Statistic inversion of multi-zone transition probability models
for aquifer characterization in alluvial fans
L. Zhu, H. Gong
College of Resource Environment and Tourism, Capital Normal University,
Beijing Key Laboratory of Resource Environment and Geographic Information System, Beijing, China
Z. Dai
Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, USA
G. Guo
Beijing Institute of Hydrogeology and Engineering Geology, Beijing, China
P. Teatini
Dept. of Civil, Environmental and Architectural Engineering,
University of Padova, Padova, Italy
Alluvial fans are highly heterogeneous in hydraulic properties due to complex depositional processes,
which make it difficult to characterize the spatial distribution of the hydraulic conductivity
( K). An original methodology is developed to identify the spatial statistical parameters
(mean, variance, correlation range) of the hydraulic conductivity in a three-dimensional (3-D) setting
by using geological and geophysical data. More specifically, a large number
of inexpensive vertical electric soundings are integrated with a facies model developed from borehole
lithologic data to simulate the log10(iK) continuous distributions in
multiple-zone heterogeneous alluvial megafans. The Chaobai River
alluvial fan in the Beijing Plain, China, is used as an example to test the proposed approach.
Due to the non-stationary property of the K distribution in the alluvial fan, a multiple-zone
parameterization approach is applied to analyze the
conductivity statistical properties of different hydrofacies in
the various zones. The composite variance in each zone is
computed to describe the evolution of the conductivity along
the flow direction. Consistently with the scales of the sedimentary transport energy,
the results show that conductivity
variances of fine sand, medium-coarse sand, and gravel decrease from the upper (zone 1)
to the lower (zone 3) portion along the flow direction. In zone 1, sediments were
moved by higher-energy flooding, which induces poor sorting and larger conductivity variances.
The composite variance confirms this feature with statistically different facies
from zone 1 to zone 3. The results of this study provide insights to improve our understanding on
conductivity heterogeneity and a method for characterizing the spatial distribution of
K in alluvial fans.
