Abstract

Water–rock interaction in surface and subsurface environments occurs in complex multicomponent systems and involves several reactions, including element transfer. Such kinetic information is obtained by fitting a forward model into the temporal evolution of solution chemistry or the spatial pattern recorded in the rock samples, although geochemical and petrological data are essentially sparse and noisy. Therefore, the optimization of kinetic parameters sometimes fails to converge toward the global minimum due to being trapped in a local minimum. In this study, we simultaneously present a novel framework to estimate multiple reaction-rate constants and the diffusivity of aqueous species from the mineral distribution pattern in a rock by using the reactive transport model coupled with the exchange Monte Carlo method. Our approach can estimate both the maximum likelihood and error of each parameter. We applied the method to the synthetic data, which were produced using a model for silica metasomatism and hydration in the olivine–quartz–H2O system. We tested the robustness and accuracy of our method over a wide range of noise intensities. This methodology can be widely applied to kinetic analyses of various kinds of water–rock interactions.

Highlights

  • The reactive transport model is an essential tool to understand the changes in physical, chemical, and hydrological properties of surface and subsurface environments during water–rock interaction, including weathering, hydrothermal alteration, and metasomatism [1,2,3]

  • The validity and prediction performance of the reactive transport model highly depend on the accuracy of kinetic parameters, such as the dissolution/precipitation rate constants of minerals and the diffusivity of aqueous species, as well as reactive surface areas of the minerals

  • We present a novel method to estimate multiple reaction-rate constants, and the diffusivity of aqueous species using only the dataset of spatial mineral distribution, and by combining the reactive transport model and the exchange Monte Carlo (EMC) method [26,27,28]

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Summary

Introduction

The reactive transport model is an essential tool to understand the changes in physical, chemical, and hydrological properties of surface and subsurface environments during water–rock interaction, including weathering, hydrothermal alteration, and metasomatism [1,2,3]. Multiple parameterizations from a coupled transport and reaction system, pertaining to the dissolution and precipitation of many minerals and the transport of aqueous species (ions and complexes), raise a difficult geochemical inverse problem due to computational difficulties This is especially true when multiple parameters are to be estimated; estimation sometimes fails to converge to the global minima due to convergence to the local minima through error minimization [24,25]. We present a novel method to estimate multiple reaction-rate constants, and the diffusivity of aqueous species using only the dataset of spatial mineral distribution, and by combining the reactive transport model and the exchange Monte Carlo (EMC) method [26,27,28]. Using our kinetics-based and data-driven approach, we derived several rate constants for surface reactions, and the diffusivity of aqueous species of primary and secondary minerals was estimated from noisy, observed abundance data

General Framework
Model System
Schematic
Kinetic Forward Model
Synthetic Datasets
Synthetic
Extraction
Dependence of Estimation
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