On the Performance of Pilot‐Point Based Hydraulic Tomography with a Geophysical a Priori Model

Poduri, Sarada; Kambhammettu, B.V.N.P.

doi:10.1111/gwat.13053

Cited by 9 publications

(4 citation statements)

References 63 publications

(101 reference statements)

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“…We observed a poor performance of inversion in delineating K and S tomograms, when model initialization is performed with a uniform ( K eff = 10 −3 cm/s, S eff = 8 × 10 −4 /cm) parameter set throughout the domain. This clearly highlights the need for a prori information of model parameters from various approaches such as: single‐hole test datasets (Berg and Illman 2015), geological model (Illman 2014; H. Zhao et al 2021), geophysical test datasets (Poduri and Kambhammettu 2020).…”

Section: Resultsmentioning

confidence: 99%

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Performance of Gradient and Gradient‐Free Optimizers in Transient Hydraulic Tomography

Chintala,

Kambhammettu,

Harmya

2023

Groundwater

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Sub‐surface characterization in fractured aquifers is challenging due to the co‐existence of contrasting materials namely matrix and fractures. Transient hydraulic tomography (THT) is proved to be an efficient and robust technique to estimate hydraulic (Km, Kf) and storage (Sm, Sf) properties in such complex hydrogeologic settings. However, performance of THT is governed by data quality and optimization technique used in inversion. We assessed the performance of gradient and gradient‐free optimizers with THT inversion. Laboratory experiments were performed on a two‐dimensional, granite rock (80 cm x 45 cm x 5 cm) with known fracture pattern. Cross‐hole pumping experiments were conducted at 10 ports (located on fractures), and time‐drawdown responses were monitored at 25 ports (located on matrix and fractures). Pumping ports were ranked based on weighted signal‐to‐noise ratio (SNR) computed at each observation port. Noise‐free, good quality (SNR > 100) datasets were inverted using Levenberg Marquardt: LM (gradient) and Nelder Mead: NM (gradient‐free) methods. All simulations were performed using a coupled simulation‐optimization model. Performance of the two optimizers is evaluated by comparing model predictions with observations made at two validation ports that were not used in simulation. Both LM and NM algorithms have broadly captured the preferential flow paths (fracture network) via K and S tomograms, however LM has outperformed NM during validation () Our results conclude that, while method of optimization has a trivial effect on model predictions, exclusion of low quality (SNR ≤ 100) datasets can significantly improve the model performance.This article is protected by copyright. All rights reserved.

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Section: Resultsmentioning

confidence: 99%

“…This clearly highlights the need for a prori information of model parameters from various approaches such as: single-hole test datasets (Berg and Illman 2015), geological model (Illman 2014;H. Zhao et al 2021), geophysical test datasets (Poduri and Kambhammettu 2020).…”

Section: Scenario 2: Considering All Pumping Test Datasetsmentioning

confidence: 99%

Performance of Gradient and Gradient‐Free Optimizers in Transient Hydraulic Tomography

Chintala,

Kambhammettu,

Harmya

2023

Groundwater

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“…The first category revolves around groundwater modeling and parameter evaluation. For instance, methodologies like the Continuous Linear Estimation (SLE) algorithm [30,31], the Steady Shape Inversion method [32], and the pilot-point method [33,34] are utilized in parameter evaluation.…”

Section: Introductionmentioning

confidence: 99%

Hydraulic Travel Time Diagnosis Using Recovery Data from Short-Term Pumping Tests for Rapid Aquifer Characterization: A Numerical Study with Monte-Carlo Simulations

Qi,

Hu,

et al. 2024

Water

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In the realm of groundwater science, characterization of heterogeneous aquifers is pivotal for resolving diverse groundwater resource and engineering-related problems that require the detailed spatial distribution of hydraulic parameters. As research progresses, one hydraulic tomographical method, which is based on hydraulic travel time inversion, emerges as a promising and rapid method due to its robust and efficient calculation. In the field, the acquisition of hydraulic excitation and head observation data required for inversion is less time-consuming. Data collection from a single hydraulic test (such as a pumping test) typically takes only a few minutes or even a few tens of seconds. However, the field application of this method faces challenges. Hydraulic travel time is typically generated in the early stages of hydrogeological tests (e.g., early drawdown of a pumping test), yet accurate data may not be readily available because of the noise signals from test equipment, which can contaminate travel time signals, leading to inaccurate inversion results. A potential solution lies in utilizing the smooth head observation during the recovery period after the pump is turned off, which yields more accurate travel times for inversion calculations. In this paper, the mathematical development suggests that the travel time of the recovery phase aligns with that of the pumping phase when pumping reaches a steady or quasi-steady state. Subsequently, by employing Monte-Carlo simulations, 1200 realizations of two-dimensional heterogeneous confined aquifer models were generated for simulating pumping tests with different pumping durations. The calculated head data were then utilized to compute the travel time derived from drawdown data (t) and recovery data (t′), respectively. Comparisons showed that t is equal to t′ when drawdown reaches a steady or quasi-steady state. Conversely, when the pump is turned off before reaching a quasi-steady state, t differs from t′. However, results also indicate the fact that a decent hydraulic travel time diagnosis can be obtained, especially for the cases when travel times are smaller than 15 s. Given the statistical results of Monte-Carlo simulations, as well as experience during pumping tests in the field with different scenarios, using the recovery data from 60 s of pumping duration, or extended pumping durations of 100 s or 200 s as a more conservative alternative, can replace the aquifer characterization based on drawdown data. The new inversion strategy not only has less data uncertainty and equivalent inversion accuracy, but also can greatly enhance the repeatability of field tests and reduce the environmental impact of long-term pumping tests.

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“…These observations have been important limitations in the technique. Nonetheless, the pilot‐point method with some constraints in parameter values has been successfully implemented in the last decade by several researchers (Castagna and Bellin 2009; Fienen et al 2009; Castagna et al 2011; Jimenez et al 2013; Poduri and Kambhammettu 2020). These methods differ largely in terms of the distribution of pilot points and the constraints imposed on the parameter ranges.…”

Section: Introductionmentioning

confidence: 99%

A New Randomized Binary Prior Model for Hydraulic Tomography in Fractured Aquifers

2021

Self Cite

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We present a novel pilot-point-based hydraulic tomography (HT) inversion procedure to delineate preferential flow paths and estimate hydraulic properties in a fractured aquifer. Our procedure considers a binary prior model developed using a randomized algorithm. The randomized algorithm involves discretizing the domain into grid cells, assigning a binary label to each cell, traversing the grid randomly, and choosing the optimal grid configuration cell-by-cell. This binary prior model is used to guide the placement of pilot points and to constrain aquifer parameters during pilot-point-based HT inversion. A two-dimensional fractured granite rock block was considered to test our methodology under controlled laboratory conditions. Multiple pumping tests were conducted at selected ports and the pressure responses were monitored. The pumping datasets thus obtained were preprocessed using median filters to remove random noise, and then analyzed using the proposed procedure. The proposed binary prior algorithm was implemented in C++ by supplying the forward groundwater model, HydroGeoSphere (HGS). Pilot-point-assisted HT inversion was performed using the parameter-estimation tool, coupled to HGS. The resulting parameter distributions were assessed by: (1) a visual comparison of the K-and S s -tomograms with the known topology of the fractures and (2) comparing model predictions with measurements made at two validation ports that were not used in calibration. The performance assessment revealed that HT with the proposed randomized binary prior could be used to recover fracture-connectivity and to predict drawdowns in fractured aquifers with reasonable accuracy, when compared to a conventional pilot-point inversion scheme.

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On the Performance of Pilot‐Point Based Hydraulic Tomography with a Geophysical a Priori Model

Cited by 9 publications

References 63 publications

Performance of Gradient and Gradient‐Free Optimizers in Transient Hydraulic Tomography

Performance of Gradient and Gradient‐Free Optimizers in Transient Hydraulic Tomography

Hydraulic Travel Time Diagnosis Using Recovery Data from Short-Term Pumping Tests for Rapid Aquifer Characterization: A Numerical Study with Monte-Carlo Simulations

A New Randomized Binary Prior Model for Hydraulic Tomography in Fractured Aquifers

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