Characterization of subsurface heterogeneity: Integration of softand hard information using multi-dimensional Coupled Markov chainapproach

Publisher Summary This chapter extends the coupled Markov chain (CMC) to three-dimensional (3-D) to better suit the model for many practical problems. The CMC model is very convenient to implement for stochastic simulation, because the CMC model requires neither parametric fitting of a semivariogram model nor cumbersome indicator cokriging techniques. In the Markovian framework, the conditional distribution of any future state is independent of the past history if the present state is given. As an illustration of the applicability of the CMC model, an example based on data from the Alabama MADE Test Site on unconsolidated coastal plain sediments is considered. Based on the developed 3-D CMC model, a single realization can be generated. Monte Carlo simulations show that this model is stable for most cases. The 2-D application on the MADE site shows that the model has promise for delineating the complex geological structure of an aquifer, even with only sparse data.