Large scale Geological Characterisation

Transcription

1 r Session 3A Large scale Geological Characterisation Chair: Andreas Gautschi / Hervé Chamley

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3 O/03A/1 SEISMIC IMAGING OF THE VARIABILITY IN THE CALLOVO-OXFORDIAN ARGILLITE D. Guillemot 1, B. Yven 1 1. Andra - Agence Nationale pour la Gestion des Déchets Radioactifs, 1/7 rue Jean Monnet, Parc de la Croix-Blanche, Châtenay-Malabry cedex2, France ( daniel.guillemot@andra.fr, beatrice.yven@andra.fr) INTRODUCTION Different studies, implying various methods, have been carried out in the Meuse / Haute-Marne area in order to evaluate the variability of the callovo-oxfordian argillite. Each method involves its proper investigation scale, ranging from the finest (high resolution well data, analysis on samples) to the largest (surface seismic imaging). The seismic method images the acoustic impedance, a physical property related to lithology. Therefore, geophysical interpretation gives clues to the lithological variability of the formation. The result is a continuous representation, at the scale of the method. The challenge is to combine these different methods, considering their own uncertainties, to provide a coherent image, as fine as possible, of the formation properties. The uncertainty driven by the seismic method and its impact on the signal are discussed in this paper. RESULTS AND SEISMIC DATA LIMITATIONS Three sedimentary sequences have been identified from well data in the argillite. The contrasts of the physical properties between them yields a clear seismic image of the geometry and of the intrinsic properties of each sequence and allows to reconstruct the architecture of the formation over great distances. After stratigraphic inversion, a finer characterisation points out two types of limitations in the method: i) vertical and horizontal resolution, which, given the seismic frequencies in the argillite, is in the 11 to 15 m range horizontally and about a few meters vertically; ii) artefacts, due to the remote nature of the method, occurring as laterally organized seismic events within the argillite formation. Such events are unexpected in the low variability sedimentary context deduced from the direct investigation methods. The comparison between the synthetic seismograms (from well data) and the actual seismic data demonstrates that this geophysical variability does not match with impedance contrasts in the formation and, therefore, is to be considered as artefacts (Figure 1a). ARTEFACTS MODELLING The origin of these artefacts has been searched for by modelling the seismic wavefront propagation in the callovo-oxfordian argillite and overlying formations. Wavefront propagation modelling is possible in isotropic viscoelastic, horizontally stratified media. Models have been built, featuring a Vertical Seismic Profile array (VSP), allowing a complete visualisation of wave trajectories and their multiple reflections. Additional models have been built, featuring a surface seismic array, for comparison with the results of the Figure 1: a : artefacts in the Callovo-Oxfordian argillite (light blue) ; b : reflections and multiples in the VSP model (green arrows). actual seismic survey. The former model points out that multiple reflections, generated in the oxfordian and kimmeridgian limestone, superimpose over the primary reflections in the argillite layer (Figure 1b). Moreover, shear waves, slower than compressional ones, are shown to interfere also with the response of the argillite. Thus, modelling suggests that the apparent geophysical variability in the argillite is a combination of artificial variability and variability of the intrinsic properties of the formation. This artificial noise is generated in the highly contrasted upper levels and is expressed clearly in the low contrast argillite. Page 37

4 O/03A/1 ARTIFACT REMOVAL The superimposed artificial seismic arrivals increase the uncertainty upon geophysical interpretation. Two approaches have been carried out to attenuate, or eliminate them: Geophysical processing: Apparent velocities of multiple reflections are slower than velocities of primary reflections, so most multiples are eliminated while stacking. Only the multiples with apparent velocities close to that of the primaries remain. Three different techniques have been tested on the 3D seismic data, to check that the multiples attenuation would not affect the amplitude of the geologically significant signal. The reflection on a carbonaceous level inside the argillite layer (RIO, known in the whole Paris Basin) is used as a true primary reflection. It appears that efficient multiples attenuation unavoidably implies significant attenuation of the primaries, which limits the use of these techniques. Geostatistical processing: A spatial filtering, based on geostatistical signal processing, is also able to attenuate the artefacts. A comparison between the actual seismic trace and seismic response from well data (synthetic seismogram and VSP) separates the noise spatial signature from the signal one. Factorial kriging of the amplitudes yields to a spatial filtering of the noise and is propagated along the profiles and in the 3D cube. Filtering coherency is then checked along the seismic horizons. RESULTS AND UNCERTAINTIES For Andra purposes, it is necessary to refine as much as possible the knowledge of the argillite variability. The maximum refinement is reached locally in wells and Underground Research Laboratory but uncertainty increases gradually away from these locations. Seismic imaging reduces the uncertainty inherent in the interpolating process. The scale of variability evaluation reachable by the seismic method depends on the amount of artefacts and on our ability to attenuate them. The accurate estimation of natural argillite variability from seismic data has to go through: attenuating of artificial components, taking into account, during interpretation, the added uncertainty due to residual artefacts, comparing the seismic imaging to the results from direct investigation methods while solving the scaling problems. This process will yield an optimal contribution of the seismic method to the building of a coherent geological model, at the scale of the area and, lately, of a possible underground disposal. References: [1] BEICIP collectif (2005): Inversion et caractérisation pétrophysiques des données sismiques 2D et 3D ; site de Meuse / Haute-Marne. Rapport Andra n C.RP.0BEI C. [2] J.M. Michel, F. Haouam (2007): Laboratoire de recherche souterrain de Meuse / Haute-Marne, Rapport de retraitement antimultiple 2006, Sismique 3D ; Rapport Andra n C.RP.0CGG A. Page 38

5 O/03A/2 IDENTIFICATION OF HOMOGENEOUS ZONES FROM WELL LOGGING MEASUREMENTS BY STATISTICAL TOOLS A. Marache 1, J. Riss 1, A. Denis 1, B. Yven 2, A. Trouiller 2 1. Université Bordeaux 1 CDGA (GHYMAC) Av. des Facultés 35 Talence Cedex - France 2. ANDRA Service Milieu Géologique 1-7 Rue Jean Monnet Châtenay-Malabry Cedex - France INTRODUCTION AND PURPOSE Since several years, ANDRA leads research programs in order to determine various properties of the Callovo-Oxfordian argillaceous formation of the Meuse-Haute Marne sector (East of Paris Basin, France) (ANDRA, 2005). A lot of boreholes with well logging measurements have been performed. The aim of the paper is to present the results of development and application of statistical methods to determine homogeneous zones from a set of well logs. The identified zones are then characterized by geomechanical parameters. First, the method has been developed from four variables (DT (inverse of the P-wave velocity), GR (gamma ray), NPHI (neutron porosity) and RHOB (density)) measured in the HTM102 borehole between 342 m and 471 m deep (measurement step equal to 12.5 cm). It then has been applied on similar set of well data recorded in 6 others boreholes drilled in 1995 and 2003 and the same study will be realised from future boreholes planed to be drilled in At the end, a three dimensional model of homogeneous zones in the Callovo-Oxfordian formation will be built. MULTIDIMENSIONAL STATISTICAL ANALYSIS In order to identify homogeneous zones, a multidimensional statistical analysis has been realised after correcting the original data of support measurement effects. First, a principal component analysis is leaded from the four standardised variables. One can see on the F1F2 correlation circle (Figure 2).) that the F1 axis (78% of absorbed variance) is formed by DT, NPHI and GR for positive values and by RHOB for negative values. The samples are then plotted on the F1F2 plan (Figure 3); in order to identify clusters of samples with equivalent characteristics, a hierarchical classification has been performed allowing to class samples into six groups. The class 1 shows the densest samples (negative values on F1, large RHOB values) which are also the most calcar- DT (10-3 ms/ft) GR (API) NPHI RHOB (t/m 3 ) F 2 RHOB 0.5 GR NPHI F DT -0.5 Figure 1: Well logging data Figure 2: Projection of variables on the F1F2 plan (91% of absorbed variance) Page 39

6 O/03A/ Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Figure 3: Projection of classified samples on the F1F2 plan F F 2 F 1 eous samples as we know from laboratory measurements while the 4, 5 and 6 classes represent the most argillaceous samples (with a maximum of clay for the group 4, large GR and DT values). Then, we have built a pseudo-log by plotting for each depth its F1 value according to the cluster analysis (Figure 4). From this pseudo-log six homogeneous zones can be identified which are then characterized by mineralogical or mechanical parameters (Figure 5). The number of zones could be increased as a function of the needed degree of accuracy (example of a thin calcareous layer at m deep which is not isolated here) E (MPa) Rc (MPa) Ed (MPa) Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Limits Figure 4: Pseudo-log and identification of homogeneous zones. Figure 5: Characteristic mechanical parameters of each zone (Young s modulus E, Compressive strength Rc and Dynamical Young s modulus Ed). CONCLUSION This stage has shown how the use of the multidimensional statistical analysis can be a highly capable and objective tool to identify homogeneous zones from a set of well logging measurements. The results from all boreholes help to identify and quantify the lateral variability of physical (mechanical) properties of the Callovo-Oxfordian formation. References: ANDRA (2005): Dossier 2005 Argile - Les recherches de l'andra sur le stockage géologique des déchets radioactifs à haute activité et à vie longue. Page 40

7 O/03A/3 CALLOVO-OXFORDIAN CLAY VARIABILITY FROM HIGH RESOLUTION LOG DATA M. Lefranc 1,2, B. Beaudoin 2, J.P. Chilès 2, D. Guillemot 1, C. Ravenne 3, A. Trouiller 1 1. Andra - Agence Nationale pour la Gestion des Déchets Radioactifs, 1/7 rue Jean Monnet, Parc de la Croix-Blanche, Châtenay-Malabry cedex2, France ( marielefranc@voila.fr, daniel.guillemot@andra.fr, alain.trouiller@andra.fr) 2. EMP Ecole des Mines de Paris, Centre de Géosciences, 35 rue Saint Honoré, Fontainebleau Cedex, France ( bernard.beaudoin@ensmp.fr, jean-paul.chiles@ensmp.fr ) 3. IFP Institut Français du Pétrole, 1 & 4 Avenue de Bois-Préau, Rueil Malmaison Cedex, France (christian.ravenne@ifp.fr) INTRODUCTION One of the main lines of research of the National Radioactive Waste Management Agency (Andra) is deep geological disposal studies. Andra has conducted studies in its Meuse/Haute-Marne underground research laboratory located at a depth of about 490 m in an argilaceous rock (argilite) 155 million years old: the Callovo-Oxfordian formation. Like any natural environment, this formation is variable, but with a low and gradual variability which depends on the parameters and the scale considered. The study of the variations of the Callovo-Oxfordian clay layer is very useful to predict the clay properties behaviour in a 250 km 2 area around the actual laboratory site and it can be conducted from logs analysis and particularly from high resolution logs (FMI ). The first part of this paper presents the FMI data, the log correlation between wells and the identification of homogeneous intervals. To improve the search for sedimentation rate variations, it is useful to transform depth intervals into geological time intervals; the second part is concerned with the geostatistical analysis of high resolution logs to build a geochronological reference system. DATA PRESENTATION AND ANALYSIS In this study, we use: (1) conventional logs and (2) a high resolution tool which provides an electrical borehole image: FMI Fullbore Formation MicroImager (Schlumberger). A texture classification software: BorTex (Schlumberger) provides 1D data from FMI : Background Conductivity (BC) and Residuals. When the carbonate content increases (core data are available for nearly all the clay layer), conductivity decreases, which makes it possible to follow the evolution of the carbonate content on the BC curve. A precise log correlation (at this scale : chronostratigraphic correlation) is established between wells (seven wells along two perpendicular axes :NE-SW: 37 km and NW-SE: 15 km). Local relative sedimentation rate variations or even sedimentation stop (hiatus) can be observed. On the FMI images and on BorTex results, resistive and conductive alternations are present. These carbonate-clay interbeddings have a periodic organisation. To improve the study of the variability, geostatistical tools are used to identify and quantify these cycles. Cycles have been shown in the Callovo-Oxfordian formation (Brégoin, 2003, Huret, 2006). If the whole clay layer is considered, cyclicity does not have a uniform organization; homogeneous intervals more than 10 m thick and correlable between different wells are selected. Three intervals are defined in the Lower Oxfordian (interval 1 at the base to interval 3 at the top). GEOSTATISTICAL RESULTS In order to get a better resolution, the FMI images are analysed, particularly the background conductivity and the conductive inclusion proportion (BorTex results). Three periods per homogeneous interval are observed on the calculated variograms. FMI thickest cycles are similar to periods given by classical log analysis. The best resolution is obtained with the conductive inclusion proportion : cycles 30 cm thick can be observed on variograms. The conductive inclusion porportion is the only parameter which gives this resolution. As a result three main periods of log data are identified; these periods vary vertically in a given well and laterally between different wells. Cycle ratios are similar to the orbital cycle ratios from the Upper Page 41

8 O/03A/3 Figure 1: FMI images, variographic analysis of the background conductivity and residuals and factorial kriging analysis results in the interval 2 (Lower Oxfordian) of EST 312. Jurassic (Berger & Loutre, 1994); cycles represents eccentricity (95000 years), obliquity (37700 years) and precession (about years). So the signal obtained is not a random signal, it is controlled by sedimentary porcesses. The periodic impact of eccentricity can be observed on both classical log data and the FMI data analysis while precession is only seen on the FMI geostatistical analysis. Variographic analysis (figure 1) gives the mean thickness corresponding to the Milankovitch cycles in each homogeneous interval. Factorial kriging (figure 1) is then used to estimate the influence of each orbital cycle. Factorial kriging also shows the local variations of cycles thickness. To improve the search for sedimentation rate variations, it is useful to transform depth intervals into geological time intervals. Working with log correlations, high resolution log data, biotratigraphic correlations, orbital cycles and factorial kriging analysis results makes it possible to improve the correlations, to estimate the stratigraphic interval duration as well as the hiatus duration. To sum up, the study of classical log correlation between wells can only show few local sedimentation rate variations. The use of a high resolution tool which can detect objects 5mm in size, and adapted geostatistical techniques are therefore necessary to quantify the variability in this argilaceous environnement. References: Andra [2005]. Référentiel du site Meuse/Haute-Marne. Dossier Rapport n C.RP.ADS Berger A. & Loutre M.-F. [1994] Astronomical forcing through geological time. In orbital forcing and cyclic sequences (editions De Boer P.L. & Smith D.G.). Special Publication of IAS, 19, Bregoin S. [2003] Variabilité spatiale et temporelle des caractéristiques du Callovo-Oxfordien de Meuse/ Haute-Marne. Thèse de l Ecole des Mines de Paris. Huret, E. [2006] Analyse cyclostratigraphique des variations de la susceptibilité magnétique des argilites callovo-oxfordiennes de l Est du Bassin de Paris : application à la recherche de hiatus sédimentaires. Thèse Univ. Pierre et Marie Curie Paris 321 p. Page 42

9 O/03A/4 MAGNETIC PROPERTIES, MAGNETIC MINERALOGY AND FABRIC OF THE ARGILLITES OF THE MEUSE/HAUTE-MARNE URL J.L. Bouchez 1, L. Esteban 1, 2, 3, 4, Y. Géraud 2, A. Trouiller 3 and R. Siqueira 1 1. Toulouse University, 14 Ave E. Belin, 31 -Toulouse and GdR CNRS FORPRO bouchez@lmtg.obs-mip.fr ; siqueira@lmtg.obs-mip.fr 2. Univ. Strasbourg, EOST, 1 rue Blessig, Strasbourg (ygeraud@illite.u-strasbg.fr ) 3. Andra, Parc de la Croix Blanche, 1-7 rue J. Monnet, Châtenay-Malabry (alain.trouiller@ andra.fr) 4. Now at Geological Survey of Canada-Pacific, 9860 West Saanich Road, Sidney, B.C., Canada, V8L 4B2 (lesteban@nrcan.gc.ca) The Jurassic in age, ~ 130 m thick, gray-coloured and homogeneous argillites that host the Andra laboratory, are a mélange of clay minerals (~ 50%), carbonates (~ 25%) and silts (~ 25%). These argillites constitute a rather short geological episode (~ 4 Ma ) in a periode dominated by carbonate plateform formations. They have been collected at depth (~ 490 m) by Andra, and this make their study quite exceptional since the samples were devoid (or almost so) of physical or chemical modifications such as hydratation and micro-textural desorganization. Magnetic measurements were performed on a collection of samples more-or-less regularly spaced over the formation, out of cores coming from a few vertical boreholes and from the inclined EST211 borehole. The magnetic susceptibility, K, when reported versus the natural remanent magnetization (NRM; Figure), helps to distinguish between a purely paramagnetic behaviour, ascribed to the slightly iron-bearing clay fraction (smectite, illite), and a behaviour due to a remanent fraction, mostly due to iron-bearing oxides (maghemite) but also to some ferromagnetic iron sulfides (pyrrho-tite or greigite). The K vs. NRM diagram shows that the dominant fraction (> 45%) is paramagnetic, and that lithologies richer in clay-minerals, such as lithology 5 hosting the Andra laboratory, have larger variations in K ( ìsi) than lithologies enriched in silt (such as litho. 3; ìsi). The anisotropy of magnetic susceptibility shows that, in addition to an ubiquitous planar anisotropy, ranging from 1 to 50 conformably to the horizontal and more-or-less cryptic bedding of the rock, a faint (3.5 in average) within-bedding linear anisotropy is always present, making 1% to 43% of the total magnetic anisotropy. It is worth noting that the orientation of the magnetic lineations is rather constant in direction, about N-S to NE-SW in average for the lithologies richer in clay, and NW-SE for lithologies enriched in silt. With respect to the rock microstructure, this «transverse» anisotropy» is attributed to the zone-axis distribution of the clay platelets and/or to the long axes the ferromagnetic grains. The mineral fabric is responsible for the anisotropy of the pore network connectivity, at least in the clay-enriched argillites, a subject examined by Géraud et al. (this volume). Origin of the transverse anisotropy remains under debate. It may be due either to a preferred direction of compaction, to a slight plastic deformation of the pile toward the center of sediment deposition, or to an overall north-south direction of the currents transporting the sediments. Since absolutely no deformation feature could be observed in the rock, even under electron microscopy, we tentatively prefer the last hypothesis which favourably agrees with the presence of Variscan terranes to the north of the study area, i.e., London-Brabant to the NW and Rheno-Bohemian to the NE, from which the sediments could have been extracted. Page 43

10 O/03A/4 Figure 1: Susceptibility as a function of remanence for the ten lithologies that were defined for the Callovo-Oxfordian formations (including the bracketing limestones). Arrows describe the evolution with time inside each lithology. Figure 2: Azimuths of the magnetic lineations (long axis of the magnetic fabric ellipsoid) of the Callovo- Oxfordian argillites for : (a) lithology 3, with distinction between the upper and lower parts, and (b) all lithologies. n : number of measured specimens. References : Esteban, L Anisotropies magnétique et de porosité des argilites du Callovo-Oxfordien du laboratoire souterrain de l'andra (Meuse/Haute-Marne, Bassin de Paris). Thèse Univ. Toulouse, 290 pp. Esteban, L., Bouchez, J.L. and Trouiller, A The Callovo-Oxfordian argilites from eastern Paris basin: magnetic data and petrofabrics. C. Rend. Acad. Sci., Paris, Géosciences, 338, Esteban, L., Géraud, Y. and Bouchez, J.L. (2006). Pore network connectivity in low permeability argillites from magnetic fabric data and oriented mercury injections. Geophysical Research Letters, vol. 33, L18311, doi : /2006GL Page 44