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Combining rock physics and sedimentology for seismic reservoir characterization of North Sea turbidite systems

Posted on:2001-08-20Degree:Ph.DType:Dissertation
University:Stanford UniversityCandidate:Avseth, Per AgeFull Text:PDF
GTID:1460390014455265Subject:Geophysics
Abstract/Summary:
The petroleum industry is increasing its focus on the exploration of reservoirs in turbidite systems. However, these sedimentary environments are often characterized by very complex sand distributions. Hence, reservoir description based on conventional seismic and well-log interpretation may be very uncertain. There is a need to employ more quantitative seismic techniques to reveal reservoirs units in these complex systems from seismic amplitude data.; In this study we focus on North Sea turbidite systems. Our goal is to improve the ability to use 3D seismic data to map reservoirs in these systems. A cross-disciplinary methodology for seismic reservoir characterization is presented that combines rock physics, sedimentology, and statistical techniques. We apply this methodology to two turbidite systems of Paleocene age located in the South Viking Graben of the North Sea.; First, we investigate the relationship between sedimentary petrography and rock physics properties. Next, we define seismic scale sedimentary units, referred to as seismic lithofacies. These facies represent populations of data that have characteristic geologic and seismic properties. We establish a statistically representative training database by identifying seismic lithofacies from thin-sections, cores, and well-log data. This procedure is guided by diagnostic rock physics modeling. Based on the training data, we perform multivariate classification of data from several wells in the area. Next, we assess uncertainties in amplitude versus offset (AVO) response related to the inherent natural variability of each seismic lithofacies. We generate bivariate probability density functions (pdfs) of two AVO parameters for different facies combinations. By combining the bivariate pdfs estimated from well-logs with the AVO parameters estimated from seismic data, we use both quadratic discriminant analysis and Bayesian classification to predict lithofacies and pore fluids from seismic amplitudes. The final results are spatial maps of the most likely facies, and their occurrence probabilities. These maps can be used as input data for well log planning and risk analysis in hydrocarbon exploration and reservoir development.
Keywords/Search Tags:Reservoir, Turbidite systems, Seismic, Rock physics, North sea, Data
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