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Borghi, Andrea
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Borghi, Andrea
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- PublicationAccès libreMissing data simulation inside flow rate time-series using multiple-point statistics(2016-10)
; ; ; ; The direct sampling (DS) multiple-point statistical technique is proposed as a non-parametric missing data simulator for hydrological flow rate time-series. The algorithm makes use of the patterns contained inside a training data set to reproduce the complexity of the missing data. The proposed setup is tested in the reconstruction of a flow rate time-series while considering several missing data scenarios, as well as a comparative test against a time-series model of type ARMAX. The results show that DS generates more realistic simulations than ARMAX, better recovering the statistical content of the missing data. The predictive power of both techniques is much increased when a correlated flow rate time-series is used, but DS can also use incomplete auxiliary time-series, with a comparable prediction power. This makes the technique a handy simulation tool for practitioners dealing with incomplete data sets. - PublicationAccès libreCan one identify karst conduit networks geometry and properties from hydraulic and tracer test data?(2016)
; ; Karst aquifers are characterized by extreme heterogeneity due to the presence of karst conduits embedded in a fractured matrix having a much lower hydraulic conductivity. The resulting contrast in the physical properties of the system implies that the system reacts very rapidly to some changes in the boundary conditions and that numerical models are extremely sensitive to small modifications in properties or positions of the conduits. Furthermore, one major issue in all those models is that the location and size of the conduits is generally unknown. For all those reasons, estimating karst network geometry and their properties by solving an inverse problem is a particularly difficult problem.
In this paper, two numerical experiments are described. In the first one, 18,000 flow and transport simulations have been computed and used in a systematic manner to assess statistically if one can retrieve the parameters of a model (geometry and radius of the conduits, hydraulic conductivity of the conduits) from head and tracer data. When two tracer test data sets are available, the solution of the inverse problems indicate with high certainty that there are indeed two conduits and not more. The radius of the conduits are usually well identified but not the properties of the matrix. If more conduits are present in the system, but only two tracer test data sets are available, the inverse problem is still able to identify the true solution as the most probable but it also indicates that the data are insufficient to conclude with high certainty.
In the second experiment, a more complex model (including non linear flow equations in conduits) is considered. In this example, gradient-based optimization techniques are proved to be efficient for estimating the radius of the conduits and the hydraulic conductivity of the matrix in a promising and efficient manner.
These results suggest that, despite the numerical difficulties, inverse methods should be used to constrain numerical models of karstic systems using flow and transport data. They also suggest that a pragmatic approach for these complex systems could be to generate a large set of karst conduit network realizations using a pseudo-genetic approach such as SKS, and for each karst realization, flow and transport parameters could be optimized using a gradient-based search such as the one implemented in PEST. - PublicationAccès libreGeneration of 3D Spatially Variable Anisotropy for Groundwater Flow Simulations(2015)
; ; Courrioux, GabrielSedimentary units generally present anisotropy in their hydraulic properties, with higher hydraulic conductivity along bedding planes, rather than perpendicular to them. This common property leads to a modeling challenge if the sedimentary structure is folded. In this paper, we show that the gradient of the geological potential used by implicit geological modeling techniques can be used to compute full hydraulic conductivity tensors varying in space according to the geological orientation. For that purpose, the gradient of the potential, a vector normal to the bedding, is used to construct a rotation matrix that allows the estimation of the 3D hydraulic conductivity tensor in a single matrix operation. A synthetic 2D cross section example is used to illustrate the method and show that flow simulations performed in such a folded environment are highly influenced by this rotating anisotropy. When using the proposed method, the streamlines follow very closely the folded formation. This is not the case with an isotropic model. - PublicationAccès libreStochastic fracture generation accounting for the stratification orientation in a folded environment based on an implicit geological model(2015)
; ; - PublicationAccès libreA method for the stochastic modeling of karstic systems accounting for geophysical data: an example of application in the region of Tulum, Yucatan Peninsula (Mexico)(2013-1-10)
; ; - PublicationAccès libreA pseudo-genetic stochastic model to generate karstic networks(2012)
; ; Jenni, SandraIn this paper, we present a methodology for the stochastic simulation of 3D karstic conduits accounting for conceptual knowledge about the speleogenesis processes and accounting for a wide variety of field measurements.
The methodology consists of four main steps. First, a 3D geological model of the region is built. The second step consists in the stochastic modeling of the internal heterogeneity of the karst formations (e.g. initial fracturation, bedding planes, inception horizons, etc.). Then a study of the regional hydrology/hydrogeology is conducted to identify the potential inlets and outlets of the system, the base levels and the possibility of having different phases of karstification. The last step consists in generating the conduits in an iterative manner using a fast marching algorithm. In most of these steps, a probabilistic model can be used to represent the degree of knowledge available and the remaining uncertainty depending on the data at hand.
The conduits are assumed to follow minimum effort paths in a heterogeneous medium from sinkholes or dolines toward springs. The search of the shortest path is performed using a fast marching algorithm. This process can be iterative, allowing to account for the presence of already simulated conduits and to produce a hierarchical network.
The final result is a stochastic ensemble of 3D karst reservoir models that are all constrained by the regional geology, the local heterogeneities and the regional flow conditions. These networks can then be used to simulate flow and transport. Several levels of uncertainty can be considered (large scale geological structures, local heterogeneity, position of possible inlets and outlets, phases of karstification).
Compared to other techniques, this method is fast, to account for the main factors controlling the 3D geometry of the network, and to allow conditioning from available field observations.