scholarly journals Transient Hydraulic Tomography Analysis of Fourteen Pumping Tests at a Highly Heterogeneous Multiple Aquifer–Aquitard System

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1864
Author(s):  
Zhanfeng Zhao ◽  
Walter A. Illman ◽  
Yuanyuan Zha ◽  
Tian-Chyi Jim Yeh ◽  
Chin Man Bill Mok ◽  
...  
Keyword(s):  
Additional Data ◽  
Joint Inversion ◽  
Pumping Test ◽  
Observation Data ◽  
Data Types ◽  
Specific Storage ◽  
Pumping Tests ◽  
Hydraulic Tomography ◽  
Low K ◽  
Tomography Analysis

Hydraulic tomography based on geostatistics has proven to be robust in characterizing subsurface heterogeneity in hydraulic conductivity (K) and specific storage (Ss) through the joint inversion of drawdown records from multiple pumping tests. However, the spatially variable estimates can be smooth or even erroneous for areas where pumping/observation data densities are not high. Previous hydraulic tomography surveys conducted at the North Campus Research Site (NCRS) on the University of Waterloo campus in Waterloo, Canada, revealed that the estimated hydraulic parameters were smooth and the known aquitard was erroneously identified as a high K zone. This was likely the consequence of the site being highly heterogeneous, while only utilizing four pumping tests and not having measurable drawdowns in the low K aquitard for inverse modeling. Here, we investigate whether improved K and Ss estimates could be obtained through the inclusion of additional pumping test data by stressing both aquifer and aquitard zones for a sufficiently long period. Specifically, six additional pumping/injection tests were conducted at the site, and a transient hydraulic tomography analysis with 14 tests was completed. Results reveal that there is a significant improvement to the K and Ss tomograms in terms of the visual correspondence with various geologic units, including its connectivity. More importantly, with the availability of additional data, we found that the inverse model now can better capture the high and low K features for nine boreholes when compared with K values obtained from permeameter tests. The estimated K and Ss tomograms are then used for the forward simulation of one additional pumping test not used for model calibration, revealing reasonable predictions. While encouraging results are obtained by including a large number of pumping tests to the transient hydraulic tomography analysis, stratigraphic boundaries are still smoothed, which is a direct consequence of utilizing a geostatistics-based inversion approach that assumes stationarity in statistical properties. To capture such sharp boundaries, incorporation of additional data types, such as geological and geophysical information, may be necessary when data densities are not sufficiently high.

scholarly journals Estimation of heterogeneous aquifer parameters using centralized and decentralized fusion of hydraulic tomography data

2014 ◽  
Vol 18 (8) ◽  
pp. 3207-3223 ◽  
Author(s):  
A. H. Alzraiee ◽  
D. Baú ◽  
A. Elhaddad
Keyword(s):  
Pumping Test ◽  
Hydraulic Head ◽  
Impulse Response Functions ◽  
Specific Storage ◽  
Pumping Tests ◽  
Hydraulic Tomography ◽  
Temporal Moment ◽  
Groundwater Systems ◽  
Transient Data ◽  
Temporal Moments

Abstract. Characterization of spatial variability of hydraulic properties of groundwater systems at high resolution is essential to simulate flow and transport phenomena. This paper investigates two schemes to invert transient hydraulic head data resulting from multiple pumping tests for the purpose of estimating the spatial distributions of the hydraulic conductivity, K, and the specific storage, Ss, of an aquifer. The two methods are centralized fusion and decentralized fusion. The centralized fusion of transient data is achieved when data from all pumping tests are processed concurrently using a central inversion processor, whereas the decentralized fusion inverts data from each pumping test separately to obtain optimal local estimates of hydraulic parameters, which are consequently fused using the generalized Millman formula, an algorithm for merging multiple correlated or uncorrelated local estimates. For both data fusion schemes, the basic inversion processor employed is the ensemble Kalman filter, which is employed to assimilate the temporal moments of impulse response functions obtained from the transient hydraulic head measurements resulting from multiple pumping tests. Assimilating the temporal moments instead of the hydraulic head transient data themselves is shown to provide a significant improvement in computational efficiency. Additionally, different assimilation strategies to improve the estimation of Ss are investigated. Results show that estimation of the K and Ss distributions using temporal moment analysis is fairly good, and the centralized inversion scheme consistently outperforms the decentralized inversion scheme.

scholarly journals Estimation of heterogeneous aquifer parameters using centralized and decentralized fusion of hydraulic tomography data from multiple pumping tests

2014 ◽  
Vol 11 (4) ◽  
pp. 4163-4208 ◽  
Author(s):  
A. H. Alzraiee ◽  
D. Baú ◽  
A. Elhaddad
Keyword(s):  
Correlation Length ◽  
Hydraulic Properties ◽  
Pumping Test ◽  
Hydraulic Head ◽  
Specific Storage ◽  
Pumping Tests ◽  
Hydraulic Tomography ◽  
Temporal Moment ◽  
Transient Data ◽  
Temporal Moments

Abstract. Characterization of spatial variability of hydraulic properties of groundwater systems at high resolution is essential to simulate flow and transport phenomena. This paper investigates two schemes to invert transient hydraulic head data resulting from multiple pumping tests for the purpose of estimating the spatial distributions of the hydraulic conductivity, K, and the specific storage, Ss, of an aquifer. The two methods are centralized fusion and decentralized fusion. The centralized fusion of transient data is achieved when data from all pumping tests are processed concurrently using a central inversion processor, whereas the decentralized fusion inverts data from each pumping test separately to obtain optimal local estimates of hydraulic parameter, which are consequently fused using the Generalized Millman Formula, an algorithm for merging multiple correlated or uncorrelated local estimates. For both data fusion schemes, the basic inversion processor employed is the Ensemble Kalman Filter, which is employed to assimilate the temporal moments of the transient hydraulic head measurements resulting from multiple pumping tests. Assimilating the temporal moments instead of the hydraulic head transient data themselves is shown to provide a significant improvement in computational efficiency. Additionally, different assimilation strategies to improve the estimation of Ss are investigated. Results show that estimation of the K and Ss distributions using temporal moment analysis is fairly good; however, the centralized inversion scheme consistently outperforms the decentralized inversion scheme. Investigations on the sensitivity of the inversion estimates to errors in geostatistical parameters of the random fields of K and Ss reveal that the estimates are not sensitive to errors in the correlation length and the variance of hydraulic properties, but are noticeably sensitive to errors in the stationary mean. The proposed inversion schemes are expanded to estimate the geostatistical parameters of the K and Ss fields. The results show that the estimation of the true stationary mean of the K field and, to a lesser degree, the stationary mean of the Ss field can be successfully achieved, while the estimation of correlation length and standard deviation for both the K and Ss fields are not as effective.

Hydraulic tomography using joint inversion of head and flux data 

2021 ◽  
Author(s):  
Behzad Pouladiborj ◽  
Olivier Bour ◽  
Niklas Linde ◽  
Laurent Longuevergne
Keyword(s):  
Hydraulic Conductivity ◽  
Joint Inversion ◽  
Data Type ◽  
Data Types ◽  
Hydraulic Tomography ◽  
Flux Data ◽  
Planning And Design ◽  
Constant Rate ◽  
Resolution Analysis ◽  
Constant Head

<p>Hydraulic tomography is a state of the art method for inferring hydraulic conductivity fields using head data. Here, a numerical model is used to simulate a steady-state hydraulic tomography experiment by assuming a Gaussian hydraulic conductivity field (also constant storativity) and generating the head and flux data in different observation points. We employed geostatistical inversion using head and flux data individually and jointly to better understand the relative merits of each data type. For the typical case of a small number of observation points, we find that flux data provide a better resolved hydraulic conductivity field compared to head data when considering data with similar signal-to-noise ratios. In the case of a high number of observation points, we find the estimated fields to be of similar quality regardless of the data type. A resolution analysis for a small number of observations reveals that head data averages over a broader region than flux data, and flux data can better resolve the hydraulic conductivity field than head data. The inversions' performance depends on borehole boundary conditions, with the best performing setting for flux data and head data are constant head and constant rate, respectively. However, the joint inversion results of both data types are insensitive to the borehole boundary type. Considering the same number of observations, the joint inversion of head and flux data does not offer advantages over individual inversions. By increasing the hydraulic conductivity field variance, we find that the resulting increased non-linearity makes it more challenging to recover high-quality estimates of the reference hydraulic conductivity field. Our findings would be useful for future planning and design of hydraulic tomography tests comprising the flux and head data.</p>

Utilizing time-lapse hydraulic tomography to characterize the subsurface changes during methane and heat injection experiments

2020 ◽  
Author(s):  
Linwei Hu ◽  
Márk Somogyvári ◽  
Sebastian Bauer
Keyword(s):  
Hydraulic Conductivity ◽  
Thermal Water ◽  
Water Injection ◽  
Time Lapse ◽  
Hot Water ◽  
Heterogeneous Structure ◽  
Specific Storage ◽  
Pumping Tests ◽  
Hydraulic Diffusivity ◽  
Hydraulic Tomography

<p>Storage options for the energy storage in the subsurface includes the injection and storage of the “energy gas” (e.g., methane, hydrogen, compressed air) or thermal water into the underground formations. The heterogeneous structure of the storage formations could play a crucial role on the potential storage capacity, as well as the formulation of post treatment strategy. Hence, innovative techniques are required for characterizing the high-resolution formation heterogeneity and monitoring the gas or heat plume distribution in the subsurface after their injections.  Previous studies have shown that flow properties can vary as the gas or thermal water being injected into the aquifer. In this study, we propose a time-lapse hydraulic tomography (HT) method for characterizing the baseline hydraulic information and depicting the hydraulic property changes through a series of cross-well pumping tests. These tests were implemented in two pilot sites for methane and hot water injection tests at Wittstock, Germany. In order to generate a three-dimensional tomographical configuration, each pumping test was conducted at certain depth in a testing well, accompanying with multiple observation points at other wells. Depth-variant pumping and observation segments were formed by the double-packer system. As a result, we achieved 198 and 135 baseline drawdown curves for the methane and heat sites, respectively. For these measured data, we initially evaluated the effective hydraulic conductivity and specific storage of the aquifer according to certain analytical fitting methods. Furthermore, the vertical anisotropy of the hydraulic conductivity was also estimated. Sequentially, the fitted hydraulic parameters and analytical drawdown curves were utilized for correcting the well skin effects on hydraulic traveltimes and attenuations, as they have an unneglectable impact on them.  The corrected hydraulic traveltimes and attenuations were used for the inversion of the baseline hydraulic diffusivity and specific storage, respectively. Hydraulic conductivity distribution was then estimated through these two parameters. After we achieved the baseline information, HT was executed again by repeating the tomographical pumping tests after methane and hot water injections. The same data processing and inversion techniques were applied to the drawdown curves derived from the post-injection period. Inverted hydraulic diffusivity, specific storage, and hydraulic conductivity were compared to the baseline inversion results. Changes on these hydraulic properties could provide the information of the spatial distribution of methane or heat plume.</p>

scholarly journals Hydraulic and Groundwater Chemical Parameters of the Aquifer in Malakasari, Bandung

2018 ◽  
Vol 147 ◽  
pp. 03007
Author(s):  
Jemi S. Ahnaf ◽  
Zufialdi Zakaria ◽  
Aton Patonah
Keyword(s):  
Hydraulic Properties ◽  
Sedimentary Rocks ◽  
Pumping Test ◽  
Coarse Sand ◽  
Observation Data ◽  
Chemical Parameters ◽  
Specific Storage ◽  
Chemical Parameter ◽  
Total Dissolved Solid ◽  
Feasibility Test

In order to reveal the physical condition of the aquifer, the pumping test using Cooper-Jacob (1946) principle has conducted at well SM5. The observation data of the test then processed to generate various value of hydraulic properties i.e. 3.241x10-4 cm2/sec for transmissivity (T), 8.103x10-6 cm/sec for conductivity (K), 0.05055 for storativity (S), and 3.852x10-3 ft-1 for specific storage (Ss). These data show that the aquifer composed of unconsolidated sedimentary rocks ranged from coarse sand to silt. In addition, also performed the feasibility test of groundwater by using Multimeter which produces chemical parameter data. The chemical parameter of eight well samples have average values of 6.62, 766.25 μs/cm and 376.25 mg/L for pH, electric conductivity (EC), and total dissolved solid (TDS) respectively, while physical observation shows no turbidity and odor.

scholarly journals Technical note: Analytical drawdown solution for steady-state pumping tests in two-dimensional isotropic heterogeneous aquifers

2016 ◽  
Vol 20 (5) ◽  
pp. 1655-1667 ◽  
Author(s):  
Alraune Zech ◽  
Sabine Attinger
Keyword(s):  
Steady State ◽  
Correlation Length ◽  
Heterogeneous Media ◽  
Radial Distance ◽  
Pumping Test ◽  
Two Dimensional ◽  
Aquifer Heterogeneity ◽  
Pumping Tests ◽  
Flow Solution ◽  
Ensemble Mean

Abstract. A new method is presented which allows interpreting steady-state pumping tests in heterogeneous isotropic transmissivity fields. In contrast to mean uniform flow, pumping test drawdowns in heterogeneous media cannot be described by a single effective or equivalent value of hydraulic transmissivity. An effective description of transmissivity is required, being a function of the radial distance to the well and including the parameters of log-transmissivity: mean, variance, and correlation length. Such a model is provided by the upscaling procedure radial coarse graining, which describes the transition of near-well to far-field transmissivity effectively. Based on this approach, an analytical solution for a steady-state pumping test drawdown is deduced. The so-called effective well flow solution is derived for two cases: the ensemble mean of pumping tests and the drawdown within an individual heterogeneous transmissivity field. The analytical form of the solution allows inversely estimating the parameters of aquifer heterogeneity. For comparison with the effective well flow solution, virtual pumping tests are performed and analysed for both cases, the ensemble mean drawdown and pumping tests at individual transmissivity fields. Interpretation of ensemble mean drawdowns showed proof of the upscaling method. The effective well flow solution reproduces the drawdown for two-dimensional pumping tests in heterogeneous media in contrast to Thiem's solution for homogeneous media. Multiple pumping tests conducted at different locations within an individual transmissivity field are analysed, making use of the effective well flow solution to show that all statistical parameters of aquifer heterogeneity can be inferred under field conditions. Thus, the presented method is a promising tool with which to estimate parameters of aquifer heterogeneity, in particular variance and horizontal correlation length of log-transmissivity fields from steady-state pumping test measurements.

scholarly journals Machine Learning Methods for Improved Understanding of a Pumping Test in Heterogeneous Aquifers

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1342 ◽  
Author(s):  
Yong Fan ◽  
Litang Hu ◽  
Hongliang Wang ◽  
Xin Liu
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Time Series Analysis ◽  
Analytical Solutions ◽  
Pumping Test ◽  
Learning Methods ◽  
Pumping Tests ◽  
Machine Learning Methods ◽  
Series Analysis ◽  
Pumping Wells

Pumping tests are very important means for investigating aquifer properties; however, interpreting the data using common analytical solutions become invalid in complex aquifer systems. The paper aims to explore the potential of machine learning methods in retrieving the pumping tests information in a field site in the Democratic Republic of Congo. A newly planned mining site with a pumping test of three pumping wells and 28 observation wells over one month was chosen to analyze the significance of machine learning methods in the pumping test analysis. Widely used machine learning methods, including correlation, cluster, time-series analysis, artificial neural network (ANN), support vector machine (SVR), random forest (RF) method, and linear regression, are all used in this study. Correlation and cluster analyses among wells provide visual pictures of possible hydraulic connections. The pathway with the best permeability ranges from the depth of 250 m to 350 m. Time-series analysis perfectly captured changes of drawdowns within the three pumping wells. The RF method is found to have the higher accuracy and the lower sensitivity to model parameters than ANN and SVR methods. The coupling of the linear regressive model and analytical solutions is applied to estimate hydraulic conductivities. The results found that ML methods can significantly and effectively improve our understanding of pumping tests by revealing inherent information hidden in those tests.

Geophysics introduces new section on multiphysics and joint inversion

2020 ◽  
Vol 39 (10) ◽  
pp. 753-754
Author(s):  
Jiajia Sun ◽  
Daniele Colombo ◽  
Yaoguo Li ◽  
Jeffrey Shragge
Keyword(s):  
Big Data ◽  
Joint Inversion ◽  
Effective Means ◽  
Added Value ◽  
Data Sets ◽  
Computational Power ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Data Types ◽  
Geoscientific Data

Geophysicists seek to extract useful and potentially actionable information about the subsurface by interpreting various types of geophysical data together with prior geologic information. It is well recognized that reliable imaging, characterization, and monitoring of subsurface systems require integration of multiple sources of information from a multitude of geoscientific data sets. With increasing data volumes and computational power, new data types, constant development of inversion algorithms, and the advent of the big data era, Geophysics editors see multiphysics integration as an effective means of meeting some of the challenges arising from imaging subsurface systems with higher resolution and reliability as well as exploring geologically more complicated areas. To advance the field of multiphysics integration and to showcase its added value, Geophysics will introduce a new section “Multiphysics and Joint Inversion” in 2021. Submissions are accepted now.

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