Uncertainty in production forecasts based on well observations, seismic data, and production history

A stochastic model in a Bayesian setting, conditioned on well observations, seismic amplitude data and production history, is defined. Samples of reservoir characteristics and production forecasts from the posterior model are used to evaluate the impact of various observation types. Well observations are found to be important to production forecasts due to near-well conditioning, while seismic data impact facies geometries but not the production forecasts. Production history contributes significantly only if certain events, such as gas-breakthrough time, are observed in wells. A brute-force rejection sampling approach may work well if proper conditioning on well observations and seismic data is done.