Information content of slug tests for estimating hydraulic properties in realistic, high-conductivity aquifer scenarios

► Recently developed slug testing model is analyzed for parameter identifiability. ► Slug data cannot uniquely identify conductivity ( K) anisotropy or specific storage. ► 2500 slug tests characterize K variations at Boise Hydrogeophysical Research Site. ► Correlation and geostatistical analyses sho...

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Published inJournal of hydrology (Amsterdam) Vol. 403; no. 1; pp. 66 - 82
Main Authors Cardiff, Michael, Barrash, Warren, Thoma, Michael, Malama, Bwalya
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier B.V 06.06.2011
Elsevier
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ISSN0022-1694
1879-2707
DOI10.1016/j.jhydrol.2011.03.044

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Abstract ► Recently developed slug testing model is analyzed for parameter identifiability. ► Slug data cannot uniquely identify conductivity ( K) anisotropy or specific storage. ► 2500 slug tests characterize K variations at Boise Hydrogeophysical Research Site. ► Correlation and geostatistical analyses show high lateral K correlations at BHRS. ► K profiles do not correlate overall with porosity values from geophysical methods. A recently developed unified model for partially-penetrating slug tests in unconfined aquifers ( Malama et al., in press) provides a semi-analytical solution for aquifer response at the wellbore in the presence of inertial effects and wellbore skin, and is able to model the full range of responses from overdamped/monotonic to underdamped/oscillatory. While the model provides a unifying framework for realistically analyzing slug tests in aquifers (with the ultimate goal of determining aquifer properties such as hydraulic conductivity K and specific storage S s ), it is currently unclear whether parameters of this model can be well-identified without significant prior information and, thus, what degree of information content can be expected from such slug tests. In this paper, we examine the information content of slug tests in realistic field scenarios with respect to estimating aquifer properties, through analysis of both numerical experiments and field datasets. First, through numerical experiments using Markov Chain Monte Carlo methods for gauging parameter uncertainty and identifiability, we find that: (1) as noted by previous researchers, estimation of aquifer storage parameters using slug test data is highly unreliable and subject to significant uncertainty; (2) joint estimation of aquifer and skin parameters contributes to significant uncertainty in both unless prior knowledge is available; and (3) similarly, without prior information joint estimation of both aquifer radial and vertical conductivity may be unreliable. These results have significant implications for the types of information that must be collected prior to slug test analysis in order to obtain reliable aquifer parameter estimates. For example, plausible estimates of aquifer anisotropy ratios and bounds on wellbore skin K should be obtained, if possible, a priori. Secondly, through analysis of field data – consisting of over 2500 records from partially-penetrating slug tests in a heterogeneous, highly conductive aquifer, we present some general findings that have applicability to slug testing. In particular, we find that aquifer hydraulic conductivity estimates obtained from larger slug heights tend to be lower on average (presumably due to non-linear wellbore losses) and tend to be less variable (presumably due to averaging over larger support volumes), supporting the notion that using the smallest slug heights possible to produce measurable water level changes is an important strategy when mapping aquifer heterogeneity. Finally, we present results specific to characterization of the aquifer at the Boise Hydrogeophysical Research Site. Specifically, we note that (1) K estimates obtained using a range of different slug heights give similar results, generally within ±20%; (2) correlations between estimated K profiles with depth at closely-spaced wells suggest that K values obtained from slug tests are representative of actual aquifer heterogeneity and not overly affected by near-well media disturbance (i.e., “skin”); (3) geostatistical analysis of K values obtained indicates reasonable correlation lengths for sediments of this type; and (4) overall, K values obtained do not appear to correlate well with porosity data from previous studies.
AbstractList A recently developed unified model for partially-penetrating slug tests in unconfined aquifers (Malama et al., in press) provides a semi-analytical solution for aquifer response at the wellbore in the presence of inertial effects and wellbore skin, and is able to model the full range of responses from overdamped/monotonic to underdamped/oscillatory. While the model provides a unifying framework for realistically analyzing slug tests in aquifers (with the ultimate goal of determining aquifer properties such as hydraulic conductivity K and specific storage Ss), it is currently unclear whether parameters of this model can be well-identified without significant prior information and, thus, what degree of information content can be expected from such slug tests. In this paper, we examine the information content of slug tests in realistic field scenarios with respect to estimating aquifer properties, through analysis of both numerical experiments and field datasets.First, through numerical experiments using Markov Chain Monte Carlo methods for gauging parameter uncertainty and identifiability, we find that: (1) as noted by previous researchers, estimation of aquifer storage parameters using slug test data is highly unreliable and subject to significant uncertainty; (2) joint estimation of aquifer and skin parameters contributes to significant uncertainty in both unless prior knowledge is available; and (3) similarly, without prior information joint estimation of both aquifer radial and vertical conductivity may be unreliable. These results have significant implications for the types of information that must be collected prior to slug test analysis in order to obtain reliable aquifer parameter estimates. For example, plausible estimates of aquifer anisotropy ratios and bounds on wellbore skin K should be obtained, if possible, a priori.Secondly, through analysis of field data - consisting of over 2500 records from partially-penetrating slug tests in a heterogeneous, highly conductive aquifer, we present some general findings that have applicability to slug testing. In particular, we find that aquifer hydraulic conductivity estimates obtained from larger slug heights tend to be lower on average (presumably due to non-linear wellbore losses) and tend to be less variable (presumably due to averaging over larger support volumes), supporting the notion that using the smallest slug heights possible to produce measurable water level changes is an important strategy when mapping aquifer heterogeneity.Finally, we present results specific to characterization of the aquifer at the Boise Hydrogeophysical Research Site. Specifically, we note that (1) K estimates obtained using a range of different slug heights give similar results, generally within +/-20%; (2) correlations between estimated K profiles with depth at closely-spaced wells suggest that K values obtained from slug tests are representative of actual aquifer heterogeneity and not overly affected by near-well media disturbance (i.e., "skin"); (3) geostatistical analysis of K values obtained indicates reasonable correlation lengths for sediments of this type; and (4) overall, K values obtained do not appear to correlate well with porosity data from previous studies.
► Recently developed slug testing model is analyzed for parameter identifiability. ► Slug data cannot uniquely identify conductivity ( K) anisotropy or specific storage. ► 2500 slug tests characterize K variations at Boise Hydrogeophysical Research Site. ► Correlation and geostatistical analyses show high lateral K correlations at BHRS. ► K profiles do not correlate overall with porosity values from geophysical methods. A recently developed unified model for partially-penetrating slug tests in unconfined aquifers ( Malama et al., in press) provides a semi-analytical solution for aquifer response at the wellbore in the presence of inertial effects and wellbore skin, and is able to model the full range of responses from overdamped/monotonic to underdamped/oscillatory. While the model provides a unifying framework for realistically analyzing slug tests in aquifers (with the ultimate goal of determining aquifer properties such as hydraulic conductivity K and specific storage S s ), it is currently unclear whether parameters of this model can be well-identified without significant prior information and, thus, what degree of information content can be expected from such slug tests. In this paper, we examine the information content of slug tests in realistic field scenarios with respect to estimating aquifer properties, through analysis of both numerical experiments and field datasets. First, through numerical experiments using Markov Chain Monte Carlo methods for gauging parameter uncertainty and identifiability, we find that: (1) as noted by previous researchers, estimation of aquifer storage parameters using slug test data is highly unreliable and subject to significant uncertainty; (2) joint estimation of aquifer and skin parameters contributes to significant uncertainty in both unless prior knowledge is available; and (3) similarly, without prior information joint estimation of both aquifer radial and vertical conductivity may be unreliable. These results have significant implications for the types of information that must be collected prior to slug test analysis in order to obtain reliable aquifer parameter estimates. For example, plausible estimates of aquifer anisotropy ratios and bounds on wellbore skin K should be obtained, if possible, a priori. Secondly, through analysis of field data – consisting of over 2500 records from partially-penetrating slug tests in a heterogeneous, highly conductive aquifer, we present some general findings that have applicability to slug testing. In particular, we find that aquifer hydraulic conductivity estimates obtained from larger slug heights tend to be lower on average (presumably due to non-linear wellbore losses) and tend to be less variable (presumably due to averaging over larger support volumes), supporting the notion that using the smallest slug heights possible to produce measurable water level changes is an important strategy when mapping aquifer heterogeneity. Finally, we present results specific to characterization of the aquifer at the Boise Hydrogeophysical Research Site. Specifically, we note that (1) K estimates obtained using a range of different slug heights give similar results, generally within ±20%; (2) correlations between estimated K profiles with depth at closely-spaced wells suggest that K values obtained from slug tests are representative of actual aquifer heterogeneity and not overly affected by near-well media disturbance (i.e., “skin”); (3) geostatistical analysis of K values obtained indicates reasonable correlation lengths for sediments of this type; and (4) overall, K values obtained do not appear to correlate well with porosity data from previous studies.
A recently developed unified model for partially-penetrating slug tests in unconfined aquifers (Malama et al., in press) provides a semi-analytical solution for aquifer response at the wellbore in the presence of inertial effects and wellbore skin, and is able to model the full range of responses from overdamped/monotonic to underdamped/oscillatory. While the model provides a unifying framework for realistically analyzing slug tests in aquifers (with the ultimate goal of determining aquifer properties such as hydraulic conductivity K and specific storage Sₛ), it is currently unclear whether parameters of this model can be well-identified without significant prior information and, thus, what degree of information content can be expected from such slug tests. In this paper, we examine the information content of slug tests in realistic field scenarios with respect to estimating aquifer properties, through analysis of both numerical experiments and field datasets. First, through numerical experiments using Markov Chain Monte Carlo methods for gauging parameter uncertainty and identifiability, we find that: (1) as noted by previous researchers, estimation of aquifer storage parameters using slug test data is highly unreliable and subject to significant uncertainty; (2) joint estimation of aquifer and skin parameters contributes to significant uncertainty in both unless prior knowledge is available; and (3) similarly, without prior information joint estimation of both aquifer radial and vertical conductivity may be unreliable. These results have significant implications for the types of information that must be collected prior to slug test analysis in order to obtain reliable aquifer parameter estimates. For example, plausible estimates of aquifer anisotropy ratios and bounds on wellbore skin K should be obtained, if possible, a priori. Secondly, through analysis of field data – consisting of over 2500 records from partially-penetrating slug tests in a heterogeneous, highly conductive aquifer, we present some general findings that have applicability to slug testing. In particular, we find that aquifer hydraulic conductivity estimates obtained from larger slug heights tend to be lower on average (presumably due to non-linear wellbore losses) and tend to be less variable (presumably due to averaging over larger support volumes), supporting the notion that using the smallest slug heights possible to produce measurable water level changes is an important strategy when mapping aquifer heterogeneity. Finally, we present results specific to characterization of the aquifer at the Boise Hydrogeophysical Research Site. Specifically, we note that (1) K estimates obtained using a range of different slug heights give similar results, generally within ±20%; (2) correlations between estimated K profiles with depth at closely-spaced wells suggest that K values obtained from slug tests are representative of actual aquifer heterogeneity and not overly affected by near-well media disturbance (i.e., “skin”); (3) geostatistical analysis of K values obtained indicates reasonable correlation lengths for sediments of this type; and (4) overall, K values obtained do not appear to correlate well with porosity data from previous studies.
Author Cardiff, Michael
Thoma, Michael
Barrash, Warren
Malama, Bwalya
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  organization: Montana Tech of the Univ. of Montana, Dept. of Geological Engineering, 1300 West Park Street, Butte, MT 59701, USA
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Issue 1
Keywords Identifiability
Kozeny–Carman
Slug test
Wellbore skin
Aquifer characterization
Markov chain analysis
experimental studies
Monte Carlo analysis
joints
anisotropy
ground water
hydraulic conductivity
hydraulics
water storage
aquifers
solution
Kozeny-Carman
uncertainties
models
porosity
testing
heterogeneity
depth
correlation
unconfined aquifers
strategy
gauging
Language English
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Snippet ► Recently developed slug testing model is analyzed for parameter identifiability. ► Slug data cannot uniquely identify conductivity ( K) anisotropy or...
A recently developed unified model for partially-penetrating slug tests in unconfined aquifers (Malama et al., in press) provides a semi-analytical solution...
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StartPage 66
SubjectTerms Aquifer characterization
Aquifers
Correlation analysis
Earth sciences
Earth, ocean, space
Estimates
Exact sciences and technology
field experimentation
Fluid flow
hydraulic conductivity
Hydraulics
Hydrology. Hydrogeology
Identifiability
Kozeny–Carman
Mathematical models
Monte Carlo method
parameter uncertainty
porosity
researchers
sediments
Slug test
Slugs
Uncertainty
Wellbore skin
wells
Title Information content of slug tests for estimating hydraulic properties in realistic, high-conductivity aquifer scenarios
URI https://dx.doi.org/10.1016/j.jhydrol.2011.03.044
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https://www.proquest.com/docview/876231886
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