Determination Of Permeability Distribution From Well Test Data Using Markov Chain Mento Carlo Method

Stochastic modeling is being increasingly used to generate the numerical of reservoir parameters. It is necessary to construct and sample the posteririori probability density function (pdf's) for the rock property fields to properly evaluate the uncertainty in reservoir performance prediction. In this work, the the posteriori pdf is constructed based on prior means and variorums for log-permeability and multiwell data. The Hybrid Markov Chain Monte Carlo (Hybrid MCMC) method is used to simulate the 2-D permeability distribution from multi-well test information. The permeability simulation realizations provide a solid foundation for reservoir simulation, which is helpful to performance prediction and risk-conscious reservoir management. And a demonstration of Xingcheng gas field is presented. It is shown that Hybrid MCMC method provides a way to explore more fully and effectively the set of plausible log-permeability fields than Simulated Annealing.