  We present a methodology for quantifying seismic velocity and pore pressure
uncertainty that incorporates information regarding the geological history of a
basin, rock physics, well log, drilling and seismic data. In particular, our
approach relies on linking velocity models to the basin modeling outputs of
porosity, mineral volume fractions and pore pressure through rock physics
models. We account for geological uncertainty by defining prior probability
distributions on uncertain parameters and performing Monte Carlo basin
simulations. We perform probabilistic calibration of the basin model outputs by
defining data likelihood distributions to represent well data uncertainty. Rock
physics modeling transforms the basin modeling outputs to give us multiple
velocity realizations used to perform multiple depth migrations. We present an
approximate Bayesian inference framework which uses migration velocity analysis
in conjunction with well data for updating velocity and basin modeling
uncertainty. We apply our methodology in 2D to a real field case from Gulf of
Mexico and demonstrate that our methodology allows building a geologic and
physical model space for velocity and pore pressure prediction with reduced
uncertainty.
