Bayesian geophysical inverse problems
Research context
research method · conditional · As of 2026-10-10
An inverse solution is a posterior distribution conditioned on observations, a forward operator, likelihood and prior.
Key knowledge
An inverse solution is a posterior distribution conditioned on observations, a forward operator, likelihood and prior. Nonuniqueness survives when different seismic, gravity or magnetic models fit the same data; posterior concentration depends on these choices.
Values and equations
p(m|d) = p(d|m) p(m) / integral p(d|m) p(m) dm
- m
- Model parameters
- d
- Observed data
- p
- Densities with respect to stated measures
Conditions and scope
- Specify observation support, coordinate/units conventions and a model-discrepancy term where needed. The normalizing evidence integral must be finite and strictly positive.
- An identifiable forward solution does not imply an identifiable inverse solution.
Sources · 1
References
Sources retain their recorded scope. A source link alone does not establish verification of every statement.
Evidence and review
The Bayesian Approach to Inverse Problems: Sections 1.1–1.3 and 4: likelihood, regularization, posterior approximation (selected source body inspected).
2026-10-10 · Bounded source check of the recorded statement and conditions. This does not certify a unique physical model, reproduce the cited study or replace independent branch review.
Entry details
Permanent link to this entry ↗- Record identity
- research-earth-bayesian-inversion
- Revision
- research.1
- Structured reference record
- Postgraduate & research reference