities) is …