[en] The modeling of fracture networks is useful for fluid flow and rock mechanics studies. About 6600 fracture traces were recorded on drifts of a uranium mine in a granite massif. The traces have an extension of 0.20-20 m. The network was studied by fractal and by geostatistical methods but can be considered neither as a fractal with a constant dimension nor a set of purely randomly located fractures. Two kinds of generalization of conventional models can still provide more flexibility for the characterization of the network: (a) a nonscaling fractal model with variable similarity dimension (for a 2-D network of traces, the dimension varying from 2 for the 10-m scale to 1 for the centimeter scale, (b) a parent-daughter model with a regionalized density; the geostatistical study allows a 3-D model to be established where: fractures are assumed to be discs; fractures are grouped in clusters or swarms; and fracturation density is regionalized (with two ranges at about 30 and 300 m). The fractal model is easy to fit and to simulate along a line, but 2-D and 3-D simulations are more difficult. The geostatistical model is more complex, but easy to simulate, even in 3-D

[en] Fluid-flow studies of fractured rocks require a three-dimensional modeling of the fracture network. Because the complexity of reality does not allow a complete description of the actual network, it is therefore necessary to use Monte-Carlo models. Various basic models can be used depending on the situation: random infinite fractures (planes), random finite fractures (polygons or discs), and locally self-similar fractal networks. Other models of easy simulation can be derived by mixing, clustering, and regionalizing the parameters. These models are reviewed. Emphasis is placed on the determination of the parameters by means of morphological, statistical, geostatistical, and fractal tools that can be used with one-dimensional data (boreholes) or two-dimensional data (outcrops and drift walls). The last section explains how to condition a three-dimensional simulation on the data

[en] This paper describes some new techniques for stochastic modeling of three-dimensional fracture networks. We use geostatistical simulation methods to reproduce features of the spatial structure of the rock such as the variation of fracture density and fracture orientation in space. For an example of the method we use mapped fracture data from the Fanay-Augeres mine, in Limousin, France. Two different sections of a drift wall, S1 and S2, were mapped. The S1 section is wet, and the S2 section is dry. For each case, the fractures are divided into five different sets and each set is modeled separately. The fractures in each set are represented as discs placed randomly in space. The diameter of each disc is chosen independently from a fixed probability distribution determined from the trace length distribution. For the location of discs a point process called the parent-daughter process is used. This process gives a clumping or swarming of fractures not found in the usual Poisson model. The orientation of the discs is characterized as a fluctuation about the mean orientation for the set. This fluctuation has a spatial structure that is simulated with geostatistics. Geostatistical simulations of the two fracture systems are under way. The connectivities of the simulations will be assessed to see if there is any correlation with the fact that the S1 section of drift is wet and the S2 section is dry

[en] The main objective of this study is to quantitatively assess the geothermal potential of deep Triassic clastic reservoirs in the Paris Basin, through an updated characterization of the composition of the argillaceous formations, temperature and geometry. These formations are located at depths with high temperatures (>60 deg. C) which can reach 125 deg. C. In addition to heat production, such temperatures could be used to generate electricity via a binary cycle. To achieve our objective, four successive stages were carried out: Stage 1 - Selection of 5 deep clastic reservoirs. These clay-sandstone reservoirs are located in the Triassic, in the deep parts of the Paris Basin, and for some of them under the currently exploited Dogger zones. Step 2 - Compilation of public data extracted from oil drilling logs, geothermal drilling logs (5 sites) and reservoir geometry maps recently produced by IFP to characterize the geometry and temperature of the five selected reservoirs. Step 3 - Production of depth (isohypse), thickness (isopaque) and temperature maps for each of the selected reservoirs, based on existing IFP maps, litho-stratigraphic knowledge of the Triassic and interpolation of temperature data extracted from oil and geothermal drilling. Step 4 - Quantitative assessment of the geothermal potential (= exploitable heat) of each of the selected clastic reservoirs by combining geometric and thermal data, on a regional scale and with a particular focus on the Dogger geothermal exploitation zones in the Ile de France region. This report is divided into three main sections: - the first part presents the Triassic geology of the Paris Basin, followed by a detailed description of the five selected clastic reservoirs; - the second part describes the methodology adopted to produce depth (isohypse), thickness (isopaque) and temperature maps for each of the selected clastic reservoirs; - the third and final section describes the geometric (thickness and depth) and thermal parameters of the five reservoirs, and ultimately analyzes their respective geothermal potential. In conclusion, perspectives for the Paris Basin component of the CLASTIQ project are proposed

[en] Within the framework of a study of granite fracturing, and more particularly of the characterisation of surface fractures or while using sounding data, by focussing on the analysis of geometrical properties of fractures at different scales, by studying the organisation of the first fracture networks and their reactivation at different stages of the granite geological history, a first report tries to examine fracturing sequences on several crystalline massifs in order to assess their impact on the geometric properties of fracture networks. The second document reports studies performed within the framework of the Welltest project which aimed at more precisely defining a methodology of water test interpretation in order to better identify the fracture network structure and its hydraulic characteristics. Thus, after a recall of the main factors influencing flows in a granite fractured environment, a definition of some typical cases of fracture network geometric organisation, it reports geometrical simulation of typical networks

[en] The Boom Clay is currently investigated as potential host formation for the deep disposal of high-level and/or long-lived radioactive waste in Belgium. Deep disposal safety relies on multiple barriers: the 'super-container' containing the vitrified waste, the repository itself and the host formation in which the disposal could be constructed. The latter is the most important as it is the one that has to slow the migration of radionuclides towards the biosphere for a sufficiently long time when the man-made barriers are no longer effective. So it is the site's geology that must ensure that the long-term radiological impact of the waste in the repository stays below the nationally and internationally allowable limits and is therefore significantly lower than natural radioactivity. The Boom Clay is a marine Oligocene clay of approximately 100 m thick deposited in the North Sea basin. It is known in Germany, The Netherlands and Belgium as a continuous layer gently dipping (∼1 deg.) towards the north-north-east but also gaining thickness in this direction. One of the most remarkable characteristics of the Boom Clay is its structure of bands that are several tens of centimeters thick, reflecting mainly cyclical variations in grain size (silt and clay content). The Boom Clay aquitard requires to be precisely characterized in terms of hydrogeological parameters, to confirm its role of geological barrier between its surrounding aquifers. Therefore, hydraulic conductivity and diffusion parameters have been intensively measured at only a few boreholes in Belgium, mainly located in the Mol-Dessel area, assuming a good lateral continuity of the geology. Combining these measurements with more densely acquired geophysical information allows quantifying their spatial variability and consolidating the continuity assumption. From a methodological point of view, the 3D modeling of hydrogeological parameters requires to solve several issues. First, it is required to find a consistent geo-reference system allowing to laterally correlate thin observations derived from boreholes separated by several tens of kilometers. Then, in order to provide a reliable 3D model, it is compulsory to integrate the correlation between the scarcely sampled target parameters (core measurements) and numerous geophysical logs (gamma ray, resistivity). Geostatistics provides a suitable framework to solve these issues. Finally, a 3D model of the target parameters is proposed and stochastic simulations are performed to quantify their local variability. This uncertainty quantification is of significant added value to assess the efficiency of the geological barrier. (authors)

[en] Full text: At the end of process equipment dismantling, the complete decontamination of nuclear facilities requires the radiological assessment of residual activity levels of building structures. As stated by the IAEA, 'Segregation and characterization of contaminated materials are the key elements of waste minimization'. From this point of view, the set up of an appropriate evaluation methodology is of primordial importance. The radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical, functional and qualitative information. Then, a systematic (exhaustive or not) control of the emergent signal is performed by means of in situ measurement methods such as surface control device combined with in situ gamma spectrometry. Besides, in order to assess the contamination depth, samples can be collected from boreholes at several locations within the premises and analyzed. Combined with historical information and emergent signal maps, such data improve and reinforce the preliminary waste zoning. In order to provide reliable estimates while avoiding supplementary investigation costs, there is therefore a crucial need for sampling optimization methods together with appropriate data processing techniques. The relevance of the geostatistical methodology relies on the presence of a spatial continuity for radiological contamination. In this case, geostatistics provides reliable methods for activity estimation, uncertainty quantification and risk analysis, which are essential decision-making tools for decommissioning and dismantling projects of nuclear installations. Besides, the ability of this geostatistical framework to provide answers to several key issues that generally occur during the clean-up preparation phase is discussed: How to optimise the investigation costs? How to deal with data quality issues? How to consistently take into account auxiliary information such as historical inventory? How to integrate the remediation support into the modelling? How to quantify uncertainties in the remediation costs while computing contaminated volumes? This geostatistical approach is currently performed in several former nuclear facilities of the CEA in France. The ATUE (enriched uranium workshops) premise, located in Cadarache, is a case in point. Focusing on this premise, the paper presents the geostatistical methodology and its added value to: (i) optimise the sampling strategy, (2) get a reliable mapping of the contaminated areas and (3) estimate the corresponding waste volumes so as to optimize the remediation plans and therefore cleanup costs. (authors)

[en] For oil recovery or CO₂ storage, 'reservoirs' are commonly used to designate geological structures where oil can be found or CO₂ can be stored. All reservoirs present a heterogeneity in terms of rock type and properties (such as porosity and permeability). In addition, some of these reservoirs present fractures and faults. Fractured reservoirs are an important part of the oil reserves in the world (Middle East, Gulf of Mexico, etc.) and some of them are important reservoirs in terms of oil volume and productivity in spite of the fractures. In addition, studies of reservoirs for geologic storage of CO₂ have shown the existence of diffuse fractures and faults and their strong impacts on flow. A key point in fractured reservoirs is to understand the geometry and hydraulic conductivity of the network formed by the fractures. This requires the construction of a reservoir model that integrates all available conceptual knowledge and quantitative data. The topic of the present paper deals with a new methodology able to perform the history matching of a fractured reservoir model by adapting the sub-seismic fault properties and positions. The main difficulty of this work is to generate a sub-seismic fault network whose fault positions can be easily modified while respecting the statistical fault model. The sub-seismic fault model we have chosen allows us to obtain a sub-seismic fault network that is consistent with the seismic fault network and that succeeds in capturing the specific spatial organization of the faults. In a first step, the geometry of the seismic fault network is characterized using fractal methods. Sub-seismic faults are then generated according to a stochastic algorithm. Finally, the geometry of this discrete fracture network is optimized in order to match the hydrodynamic data about the reservoir. The optimization algorithm modifies the sub-seismic fault positions, leading to the history matching of the reservoir model. Fractal properties are preserved during the deformation process. These different steps are demonstrated on a realistic synthetic case. (authors)

[en] At the end of process equipment dismantling, the complete decontamination of nuclear facilities requires a radiological assessment of the building structure residual activity. From this point of view, the set up of an appropriate evaluation methodology is of crucial importance. The radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical and qualitative information. Then, a systematic (exhaustive) control of the emergent signal is commonly performed using in situ measurement methods such as surface controls combined with in situ gamma spectrometry. Finally, in order to assess the contamination depth, samples are collected at several locations within the premises and analyzed. Combined with historical information and emergent signal maps, such data allow the definition of a preliminary waste zoning. The exhaustive control of the emergent signal with surface measurements usually leads to inaccurate estimates, because of several factors: varying position of the measuring device, subtraction of an estimate of the background signal, etc. In order to provide reliable estimates while avoiding supplementary investigation costs, there is therefore a crucial need for sampling optimization methods together with appropriate data processing techniques. The initial activity usually presents a spatial continuity within the premises, with preferential contamination of specific areas or existence of activity gradients. Taking into account this spatial continuity is essential to avoid bias while setting up the sampling plan. In such a case, Geostatistics provides methods that integrate the contamination spatial structure. After the characterization of this spatial structure, most probable estimates of the surface activity at un-sampled locations can be derived using kriging techniques. Variants of these techniques also give access to estimates of the uncertainty associated to the spatial prediction, or to the probability to exceed a given decontamination threshold. The activity spatial continuity similarity for comparable contaminations allows us to propose adequate sampling plans. The ability of Geostatistics to provide such alternative sampling strategies to the systematic control has been successfully evaluated on several premises located in former nuclear facilities of the CEA in France. The ATUE (enriched uranium workshops) premise, located in Cadarache, is a case in point. Focusing on this premise, the paper presents the geostatistical methodology and its added value to optimise the sampling strategy, to get a reliable mapping of the contaminated areas and to estimate the corresponding waste volumes. Besides, the ability of this geostatistical framework to provide answers to several key issues that generally occur during the clean-up preparation phase is discussed: How to optimise the investigation costs? How to deal with data quality problems in a spatial data analysis? How to consistently take into account auxiliary information such as historical inventory? How to integrate the remediation support into the modelling? How to quantify uncertainties in the remediation costs while computing contaminated volumes? (authors)

[en] Document available in extended abstract form only. Full text of publication follows: The Boom Clay is currently investigated as potential host formation for the deep disposal of high-level and/ or long-lived radioactive waste in Belgium. Deep disposal safety relies on multiple barriers: the 'supercontainer' containing the vitrified waste, the repository itself and the host formation in which the disposal could be constructed. The latter is the most important as it is the one that has to slow the migration of radionuclides towards the biosphere for a sufficiently long time when the man-made barriers are no longer effective. So it is the site's geology that must ensure that the long-term radiological impact of the waste in the repository stays below the nationally and internationally allowable limits and is therefore significantly lower than natural radioactivity. The Boom Clay is a marine Oligocene clay of approximately 100 m thick deposited in the North Sea basin. It is known in Germany, The Netherlands and Belgium as a continuous layer gently dipping (∼ 1 deg.) towards the north-north-east but also gaining thickness in this direction. One of the most remarkable characteristics of the Boom Clay is its structure of bands that are several tens of centimeters thick, reflecting mainly cyclical variations in grain size (silt and clay content). The Boom Clay aquitard requires to be precisely characterized in terms of hydrogeological parameters, to confirm its role of geological barrier between its surrounding aquifers. Therefore, hydraulic conductivity and diffusion parameters have been intensively measured at only a few boreholes in Belgium, mainly located in the Mol-Dessel area, assuming a good lateral continuity of the geology. This assumption needs to be validated by quantifying the transferability of the hydraulic parameters from well sampled to scarcely covered areas. Combining core measurements with more densely acquired geophysical information allows quantifying their spatial variability and bringing promising answers. From a methodological point of view, the 3D modeling of hydrogeological parameters requires to solve several issues. First, it is required to find a consistent geo-reference system allowing to laterally correlate thin observations derived from boreholes separated by several tens of kilometers. Then, in order to provide a reliable 3D model, it is compulsory to integrate the correlation between the scarcely sampled target parameters (core measurements) and numerous geophysical logs (gamma ray, resistivity). Geostatistics provides a suitable framework to solve these issues. Finally, a 3D model of the target parameters is proposed, together with an uncertainty envelope. This uncertainty quantification is of significant added value to assess the efficiency of the geological barrier. Besides the actual modeling of target parameters, the paper also presents sampling recommendations for forthcoming boreholes. (authors)