Simulation models of physical phenomena in earth sciences

Abstract

The estimation techniques introduced in the previous chapter are the necessary background to describe the stochastic sequential simulation methodologies used to infer the probability distribution of a given property of interest at an unknown location, allowing at the same time the assessment of the spatial uncertainty of that property. This chapter includes a description of the most known stochastic sequential simulation used in the oil industry and discusses its pros and cons. Besides the maturity of these algorithms, there is still a lack of documentation in placing these algorithms within a single framework and as part of the modeling workflow for the oil and gas industry. The stochastic simulation algorithms presented herein are used as model perturbation techniques in the geostatistical seismic inversion methodologies presented in the following chapters.