Bayesian Inference and Its Application to Geophysical Inversion
A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Geophysics".
Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 6419
Special Issue Editor
Special Issue Information
Dear Colleagues,
Geophysical observations are generally collected in remote sensing-type experiments, which do not represent the Earth’s interior directly. Geophysical inversion is, therefore, required to characterize properties of the Earth’s interior from these measurements.
Geophysical inverse problems are usually ill-conditioned and have nonunique solutions due to the nonlinearity of the physical relationships between the model parameters and data, to insufficient data sampling and to noise in the data. It is, therefore, necessary to quantify solution uncertainties in order to interpret the inversion results correctly.
Bayesian inference provides a powerful theoretical framework for solving inverse problems and to quantify uncertainties, having become popular in geophysics in the past decades, and having shown great potential in solving various geophysical inverse problems.
This Special Issue aims to collect all research developments related to Bayesian inference in geophysics, from method developments to various applications, including seismic, gravitational, electromagnetic inversion, etc., in order to provide a comprehensive update of the state of the art in this field.
Dr. Xin Zhang
Guest Editor
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Keywords
- Bayesian inference
- Uncertainty quantification
- Geophysical inversion
- Inverse problem
- Probability
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