Statistic inversion of multi-zone transition probability models for aquifer characterization in alluvial fans

Zhu, Lin; Dai, Zhenxue; Gong, Huili; Gable, Carl; Teatini, Pietro

doi:10.1007/s00477-015-1089-2

Title: Statistic inversion of multi-zone transition probability models for aquifer characterization in alluvial fans

Journal Article · Fri Jun 12 00:00:00 EDT 2015 · Stochastic environmental research and risk assessment

DOI:https://doi.org/10.1007/s00477-015-1089-2· OSTI ID:1325631

Zhu, Lin ^[1]; Dai, Zhenxue ^[2]; Gong, Huili ^[3]; Gable, Carl ^[2]; Teatini, Pietro ^[4]

Capital Normal Univ., Beijing (China). College of Resources, Environment and Tourism. Lab. Cultivation Base of Environment Process and Digital Simulation; Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Earth and Environmental Sciences Division
Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Earth and Environmental Sciences Division
Capital Normal Univ., Beijing (China). College of Resources, Environment and Tourism. Lab. Cultivation Base of Environment Process and Digital Simulation
Univ. of Padua (Italy). Dept. of Civil, Environmental and Architectural Engineering

Understanding the heterogeneity arising from the complex architecture of sedimentary sequences in alluvial fans is challenging. This study develops a statistical inverse framework in a multi-zone transition probability approach for characterizing the heterogeneity in alluvial fans. An analytical solution of the transition probability matrix is used to define the statistical relationships among different hydrofacies and their mean lengths, integral scales, and volumetric proportions. A statistical inversion is conducted to identify the multi-zone transition probability models and estimate the optimal statistical parameters using the modified Gauss–Newton–Levenberg–Marquardt method. The Jacobian matrix is computed by the sensitivity equation method, which results in an accurate inverse solution with quantification of parameter uncertainty. We use the Chaobai River alluvial fan in the Beijing Plain, China, as an example for elucidating the methodology of alluvial fan characterization. The alluvial fan is divided into three sediment zones. In each zone, the explicit mathematical formulations of the transition probability models are constructed with optimized different integral scales and volumetric proportions. The hydrofacies distributions in the three zones are simulated sequentially by the multi-zone transition probability-based indicator simulations. Finally, the result of this study provides the heterogeneous structure of the alluvial fan for further study of flow and transport simulations.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Capital Normal Univ., Beijing (China)

Sponsoring Organization:: USDOE; National Natural Science Foundation of China (NSFC); Beijing Nova Program (China); Beijing Young Talent Program (China)

Contributing Organization:: Univ. of Padua (Italy)

Grant/Contract Number:: 41201420; 41130744; Z111106054511097

OSTI ID:: 1325631

Report Number(s):: LA-UR-15-20404

Journal Information:: Stochastic environmental research and risk assessment, Vol. 30, Issue 3; ISSN 1436-3240

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 22 works

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Modeling 3-D permeability distribution in alluvial fans using facies architecture and geophysical acquisitions Zhu, Lin; Gong, Huili; Dai, Zhenxue Hydrology and Earth System Sciences, Vol. 21, Issue 2 https://doi.org/10.5194/hess-21-721-2017	journal	January 2017

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54 ENVIRONMENTAL SCIENCES
environmental protection
multi-zone transition probability
alluvial fan
sediment heterogeneity
structure parameter uncertainty
statistic inversion
indicator simulation

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