Detailed reservoir engineering fundamentals and real-world applications along with well testing procedures This practical resource provides you with the tools and techniques you need to successfully construct petroleum reservoir models of all types and sizes. You will learn how to improve reserve estimations and make development decisions that will optimize well performance. Each chapter features detailed explanations and applications as well as examples and exercise questions that reinforce salient points. Petroleum Reservoir Modeling and Simulation: Geology, Geostatistics, and Performance Prediction describes the process of applying reservoir modeling techniques and flow analysis methods to specific geologic systems encountered in all subsurface exploration and development. Special attention is given to shale, carbonate, and subsea formations. You will get comprehensive coverage of geologic descriptions, quantitative modeling, geostatistics, well testing principles, upscaled models, and history matching. *Contains worked-out numerical examples and cases studies*Provides software simulation modules that demonstrate modeling and analysis*Written by a team of experienced engineers and academics

Space-time modeling of atmospheric pollutants has been actively attempted by many workers, including Kyriakidis (1999) who successfully integrated the deterministic trend m(t) and the probabilistic residual R(t) components of a random variable RV Z(t) through a stochastic simulation approach. However, many of the spatiotemporal studies carried a major assumption that the temporal aspect is fully understood and thus focused primarily on spatial modeling. The main objective of this work is concerned with evaluating the accuracy and suitability of the techniques used for modeling the temporal phenomena. Various statistical methodologies, i.e., linear regression, kriging and stochastic simulation, were performed in the case of predicting tropospheric ozone concentrations in Calgary, Alberta for 1998-2000. It should be emphasized that the more accurate the temporal modeling is performed at various environmental monitoring stations, the higher the probability of success in estimating ozone values at unknown locations. Therefore, exhaustive studies of ozone phenomena must be carried out at as many cities in Canada as possible.