Monte Carlo inversion techniques were first used by Earth scientists more than 30 years
ago. Since that time they have been applied to a wide range of problems, from the inversion …

Monte Carlo methods have become important in analysis of nonlinear inverse problems
where no analytical expression for the forward relation between data and model parameters …

Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial
optimization and neural computing | Guide books skip to main content ACM Digital Library …

Providing an up-to-date overview of the most popular global optimization methods used in
interpreting geophysical observations, this new edition includes a detailed description of the …

Probabilistic formulation of inverse problems leads to the definition of a probability
distribution in the model space. This probability distribution combines a priori information …

This paper presents a new derivative-free search method for finding models of acceptable
data fit in a multidimensional parameter space. It falls into the same class of method as …

Simulated annealing (SA) presents an optimization technique with several striking positive
and negative features. Perhaps its most salient feature, statistically promising to deliver an …

The treatment of multioffset seismic data as an acoustic wave field is becoming increasingly
disturbing to many geophysicists who see a multitude of wave phenomena, such as …

Probabilistic earthquake location with non-linear, global search methods allows the use of
3D models and produces comprehensive uncertainty and resolution information …

Monte Carlo direct search methods, such as genetic algorithms, simulated annealing, etc.,
are often used to explore a finite-dimensional parameter space. They require the solving of …