A lithofacies approach for modeling non‐<scp>F</scp>ickian solute transport in a heterogeneous alluvial aquifer

Bianchi, Marco; Chen, Kewei

doi:10.1002/2015wr018186

Cited by 56 publications

(85 citation statements)

References 67 publications

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“…This skewness value not only qualitatively agrees with the anomalous transport conditions observed at this site, it also suggests that such conditions may be mainly the effect of the low geological entropy of the aquifer. This is consistent with the presence of connected structures and organized features as suggested by several previous studies [ Dogan et al ., ; Bianchi and Zheng , ; Zheng et al ., , and references therein].…”

Section: Results and Analysismentioning

confidence: 99%

“…The real and synthetic aquifers used for generating the second set of validation data include: the aquifer at the MADE site [ Zheng et al ., ], as per the lithological model presented by Bianchi and Zheng []; the aquifer at the Lawrence Livermore National Laboratory (LLNL P18), as per the statistical parameters of the hydrofacies models presented by Fogg et al . [], LaBolle and Fogg [], and Zhang et al .…”

Section: Results and Analysismentioning

confidence: 99%

“…Therefore, the K fields considered here are mapped on the basis of stochastic realizations of the spatial distribution of hydrofacies generated with a transition probability/Markov Chain approach [ Carle and Fogg , ]. With this approach, the K structure of the aquifer is consistent with the geological and sedimentological setting [e.g., Fogg , ; Anderson , ; Allen‐King et al ., ; Fogg et al ., ; Riva et al ., ; Zhang et al ., ; Bianchi and Zheng , ].…”

Section: Introductionmentioning

confidence: 99%

“…We consider several testing scenarios with different level of K heterogeneity and spatial disorder including five scenarios that mimic the conditions of real alluvial aquifers known in the literature [ LaBolle and Fogg , ; Zhang et al ., ; Bianchi and Zheng , ; Terrenghi et al ., ]. Based on analysis of the ensemble of results obtained from the numerical experiment, our goal is to prove that simple closed‐form expressions could be derived to relate ( H R ,

σ_{Y}^{2}

) pairs to metrics describing transport behavior in different settings of aquifer heterogeneity.…”

Section: Introductionmentioning

confidence: 99%

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Geological entropy and solute transport in heterogeneous porous media

Bianchi

Pedretti

2017

Water Resources Research

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We propose a novel approach to link solute transport behavior to the physical heterogeneity of the aquifer, which we fully characterize with two measurable parameters: the variance of the log K values (r 2 Y), and a new indicator (H R) that integrates multiple properties of the K field into a global measure of spatial disorder or geological entropy. From the results of a detailed numerical experiment considering solute transport in K fields representing realistic distributions of hydrofacies in alluvial aquifers, we identify empirical relationship between the two parameters and the first three central moments of the distributions of arrival times of solute particles at a selected control plane. The analysis of experimental data indicates that the mean and the variance of the solutes arrival times tend to increase with spatial disorder (i.e., H R increasing), while highly skewed distributions are observed in more orderly structures (i.e., H R decreasing) or at higher r 2 Y. We found that simple closed-form empirical expressions of the bivariate dependency of skewness on H R and r 2 Y can be used to predict the emergence of non-Fickian transport in K fields considering a range of structures and heterogeneity levels, some of which based on documented real aquifers. The accuracy of these predictions and in general the results from this study indicate that a description of the global variability and structure of the K field in terms of variance and geological entropy offers a valid and broadly applicable approach for the interpretation and prediction of transport in heterogeneous porous media.

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Section: Results and Analysismentioning

confidence: 99%

Section: Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

σ_{Y}^{2}

) pairs to metrics describing transport behavior in different settings of aquifer heterogeneity.…”

Section: Introductionmentioning

confidence: 99%

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Geological entropy and solute transport in heterogeneous porous media

Bianchi

Pedretti

2017

Water Resources Research

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“…However, because the scale of heterogeneity of alluvial lithofacies can be much finer than typical inter-borehole spacing [1][2][3][4][5], understanding how K varies in space from sparse hydraulic tests is inherently impractical. Alternatively, when numerous continuous-core boreholes are available, one can resort to geostatistics for simulating lithofacies at first step, and then obtain the K-field by assigning appropriate K to simulated lithofacies [6][7][8][9]. Geostatistics deals with prediction of any property (including discrete variables such as, for example, lithofacies) exhibiting some degree of spatial continuity [10].…”

Section: Introductionmentioning

confidence: 99%

Three Geostatistical Methods for Hydrofacies Simulation Ranked Using a Large Borehole Lithology Dataset from the Venice Hinterland (NE Italy)

Marini

Felletti

Beretta

et al. 2018

Water

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Abstract:A large borehole lithology dataset from the shallowly buried alluvial aquifer of the Brenta River Megafan (NE Italy) is used in this paper to model hydrofacies with three classical geostatistical methods, namely the Object-Based Simulation (OBS), the Sequential Indicator Simulation (SIS), and the Truncated Gaussian Simulation (TGS), and rank alternative output models. Results show that, though compromising with geological realism and rendering a noisy picture of subsurface geology, the pixel-based TGS and SIS are better suited than OBS for their ease of conditioning to closely spaced boreholes, especially in fine-scale simulation grids. In turn, SIS appears to provide better prediction and less noisy hydrofacies models than TGS without requiring assumptions about relationship among operative facies, which makes it particularly suited for use with large borehole lithology datasets lacking detail and quality consistency. Flow simulation on a test volume constrained with numerous boreholes indicates the SIS hydrofacies models feature well-connected sands forming relatively fast flow paths as opposed to TGS models, which instead appear to carry a more dispersed flow. It is shown how such a difference primarily relates to 'noise', which in TGS models is so widespread to translate into a disordered spatial distribution of K and, consequently, a nearly isotropic simulated flow.

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Reassessing the MADE direct‐push hydraulic conductivity data using a revised calibration procedure

Bohling

Dietrich

Butler

2016

Water Resources Research

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In earlier work, we presented a geostatistical assessment of high‐resolution hydraulic conductivity (K) profiles obtained at the MADE site using direct‐push (DP) methods. The profiles are derived from direct‐push injection logger (DPIL) measurements that provide a relative indicator of vertical variations in K with a sample spacing of 1.5 cm. The DPIL profiles are converted to K profiles by calibrating to the results of direct‐push permeameter (DPP) tests performed at selected depths in some of the profiles. Our original calibration used a linear transform that failed to adequately account for an upper limit on DPIL responses in high‐K zones and noise in the DPIL data. Here we present a revised calibration procedure that accounts for the upper limit and noise, leading to DPIL K values that display a somewhat different univariate distribution and a lower lnK variance (5.9 ± 1.5) than the original calibration values (6.9 ± 1.8), although each variance estimate falls within the other's 95% confidence interval. Despite the change in the univariate distribution, the autocorrelation structure and large‐scale patterns exhibited by the revised DPIL K values still agree well with those exhibited by the flowmeter data from the site. We provide the DPIL and DPP data, along with our calibrated DPIL K values, in the Supporting Information.

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A lithofacies approach for modeling non‐Fickian solute transport in a heterogeneous alluvial aquifer

Cited by 56 publications

References 67 publications

Geological entropy and solute transport in heterogeneous porous media

Geological entropy and solute transport in heterogeneous porous media

Three Geostatistical Methods for Hydrofacies Simulation Ranked Using a Large Borehole Lithology Dataset from the Venice Hinterland (NE Italy)

Reassessing the MADE direct‐push hydraulic conductivity data using a revised calibration procedure

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