A Short‐Term Pumping Strategy for Hydraulic Tomography Based on the Successive Linear Estimator

Hou, Xiaolan; Hu, Rui; Yeh, Tian‐Chyi Jim; Li, Yukun; Qi, Junjie; Song, Yang; Qiu, Huiyang

doi:10.1029/2022wr033831

Cited by 6 publications

(8 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, only the first 100 s of the signals were evaluated within the inversion. This early time span is the most dynamic part of the response and contains almost all necessary information about the subsurface hydraulic parameters (e.g., Hou et al., 2023). Also, using the complete signal for the inversion procedure would significantly increase the computational cost.…”

Section: Methodsmentioning

confidence: 99%

Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured‐Porous Field Site

Römhild,

Ringel,

Liu

et al. 2024

Water Resources Research

View full text Add to dashboard Cite

The accurate characterization of hydraulic conductivity heterogeneities in an aquifer is crucial for predicting flow and transport processes correctly. Hydraulic tomography (HT) experiments are often used to infer the hydraulically relevant features, but the correct inversion of the data remains a challenging task. We implemented a discrete fracture network (DFN) inversion approach that is expanded by considering a nonzero matrix permeability. The hybrid model allows the accurate characterization of fractured‐porous sites by taking into account both matrix and fracture flow. This novel inversion algorithm is successfully applied to HT data acquired at a field site in Goettingen (Germany), and the results are compared with those of a standard travel time inversion. Furthermore, we validate the inversion results by using them as the underlying material parameters for simulating heat tracer experiments and comparing the modeled temperature responses with those of heat tracer tests actually conducted at the site. It is shown that the DFN ensemble predicts the thermal response of the experiments correctly for the two major fractures in terms of location, amplitude, and time‐dependent behavior of the temperature anomaly, as long as the stochastic nature of the results is taken into account. We conclude that considering both matrix and fracture flow in a hybrid DFN inversion approach can lead to significant improvements in flow and transport modeling at fractured‐porous sites.

show abstract

Section: Methodsmentioning

confidence: 99%

Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured‐Porous Field Site

Römhild,

Ringel,

Liu

et al. 2024

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…The kriging superposition approach (KSA) was used in this study 37,38 . The first step is based on the kriging method to estimate the parameters of each unknown point across the reservoir using the reservoir's accurate permeability data, which can be obtained by assuming that the number of sampling points i is n :

\begin{equation} \mathop \sum \limits_j {\lambda }_{0i}C\left( {{x}_i,{x}_i} \right) = C\left( {{x}_i,{x}_m} \right)\end{equation}

…”

Section: Methodsmentioning

confidence: 99%

Reciprocal cross‐correlation analysis of two‐phase seepage processes and reservoir heterogeneities in CO₂ saline aquifer sequestration

Zhong,

Li,

et al. 2024

Greenhouse Gases

Self Cite

View full text Add to dashboard Cite

When CO2 saline aquifer storage is carried out, the heterogeneity of reservoir rock is an important factor affecting CO2 transport, and the reservoir heterogeneity in numerical simulations is mainly manifested as the heterogeneity of the parameter field. Since the parameter distributions across the reservoir are not available with the existing probes, the stochastic finite element method is combined with a two‐phase flow model to establish an unconditional random field of permeability, and computations are performed using the Monte Carlo method. The permeability, CO2 maximum migration distance (Md) and CO2 sweep area (Sa) were analyzed for mutual correlation. The permeability correlation area affecting Md and Sa was obtained, and the changes in the correlation area under the coefficient of variation (Cv) and correlation length (λx) of the permeability field in the different reservoirs were analyzed. The kriging superposition approach (KSA) was subsequently used to estimate both the Md and Sa of the target reservoir by establishing conditional random fields based on the sampling parameters in regions with different correlations, resulting in errors of 0.66% for Md and 0.96% for Sa in the high correlation region and 4.86% and 3.12% for Md and Sa in the low correlation region, which suggested that the sampling results from the high correlation region were less biased in the estimation. Under limited sampling conditions, it is recommended that samples be collected in regions with high correlations to reduce the uncertainty of CO2 transport analysis due to unknown heterogeneity. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

show abstract

“…A joint probability distribution is then used to describe the likelihood of a specific realization occurring. Because geological deposition processes may lead to spatial correlations between parameters at different locations, the joint probability distribution needs to consider an autocorrelation function, along with mean and variance [44,45].…”

Section: Monte-carlo Simulationsmentioning

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

Self Cite

View full text Add to dashboard Cite

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.

show abstract

A Short‐Term Pumping Strategy for Hydraulic Tomography Based on the Successive Linear Estimator

Cited by 6 publications

References 54 publications

Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured‐Porous Field Site

Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured‐Porous Field Site

Reciprocal cross‐correlation analysis of two‐phase seepage processes and reservoir heterogeneities in CO₂ saline aquifer sequestration

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

Contact Info

Product

Resources

About

A Short‐Term Pumping Strategy for Hydraulic Tomography Based on the Successive Linear Estimator

Cited by 6 publications

References 54 publications

Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured‐Porous Field Site

Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured‐Porous Field Site

Reciprocal cross‐correlation analysis of two‐phase seepage processes and reservoir heterogeneities in CO2 saline aquifer sequestration

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

Contact Info

Product

Resources

About

Reciprocal cross‐correlation analysis of two‐phase seepage processes and reservoir heterogeneities in CO₂ saline aquifer sequestration