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Reservoir modeling today combines the empirical conceptual ideas developed by geologists over the past 300 years with the rigor of formal statistical analysis to capture the uncertainty inherent in predicting reservoir properties in the inter-well space. In particular, this volume addresses the application of geostatistical methods that have emerged over...
Reservoir modeling today combines the empirical conceptual ideas developed by geologists over the past 300 years with the rigor of formal statistical analysis to capture the uncertainty inherent in predicting reservoir properties in the inter-well space. In particular, this volume addresses the application of geostatistical methods that have emerged over the past two decades and are now found embedded in petroleum reservoir characterization and simulation software. The popularity of this specialized statistics for spatially related data has occurred because of its ability to successfully analyze and integrate different types of data, provide meaningful results for model building, and quantitatively assess uncertainty for risk management. Additionally, this modeling approach is applicable to both geoscientists and engineers thereby lending itself to the concept of a shared earth model and a multidisciplinary workforce. However, the technology is not intuitive and has been implemented at a pace that has left many geoscientists and engineers wanting. This book is designed for front-line modelers who want to better understand the fundamentals of spatial statistics and their application to reservoir modeling. It describes the five basic steps and their important methodologies necessary to creating reliable reservoir models; exploratory data analysis, spatial modeling, modeling of key reservoir properties including facies and petrophysics, uncertainty assessment, and preparation for flow simulation.
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