Conditional stochastic simulation of carbon dioxide concentrations

Abstract

This paper deals with conditional stochastic simulation. Old, abandoned coal mines contain the vestiges of coal mine gas. Coal mine gas usually consists of methane, nitrogen and carbon dioxide. But despite that they no longer produce coal, these sites are still contributing to climate change by leaking carbon dioxide into the atmosphere. The concentrations of carbon dioxide were studied and used as input parameters for stochastic simulation. Kriged surface underestimates the high values and overestimates the low values. The simulation model is conditioned to reproduce the data at known sample points to minimize the variability between the simulated data and the true field data. The main aim of this investigation is to compare selected interpolation methods that are currently used in practice with stochastic simulation, based on the development of the values. The advantages and disadvantages of each approach are discussed. The study shall provide users with rec-ommendations for selecting the optimal interpolation method and its application to real data.