Stochastic Modeling and Statistical Inference of Geological Fault Populations and Patterns
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The focus of this work is on faults, and the main issue is statistical analysis and stochastic modeling of faults and fault patterns in petroleum reservoirs. The thesis consists of Part I-V and Appendix A-C. The units can be read independently. Part III is written for a geophysical audience, and the topic of this part is fault and fracture size-frequency distributions. The remaining parts are written for a statistical audience, but can also be read by people with an interest in quantitative geology. The topic of Part I and II is statistical model choice for fault size distributions, with a samling algorithm for estimating Bayes factor. Part IV describes work on spatial modeling of fault geometry, and Part V is a short note on line partitioning. Part I, II and III constitute the main part of the thesis. The appendices are conference abstracts and papers based on Part I and IV.
Består avBorgos, HG. Model choice for fault size distributions. .
Borgos, HG. Sampling algorithm for estimating Bayes factor. .
Borgos, HG; Cowie, PA; Dawers, NH. Practicalities of extrapolating one-dimensional fault and fracture size-frequency distributions to higher-dimensional samples. J. Geophys. Res.. 105(B12): 377-392, 2000.
Borgos, HG. Stochastic model for fault geometry conditioned to seismic data and well observations. .
Borgos, HG. Partitioning of a line segment. .
Borgos, Hilde Grude; Omre, H. Model chice for fault distribution. .
Borgos, HG. Stochastic simulation of fault patterns conditioned on seismic data and well data. .
Borgos, HG; Omre, H. Uncertainty in fault geometries. .