Random Field Models in Earth Sciences

This book is about modeling as a prinicipal component of scientific investigations. In general terms, modeling is the funamental process of combining intellectual creativity with physical knowledge and mathematical techniques in order to learn the properties of the mechanisms underlying a physical phenomenon and make predictions. The book focuses on a specific class of models, namely, random field models and certain of their physical applications in the context of a stochastic data analysis and processing research program. The term application is considered here in the sense wherein the mathematical random field model is shaping, but is also being shaped by, its objects.

@introbul:Key Features @bul:* This book explores the application of random field models and stochastic data processing to problems in hydrogeology, geostatistics, climate modeling, and oil reservoir engineering, among others Researchers in the geosciences who work with models of natural processes will find discussion of;

• Spatiotemporal random fields
• Space transformation
• Multidimensional estimation
• Simulation
• Sampling design
• Stochastic partial differential equations

Researchers in geostatistics, geology, mining engineering, hyrdrology, environmental and ocean engineering, and climate modeling.

Prolegomena. The Spatial Random Field Model. The Intrinsic Spatial Random Field Model. The Factorable Random Field Model. The Spatiotemporal Random Field Model. Space Transformations of Random Fields. Random Field Modeling of Natural Processes. Simulation of Natural Processes. Estimation in Space and Time. Sampling Design. References. Index.