Three-dimensional interference test interpretation in a fractured-unfractured aquifer using the pilot point inverse method

Lavenue, Marsh

doi:10.1029/2000wr900289

Cited by 7 publications

(7 citation statements)

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“…This is discussed at length in Carrera (this issue) and was the basis for the "Pilot Point" inverse approach (see e.g. Marsily 1978; Certes and Marsily 1991; Ramarao et al 1995;Lavenue et al 1995;Lavenue and Marsily 2001). 3.…”

Section: Stochastic Methods and Geostatisticsmentioning

confidence: 99%

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Dealing with spatial heterogeneity

et al. 2005

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Heterogeneity can be dealt with by defining homogeneous equivalent properties, known as averaging, or by trying to describe the spatial variability of the rock properties from geologic observations and local measurements. The techniques available for these descriptions are mostly continuous Geostatistical models, or discontinuous facies models such as the Boolean, Indicator or Gaussian-Threshold models and the Markov chain model. These facies models are better suited to treating issues of rock strata connectivity, e.g. buried high permeability channels or low permeability barriers, which greatly affect flow and, above all, transport in aquifers. Genetic models provide new ways to incorporate more geology into the facies description, an approach that has been well developed in the oil industry, but not enough in hydrogeology. The conclusion is that future work should be focused on improving the facies models, comparing them, and designing new in situ testing procedures (including geophysics) that would help identify the facies geometry and properties. A world-wide catalog of aquifer facies geometry and properties, which could combine site genesis and description with methods used to assess the system, would be of great value for practical applications.RØsumØ On peut aborder le problme de l'hØtØrogØnØitØ en s'efforçant de dØfinir une permØabilitØ Øquivalente homogne, par prise de moyenne, ou au contraire en dØ-crivant la variation dans l'espace des propriØtØs des roches à partir des observations gØologiques et des mesures locales. Les techniques disponibles pour une telle description sont soit continues, comme l'approche GØosta-tistique, soit discontinues, comme les modles de facis, BoolØens, ou bien par Indicatrices ou Gaussiennes SeuillØes, ou enfin Markoviens. Ces modles de facis sont mieux capables de prendre en compte la connectivitØ des strates gØologiques, telles que les chenaux enfouis à forte permØabilitØ, ou au contraire les facis fins de barrires de permØabilitØ, qui ont une influence importante sur les Øcoulement, et, plus encore, sur le transport. Les modles gØnØtiques rØcemment apparus ont la capacitØ de mieux incorporer dans les modles de facis les observations gØologiques, chose courante dans l'industrie pØ-trolire, mais insuffisamment dØveloppØe en hydrogØo-logie. On conclut que les travaux de recherche ultØrieurs devraient s'attacher à dØvelopper les modles de facis, à les comparer entre eux, et à mettre au point de nouvelles mØthodes d'essais in situ, comprenant les mØthodes gØo-physiques, capables de reconnaître la gØomØtrie et les propriØtØs des facis. La constitution d'un catalogue mondial de la gØomØtrie et des propriØtØs des facis aquifres, ainsi que des mØthodes de reconnaissance utilisØes pour arriver à la dØtermination de ces systmes, serait d'une grande importance pratique pour les applications.Resumen La heterogeneidad se puede manejar por medio de la definición de características homogØneas equivalentes, conocidas como promediar o tratando de describir la variabilidad espacia...

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Section: Stochastic Methods and Geostatisticsmentioning

confidence: 99%

“…The fine-tuning of the model would be made by calibration on experiments made on the site (pumping tests, see e.g. an example of 3-D interpretation of a pumping test with an inverse in Lavenue and Marsily 2001). Preliminary tracer tests would also be used to calibrate the model.…”

Section: Ignoring Heterogeneitymentioning

confidence: 99%

Dealing with spatial heterogeneity

et al. 2005

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“…Packers were placed in the seven boreholes for a series of sinusoidal pumping tests which were conducted at the upper and the lower zone of two boreholes, i.e., an oscillatory hydraulic tomographic survey (Cardiff et al, 2013). Lavenue and de Marsily (2001) then employed the pilot point inverse method and heterogeneous conceptual model to characterize the K field in the Culebra dolomite formation, using these data sets and available geologic facies data. Their characterization was limited to the horizontal variability of the formation, and suffered from the handicap of the pilot point method for tomographic surveys as discussed by Huang et al (2011).…”

Section: Introductionmentioning

confidence: 99%

What does hydraulic tomography tell us about fractured geological media? A field study and synthetic experiments

Zha

Illman

Tanaka

et al. 2015

Journal of Hydrology

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“…Methods of predictive uncertainty analysis include generalized likelihood uncertainty estimation (GLUE) [ Beven and Binley , 1992]; techniques that condition stochastic realizations using property measurements alone [ Deutsch and Journel , 1992; Gutjahr et al , 1994]; calibration‐constrained Monte Carlo, Markov‐Chain Monte Carlo (MCMC), and other methods that propagate prior stochastic parameter descriptions through the model to develop posterior parameter and prediction probabilities [ Kitanidis , 1996; Yeh et al , 1996; Oliver et al , 1997; Kuczera and Parent , 1998; Zimmerman et al , 1998; Woodbury and Ulrych , 2000; Carrera et al , 2005]; and methods based on stochastic equations that solve directly for posterior parameter and prediction probabilities [ Rubin and Dagan , 1987a, 1987b; Guadagnini and Neuman , 1999a, 1999b; Hernandez et al , 2006]. Non‐Bayesian methods, which deform stochastic parameter fields until a desired objective function is achieved, have been described by Lavenue and de Marsily [2001] and Gomez‐Hernandez et al [1997, 2003] among others.…”

Section: Introductionmentioning

confidence: 99%

Efficient nonlinear predictive error variance for highly parameterized models

Tonkin

Doherty²,

Moore

2007

Water Resources Research

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[1] Predictive error variance analysis attempts to determine how wrong predictions made by a calibrated model may be. Predictive error variance analysis is usually undertaken following calibration using a small number of parameters defined through a priori parsimony. In contrast, we introduce a method for investigating the potential error in predictions made by highly parameterized models calibrated using regularized inversion. Vecchia and Cooley (1987) describe a method of predictive error variance analysis that is constrained by calibration data. We extend this approach to include constraints on parameters that lie within the calibration null space. These constraints are determined by dividing parameter space into combinations of parameters for which estimates can be obtained and those for which they cannot. This enables the contribution to predictive error variance from parameterization simplifications required to solve the inverse problem to be quantified, in addition to the contribution from measurement noise. We also describe a novel technique that restricts the analysis to a strategically defined predictive solution subspace, enabling an approximate predictive error variance analysis to be completed efficiently. The method is illustrated using a synthetic and a real-world groundwater flow and transport model.

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Three-dimensional interference test interpretation in a fractured-unfractured aquifer using the pilot point inverse method

Cited by 7 publications

References 0 publications

Dealing with spatial heterogeneity

Dealing with spatial heterogeneity

What does hydraulic tomography tell us about fractured geological media? A field study and synthetic experiments

Efficient nonlinear predictive error variance for highly parameterized models

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