Tuesday, April 26, 2016
Confluence Ballroom Foyer (The Westin Denver Downtown)
Amir Niazi
,
University of Calgary, Calgary, AB, Canada
Laurence Bentley
,
University of Calgary, Calgary, AB, Canada
Masaki Hayashi, Ph.D.
,
University of Calgary, Calgary, AB, Canada
Geostatistical simulation is a powerful tool to explore the uncertainty associated with heterogeneity in groundwater and reservoir studies. Nonetheless, conditioning simulations merely with lithological information does not utilize all of the available information and so some workers additionally condition simulations with flow data.
In this study, we introduce an approach to condition geostatistical simulations of the Paskapoo Formation, which is a paleo-fluvial system consisting of sandstone channels embedded in mudstone. The conditioning data consist of two-hour single well pumping tests extracted from the public water well database in Alberta, Canada.
In this approach, lithologic models of an entire watershed are simulated and conditioned with hard lithological data using transition probability geostatistics (TPROGS). Then, a segment of the simulation around a pumping well was used to populate a flow model (FEFLOW) with either sand or mudstone. The values of the hydraulic conductivity and specific storage of sand and mudstone were then adjusted to minimize the difference between simulated and actual pumping test data using the parameter estimation program PEST. If the simulated data do not adequately match the measured data, the lithologic model is updated by locally deforming the lithology distribution using the probability perturbation method (PPM) and the model parameters are again updated with PEST. This procedure is repeated until the simulated and measured data agree within a pre-determined tolerance. The procedure is repeated for each pumping well that has pumping test data.
The method constrains the lithological simulations and provides estimates of hydraulic conductivity and specific storage that are consistent with the pumping test data. Eventually, the simulations will be combined in watershed scale groundwater models
Amir Niazi, University of Calgary, Calgary, AB, Canada
I am PhD. Candidate at university of Calgary. I received my Master in Isfahan University of technology, Iran with focus of Irrigation and drainage engineering, after working several years in industry, I received my second master in integrated water resources management from McGill university. My area of research is stochastic modelling of groundwater.
Laurence Bentley, University of Calgary, Calgary, AB, Canada
TBA
Masaki Hayashi, Ph.D., University of Calgary, Calgary, AB, Canada
Masaki Hayashi, Ph.D., is a professor in the Department of Geoscience at the University of Calgary. He holds the Canada Research Chair in Physical Hydrology. Hayashi received his B.S. and M.S. in earth sciences from Waseda University and Chiba University, respectively, in Japan, and his Ph.D. in earth sciences from the University of Waterloo in Canada. His main research interests are in the connection among groundwater, surface water, and atmospheric moisture in various environments ranging from the prairies to the mountains.
