A stochastic approach to uncertainty quantification in residual moveout analysis

• We present a framework for a stochastic uncertainty analysis of the residual moveout.
• Our work shows practically how the uncertainty increases with depth.
• A priori knowledge of data can be introduced with our framework.
• The obtained results add value to seismic interpretation.

Oil and gas exploration and production relies usually on the interpretation of a single seismic image, which is obtained from observed data. However, the statistical nature of seismic data and the various approximations and assumptions are sources of uncertainties which may corrupt the evaluation of parameters. The quantification of these uncertainties is a major issue which supposes to help in decisions that have important social and commercial implications. The residual moveout analysis, which is an important step in seismic data processing is usually performed by a deterministic approach. In this paper we discuss a Bayesian approach to the uncertainty analysis.