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Avon, France

Chihi H.,University of Carthage | Jeannee N.,Geovariances | Yahyaoui H.,Regional Commissary for Agricultural Development of Medenine | Belayouni H.,Tunis el Manar University | Bedir M.,University of Carthage
Desalination and Water Treatment | Year: 2014

This study attempts to characterize the organization, geometry and continuity of aquifer systems in a faulted setting, by geostatistical methods. It concerns the "Jeffara de Medenine" aquifers, in South-Eastern Tunisia. The quality of architectural reservoir modelling depends heavily on available data and on the fault network at the origin of its compartmentalization. In our case study, the available data consist mainly of boreholes: (i) usually sparse: the data distribution and density are very uneven within the study area, depending on the aquifers and the river network; (ii) they do not, usually penetrate the entire aquifer formation. Therefore, aquifers situated at a great depth remain unattainable for many drillings, leaving large areas under-informed and (iii) they are supplemented by seismic data which, although of variable quality, provide useful information for building the fault network at a large scale. To deal with this lack of data, an original geostatistical approach is applied in order to make the best use of the available data: (i) borehole data corresponding to the geological interfaces: these are exact data (equal to) and (ii) information provided by the end of drilling; these are uncertain data using inequalities (less than, greater than, between). The estimation of the Turonian reservoir top (taken as an example in this study) may indeed be constrained by the exact and inequality well values, thus avoiding some inconsistencies during interpolation by kriging under inequality constraints. Fault parameters are also explicitly incorporated in the interpolation procedure. This geostatistical approach is used for depth estimation within the "Jeffara de Medenine" aquifer system and is compared to classical kriging and evaluated through the quality of estimation, the adopted assumptions and method limitations. Thus, estimation procedures can be improved to build geometric models that describe as well as possible the geological reality. © 2013 Balaban Desalination Publications. All rights reserved. Source

Chautru J.M.,Geovariances
Petroleum Geostatistics 2015 | Year: 2015

There are several ways for integrating different sources of data in mapping processes: Multivariate estimations (cokriging, collocated cokriging) which require the fitting of a multivariate model (variograms and cross-variograms) and a stationary context; Kriging with external drift or kriging with Bayesian drift, which can be applied in non-stationary contexts and requires a univariate model. This paper proposes another approach which is based on the definition of additional data, well distributed over the area of interest, which define upper and lower envelopes for the map to be drawn. These envelopes are built from auxiliary data and will be considered as soft data of less accuracy than hard data. The approach is based on the combination of two geostatistical methods that are quite rarely used, conditional expectation with inequalities and kriging with measurement error. After a brief reminder of the methods, some applications in geological modelling are proposed: Control of extrapolation Mapping of geological horizons using the full trace of horizontal wells Integration of geophysical data of varying accuracy in mapping at regional scale Mapping layer tops in layer-cake models. Source

Birgand F.,North Carolina State University | Faucheux C.,Geovariances | Gruau G.,French National Center for Scientific Research | Augeard B.,IRSTEA | And 2 more authors.
Transactions of the ASABE | Year: 2010

The objectives of this study are to evaluate the uncertainty in annual nitrate loads and concentrations (such as annual average and median concentrations) as induced by infrequent sampling and by the algorithms used to compute fluxes. A total of 50 watershed-years of hourly to daily flow and concentration data gathered from nine watersheds (5 to 252 km 2) in Brittany, France, were analyzed. Original (high frequency) nitrate concentration and flow data were numerically sampled to simulate common sampling frequencies. Annual fluxes and concentration indicators calculated from the simulated samples were compared to the reference values calculated from the high-frequency data. The uncertainties contributed by several algorithms used to calculate annual fluxes were also quantified. In all cases, uncertainty increased as sampling intervals increased. Results showed that all the tested algorithms that do not use continuous flow data to compute nitrate fluxes introduced considerable uncertainty. The flow-weighted average concentration ratio method was found to perform best across the 50 annual datasets. Analysis of the bias values suggests that the 90th and 95th percentiles and the maximum concentration values tend to be systematically underestimated in the long term, but the load estimates (using the chosen algorithm) and the average and median concentrations were relatively unbiased. Great variability in the precision of the load estimation algorithms was observed, both between watersheds of different sizes and between years for a particular watershed. This has prevented definitive uncertainty predictions for nitrate loads and concentrations in this preliminary work, but suggests that hydrologic factors, such as the watershed hydrological reactivity, could be a key factor in predicting uncertainty levels. © 2010 American Society of Agricultural and Biological Engineers ISSN 2151-0032. Source

Bertoli O.,Geovariances Pty Ltd | Paul A.,BHP Billiton | Casley Z.,Geovariances | Dunn D.,BHP Billiton
International Journal of Coal Geology | Year: 2013

Geostatistical drill hole spacing analysis ('DHSA') for resource classification using the global estimation variance technique has been used across BHP Billiton Mitsubishi Alliance ('BMA') Coal Operation's various mines and projects since 2004. Analysis of the results points to the emergence of possible patterns in the results for projects pertaining to specific coal measures being mined by BMA. This correlation may be a useful guide to assist in developing resource classifications for projects based on the coal measures in which they occur. Comparison of the results of classification using the Coal Guidelines versus classification using the geostatistical DHSA method for a selection of BMA's operating mines in Queensland's Bowen Basin indicates that the non-geostatistical approach leads to level of uncertainty that does not always agree with the complexity of the geology. © 2013 Elsevier B.V. Source

Pernet F.,French Research Institute for Exploitation of the Sea | Pernet F.,IRD Montpellier | Lagarde F.,French Research Institute for Exploitation of the Sea | Jeanne N.,Geovariances | And 5 more authors.
PLoS ONE | Year: 2014

Although spatial studies of diseases on land have a long history, far fewer have been made on aquatic diseases. Here, we present the first large-scale, high-resolution spatial and temporal representation of a mass mortality phenomenon cause by the Ostreid herpesvirus (OsHV-1) that has affected oysters (Crassostrea gigas) every year since 2008, in relation to their energetic reserves and the quality of their food. Disease mortality was investigated in healthy oysters deployed at 106 locations in the Thau Mediterranean lagoon before the start of the epizootic in spring 2011. We found that disease mortality of oysters showed strong spatial dependence clearly reflecting the epizootic process of local transmission. Disease initiated inside oyster farms spread rapidly beyond these areas. Local differences in energetic condition of oysters, partly driven by variation in food quality, played a significant role in the spatial and temporal dynamics of disease mortality. In particular, the relative contribution of diatoms to the diet of oysters was positively correlated with their energetic reserves, which in turn decreased the risk of disease mortality. © 2014 Pernet et al. Source

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