Multi-scale Quantitative Diagenesis and Impacts on Heterogeneity of Carbonate Reservoir Rocks (eBook)

Dr. habil. Fadi Henri Nader is an Engineer Sedimentologist at the IFP Energies nouvelles (formerly: Institut Français du Pétrole, IFP). He is working on diagenesis (fluid-rock interactions) and its impacts on reservoir properties (porosity/permeability) at the plug-, reservoir- and basin-scales. he has also launched several new research projects related to reflection seismic interpretations and modelling of frontier basins.

iTABLE OF CONTENTS General Summary of Scientific/Academic Activities xvii Chapter 1: Introduction1.1. Diagenetic realms 11.2. Porosity and diagenesis 41.3. Quantitative diagenesis 71.4. Numerical modelling of diagenesis 91.5. Objectives and way forward 13 Chapter 2: Characterization of diagenesis2.1. State of the art (Characterization of diagenesis) 152.1.1. Fieldwork 162.1.2. Petrography 18Pre-microscopic observations 18Microscopic observations 192.1.3. Geochemistry 20Major and trace element analyses 20Stable oxygen and carbon isotopic analyses 21Strontium isotope analyses 212.1.4. Mineralogy 22IFPEN protocol for XRD 22Electron microprobe 232.1.5. Fluid inclusions 24Microthermometry 24Crush-leach analyses 242.1.6. Integrated techniques for building conceptual models 252.2. Future perspectives 272.2.1. Clumped oxygen isotopic analyses 272.2.2. Mg isotopic analyses 282.2.3. 3D porosity 30Micro-CT setup and 3D-image reconstruction 31Building an equivalent pore network from the actual pore space 31Numerical simulation of mercury intrusion and permeability 34ii2.3. Discussion and personal contribution 352.3.1. General discussion 352.3.2. Personal contribution 37Analytical methods: Dolomite stoichiometry assessment 37Dolomitization 38Sandstone diagenesis 39Source rocks 392.4. Advancement in characterization of diagenesis 412.5. Samples of published articles in peer-reviewed journals 43Chapter 3: Quantitative diagenesis3.1. State of the art (Quantitative diagenesis) 993.1.1. Petrography – Plug/Sample scale 993.1.2. Petrography – Reservoir scale 1023.1.3. Mineralogical analyses (X-Ray Diffraction) 1063.1.4. Geochemical analyses – Thin section scale 1093.1.5. Geochemical analyses – Reservoir scale 1103.1.6. Geochemical analyses – Basin scale 1123.1.7. Fluid inclusion analyses – Petroleum systems 1143.1.8. 3D Scanning (CT and micro-CT) and image analysis 1173.2. Future perspectives 1213.2.1. Remote sensing and photogrammetry 1213.2.2. Integrated data analysis tools 1223.2.3. Pore space models 1233.3. Discussion and personal contribution 1253.3.1. General discussion 1253.3.2. Personal contribution 128Quantitative analytical methods 129Fluid inclusion analysis 129Integrated petrographic and petrophysical data analyses 129Micro-CT and image analyses 1293.4. Advancement in quantitative diagenesis 1313.5. Samples of published articles in peer-reviewed journals 133iii Chapter 4: Numerical modelling of diagenesis4.1. State of the art (Numerical modelling of diagenesis) 1814.1.1. Geometry-based modelling 181Karst networks modelling 181Fracture-related hydrothermal dolomite modelling 1854.1.2. Geostatistical modelling 188Methodology: Geostatistical parameterization steps 188Methodology: Geostatistical simulation methods 191Case study: Geostatistical modelling of the Upper Jurassic Arab D reservoir heterogeneity, Offshore Abu Dhabi, United Arab Emirates (Morad, 2012) 197Alternative workflow for geostatistical modeling of the Arab D reservoir heterogeneity 2154.1.3. Geochemical modelling 2200D geochemical modelling: Dissolution/Precipitation rates 2202D geochemical reactive transport modelling: Reflux dolomitization 2233D geochemical reactive transport modelling: Compactional dolomitization 2284.2. Future perspectives 2334.2.1. Geometry-based modelling 2334.2.2. Geostatistical modelling 2334.2.3. Geochemical modelling 2344.2.4. Towards integraded geomodels 2354.3. Discussion and personal contribution 2374.3.1. General discussion 2374.3.2. Personal contribution 241Geometry-based modelling 241Geostatistical modelling 242Geochemical modelling 2424.4. Advancement in numerical modelling of diagenesis 2454.5. Samples of published articles 247 Chapter 5: Petroleum systems and basin evolution5.1. The Levant Basin 2835.2. State of the art (petroleum systems and basin modelling) 2905.2.1. Forward stratigraphic modelling 290Methodology (DionisosFlowTM) 291Levant Basin forward stratigraphic model 293iv5.2.2. Basin modelling 299Methodology (TemisFlowTM) 300Lithofacies transfer from DionisosFlowTM to TemisFlowTM 301Levant Basin model 309Synopsis 3165.3. Future perspectives 3175.3.1. Towards integrated stratigraphic basin models 3175.3.2. Towards integrated basin/reservoir models 3195.4. Discussion and personal contribution 3215.4.1. General discussion 3215.4.2. Personal contribution 324Stratigraphic modelling 324Petroleum systems modelling 324Structural modelling 3255.5. Advancement in numerical integrated modelling 3275.6. Samples of published articles in peer-reviewed journals 329 Chapter 6: Conclusions and general perspectives6.1. Characterization techniques and workflows 3746.2. Quantitative techniques and workflows 3756.3. Modelling techniques and workflows 3766.4. Integrated modelling workflows 3776.5. Way forward and research strategy 378 References 381 Extended curriculum vitae 399vLIST OF FIGURESFigure i. From conceptual to numerical modelling of diagenesis, quantifying diagenetic phases remains essential…………………………………………………………………………………………….... xviiiChapter 1: IntroductionFigure 1- 1. Schematic representation of major diagenetic realms, related processes and resulting products in a carbonate platform.…………………………………………………………………...…………….... 1Figure 1- 2. Field photograph showing the Lower Cretaceous microbialithes of the Qishn Formation in Wadi Baw (Oman) during a field visit with Petrobras (in 2007)…………………………………………... 3Figure 1- 3. Diagenesis occurs in depositional and erosional environments with distinct spatiotemporal zones: Eogenetic, Mesogenetic and Telogenetic……………………………………………………………. 4Figure 1- 4. Schematic illustration of porosity evolution during diagenesis: progressive dissolution (from mould to vug) and porosity reduction by cementation……………………………………………………… 5Figure 1- 5. Porosity 3D network building based on micro-CT and image analyses (from De Boever et al., 2012)…………………………………………………………………………………………………. 6Figure 1- 6. Integrated techniques for constraining flow properties (porosity and permeability) during dissolution of dolomite and successive anhydrite cementation of a reservoir rock…………………. 6Figure 1- 7. Photograph showing the extent of hydrothermal dolomites (dark brown) in platform carbonates (Ranero, northern Spain)…………………………………………………………………………….. 7Figure 1- 8. 3D cube of a typical Jurassic Arab C dolostone sample (Middle East), which have been scanned with micro-CT at resolution of 1.5 μm………………………………………………………………. 8Figure 1- 9. Illustrations showing subsampling schemes for determining the Representative Elementary Volume (REV)………………………………………………………………………………………………... 8Figure 1- 10. Geometry-based modelling of the fracture related Ranero hydrothermal dolomites (northern Spain)………………………………………………………………………………………………… 10Figure 1- 11. Results of geostatistical stochastic joint simulations of sedimentary facies and diagnetic imprints of the three stratigraphic units in the Madison Formation, Wyoming – USA………………………. 11Figure 1- 12. Results of reactive transport modelling of reflux dolomitization showing the volumetric evolution (in %) of dolomite, anhydrite and porosity………………………………………………………….. 12Chapter 2: Characterization of diagenesisFigure 2- 1. Map showing dolomite occurrence and fracture (fault) lineaments in Cretaceous platform carbonate rocks exposed in Ranero (NE Spain)………………………………………………………………… 16Figure 2- 2. Out-crop scale petrographic observations on the world class fault-associated dolomites in the Ranero, Pozalagua quarry/auditorium (NE Spain)…………………………………………………... 17viFigure 2- 3. Stained polished, etched slab of dolomite from the Ghalilah Formation (Upper Triassic) in Ras Al Khaimah (UAE)……………………………………………………………………………………… 18Figure 2- 4. SEM backscattered electron image (left) and cluster analysis of electron microprobe map (right), as well as mean structural formula for two different dolomites………………………………………... 23Figure 2- 5. Proposed sequence of diagenetic phases (paragenesis) for the dolostones of the Marjaba HDT front (central, Lebanon)……………………………………………………………………………………. 25Figure 2- 6. Examples of conceptual dolomitization models and their schematic geometries and extent… 26Figure 2- 7. Interpolated (solid) line of Δ47 values (in ‰) and corresponding temperatures (in K) for inorganic and organic carbonates (from Eiler, 2007)…………………………………………………………... 28Figure 2- 8. Theoretically predicted Mg isotope fractionation factors (from Li et al., 2012 and references therein)……………………………………………………………………………………………….. 29Figure 2- 9. Extracted macro-pore network for the Estaillades carbonate rock standard. ………………… 30Figure 2- 10. (A) 3D grey scale view of micro-CT scan (2000x1000x1000 pxls) of a typical Jurassic Arab C dolostone (Middle East). (B) Grey level histogram (De Boever et al., 2012)……………………….. 32Figure 2- 11. Equivalent network building of the actual pore structure of a typical Jurassic Arab C dolostone (Middle East)………………………………………………………………………………………… 33Figure 2- 12. Simulated and measured mercury injection capillary pressure curve of the actual pore structure of a typical Jurassic Arab C dolostone (Middle East)………………………………………………….. 34Figure 2- 13. Burial model for a well intercepting Khuff equivalent reservoirs (Kangan Formation) in the Salman field, offshore Iran (Peyravi et al., 2014 )………………………………….……………….. 36Chapter 3: Quantitative diagenesisFigure 3- 1. Scanning electron microscope (SEM) photomicrographs coupled with nuclear magnetic resonance (NMR) T2 distribution graphs of two typical carbonate rocks ……………………………………… 100Figure 3- 2. Correlation cross-section (constructed by EasyTraceTM software based on petrographic analyses of thin sections) ………………………………………..……………………………………………….. 103Figure 3- 3. Statistical analyses of well data based on 10000 thin sections (and samples) from 13 wells (Arab D, Middle East).………………………………………………………………………………………… 104Figure 3- 4. Proportional maps showing: (i) the dolomite distribution (A: Wackestone-Packstone; B: Packstone-Grainstone; C: Mudstone-Wackestone); and (ii) the relative abundance of the syntaxial calcite overgrowth cement (D: wackestone-Packstone; E: Packstone-Grainstone; F: Mudstone-Wackestone) in the Arab D member of an investigated oilfield offshore Abu Dhabi (UAE)…………………………………….. 105Figure 3- 5. XRD and Rietveld diagram showing the quantitative assessments of calcite, dolomite and anhydrite in a Triassic carbonate rock from the French Jura…………………………………………………... 106Figure 3- 6. Cross-plot diagram of dolomite stoichiometry (%Ca in dolomite) versus dolomite cell parameter (c in Å) featuring data from various sources…………………………………………………………… 107Figure 3- 7. Unit cell dimensions of Upper Muschelkalk and Lettenkohle dolomites…………………….. 108Figure 3- 8. Spectral analysis and resulting mineralogical mapping of a sandstone sample from the Lower Cretaceous Upper Mannville Formation (Alberta, Canada)…………………………………………. 109viiFigure 3- 9. Detailed geological map of the Marjaba dolostone front with discordant geometry and its surrounding limestone host-rock (central Lebanon; Nader et al., 2007)……………………………. 110Figure 3- 10. Fe and Mn concentration contour maps (A) and cross-plot (B) for the Marjaba HDT front (central Lebanon; concentrations in ppm)……………………………………………………………………. 111Figure 3- 11. Schematic illustration representing the typical fracture-filling cement stratigraphy………… 113Figure 3- 12. Calculated oxygen stable isotopic composition ranges of the ‘parent’ diagenetic fluids (expressed in δ18O VSMOW) for dolomite and calcite cement phases………………………………………..… 113Figure 3- 13. Workflow for dating unaltered (preserved, A and D) and re-equilibrated (B and E) fluid water (aqueous) and petroleum inclusions…………………………………………………….…………… 116Figure 3- 14. Examples of training images of carbonate rock textures for constructing 3D models of pore space (with evolving diagenesis)…………………………………………………………………………… 117Figure 3- 15. Calculation of porosity% for increasing volumes to investigate the representative elementary volume of the studied sample…………………………………………………………………….….. 119Figure 3- 16. 2D-grey scale view of CT scan of a typical dolomitized grainstone………………………… 119Figure 3- 17. Integrated workflow for reservoir models based on 3D photogrammetry of outcrop analogues (from Schmitz et al., 2014)…………………………………………………………………………... 121Figure 3- 18. Hyperspctral image analysis and interpretation of the main face of the Pozalagua Quarry (Ranero, NE Spain; from Kurz et al., 2012)…………………………………………..……………………….. 122Figure 3- 19. Rock-Eval pyrolysis results for identifying and quantifying carbonate species)…………….. 127Chapter 4: Numerical modelling of diagenesisFigure 4- 1. An example of a 3D speleological map of underground karstic networks (Llueva cave, Spain) with Survex and supported by Therion software packages………………………………………………. 182Figure 4- 2. Improved workflow for ODSIM of karstic networks…………………………………………. 183Figure 4- 3. Simulated envelope of a karstic network skeleton obtained by taking into account the bedding plane (H1) – a stratigraphic feature, a fault (F1) – a structural feature, and an ‘attraction level’ (water-table) coinciding with the lowest conduits………………………………………………………...……….. 184Figure 4- 4. Top views of the Ranero model (6000 x 2000 m) showing the two study areas (outlined in black) and the distribution of dolomites (brown) within the original sedimentary facies………………..… 185Figure 4- 5. Based on field data and conceptual models, the Ranero fault-related dolomites can be further constrained by applying a distance decreasing control for the dolomite occurrence along faults/fractures with increasing depth from a preferential horizon……………….………………………………….. 186Figure 4- 6. Dolomite distribution simulation of the Ranero model (6000 x 2000 m) taking into account the NW-SE faults and the vertical geometry constraining factors……………………………………………. 187Figure 4- 7. The principle of computing a vertical proportion curve (VPC)………………………….……. 189Figure 4- 8. Schematic representation of the computation of VPCs and VPMs……………………….…… 189viiiFigure 4- 9. An example of a variogram showing its characteristic parameters…………………………… 190Figure 4- 10. Influence of variogram model type (A: Exponential; B: Spherical; and C: Gaussian) on the resulting distribution of modelled properties………………………………………………..………. 191Figure 4- 11. (A) The principles of the Sequential Indicator Simulation (SIS). (B) The way categorical variables are transformed into indicator functions……………………………………………………………...192Figure 4- 12. The principle of truncated Gaussian approach……………………….………………………. 193Figure 4- 13. The plurigaussian method and related parameters……………………………………...……. 194Figure 4- 14. The multiple-point geostatistics applied on channels…………….………………………….. 195Figure 4- 15. Schematic depositional model of the Arab D and C members……………………….……… 197Figure 4- 16. Three well-logs from southeast outer ramp to the northeast inner ramp across the investigated field, showing the rock texture distribution of the investigated parasequence set………………….. 198Figure 4- 17. Simplified map showing the investigated field (~20 x25 km) at the PS3 interval, the extent of the depositional facies, as well as the locations of wells………………………………………………… 199Figure 4- 18. Photomicrographs (PPL) displaying characteristic lagoon microfacies in PS3……………… 200Figure 4- 19. Photomicrographs (PPL) displaying examples of shoal microfacies in PS3………………… 200Figure 4- 20. Photomicrographs (PPL) displaying characteristic outer shoal microfacies in PS3…….…… 201Figure 4- 21. Photomicrographs (PPL) displaying characteristic outer ramp microfacies in PS3…………. 201Figure 4- 22. Cross-plots of bulk porosity (%) versus log-permeability analysed based on the abundance of SCOC and dolomite% within the PS3…………………………….…………………………………. 203Figure 4- 23. Geostatistical modeling workflow for the distributions of rock textures (in three classes: grainy, packstone, muddy), the SCOC (in four classes: absent, rare, common, abundant), dolomite (%) and porosity (%) in PS3………………………………………………….………………………………. 204Figure 4- 24. (Left) Depositional facies map showing the location of the wells (hard data) across the investigated field. (Right) Computed vertical proportion curves (VPCs) representing the vertical rock textures distributions in each of the ten wells…………………………...……………………………………. 205Figure 4- 25. Property map showing the extent of the depositional environments (i.e. areas)………...…… 206Figure 4- 26. Constrained proportion matrix (VPM) for rock textures in PS3……………………..………. 206Figure 4- 27. Top view of the modelled rock textures distribution in PS3…………………………………. 207Figure 4- 28. (Left) Depositional facies map showing the location of the wells (hard data) across the investigated field. (Right) Reported well-logs data representing the vertical SCOC abundance distributions in each of the ten wells………………………………………………………………………………………….. 208Figure 4- 29. Property map for constraining the distribution of SCOC in PS3……………………….……. 209Figure 4- 30. Constrained proportion matrix (VPM) for SCOC in PS3…………………...……………….. 210Figure 4- 31. Top view of the modelled SCOC distribution in PS3……………………………...………… 211Figure 4- 32. Top view of the modelled dolomite distribution in PS3………………………….………….. 212ixFigure 4- 33. View of the porosity attribution in PS3, based on the modelled distributions of rock textures, SCOC and dolomite as well as the diagenetic drivers rules…………………….…………………… 213Figure 4- 34. View of the permeability attribution in PS3, based on the modelled distributions of rock textures, SCOC and dolomite as well as the diagenetic drivers rules…………………………………………. 214Figure 4- 35. Geostatistical modelling workflow for the distributions of facies (rock textures in three classes: grainy, packstone, muddy) by means of plurigaussian method……………………………...……….215Figure 4- 36. Results of the two Gaussian simulations (A: G1; B: G2) across the study area for the rock textures (facies)………………………………………………………………………………..……………… 216Figure 4- 37. Distributions of rock textures (facies; A), porosity in % (B), SCOC (C) and permeability in mD (D) based on geostatistical modelling involving plurigaussian, FFT-MA, collocated cokriging methods for the PS3 interval (Upper Jurassic Arab D Member)………………………….………………………. 219Figure 4- 38. General characteristics of reflux dolomite model………………………………………...….. 223Figure 4- 39. Conceptual model of reflux dolomitization, including both processes of replacement of calcite and precipitation of dolomite cement (overdolomitization)……………………………………………… 225Figure 4- 40. Simulation results of reflux dolomitization 2D geochemical RTM with the original brines at 50°C and in three time steps (0.1, 0.2 and 0.3 m.y. after the start of fluid injection)…………………...…. 226Figure 4- 41. A typical example of sensitivity analyses demonstrating the influence of the reactive surface areas (102 and 104 cm2/g) on the modelled dolomite and anhydrite precipitations as well as porosity; from Jones and Xiao (2005)………………………………………………………………..…………………….. 227Figure 4- 42. Simplified map and cross-section showing the paleogeographic configuration at the Jurassic times of the Po Plain and the southern Alps (from Consonni et al., 2010)………………………………… 228Figure 4- 43. Basin (burial) modelling results across the Canonica basin and Malossa Paleohigh (Po Plain, Italy; from Consonni et al., 2010)………………………………………………………………………..… 229Figure 4- 44. Results of the 3D geochemical reactive transport model (RTM; with TOUGHREACT code) covering the Malossa Paleohigh…………………………………………………...………………… 230Figure 4- 45. Results of the 3D geochemical reactive transport model of the Malossa Paleohigh highlighting the impact of two different configurations of faults/fractures………………………...…………………. 231Figure 4- 46. Towards integrated basin/reservoir geomodels……………………………...……………….. 235Figure 4- 47. Results of geochemical RTM simulations achieved by ArXim-CooresTM representing the formation of hydrothermal dolomite fronts (dolomite, anhydrite and porosity%)………………….. 240Chapter 5: Petroleum systems and basin evolutionFigure 5- 1. Schematic representation of major diagenetic processes within basin-scale and/or reservoir-scale evolution frameworks……………………………………………………...………………………… 281Figure 5- 2. Schematic map showing the Levant Basin and the major oil/gas fields in the East-Mediterranean region and northern Arabia (from Nader, 2014a)……………………………………………………. 282Figure 5- 3. Petroleum systems model for onshore and offshore Lebanon showing potential source rocks, migration pathways, plays and seals (slightly modified from Nader, 2014b)……………….………. 284xFigure 5- 4. Chronostratigraphic chart showing observed onshore sedimentary facies and inferred offshore facies in Lebanon (based on seismic interpretation)…………………………………….………………….. 285Figure 5- 5. Un-interpreted and interpreted south-north 2D seismic profile offshore Lebanon (courtesy of PGS), showing the structure of the Levant margin…………………………………………………………. 286Figure 5- 6. An example of west-east oriented 2D seismic profile across the Levant Basin offshore northern Lebanon……………………………………………………………………………………………… 287Figure 5- 7. (A) 2D seismic profile showing interpreted facies associated to the Oligo-Miocene deepwater depositional settings offshore northern Lebanon, with channel incisions and fan lobe (turbidite) deposits (Hawie, 2014). (B) Amplitude map of at the Upper Miocene horizon showing the extent of the fan lobe (turbidite) complexes offshore norther Lebanon (from Fürstenau et al., 2013)………………...…… 288Figure 5- 8. Field photograph of the organic-rich Campanian lime-mudstone facies exposed in the Chekka quarries (Cimenterie Nationale sarl.) in northern coastal Lebanon………………………………..… 289Figure 5- 9. Conceptual model proposed for the eastern margin of the northern Levant Basin………...…. 290Figure 5- 10. Input parameters and sediment accommodation calculation with DionisosFlowTM……...….. 292Figure 5- 11. Constraining data for the forward stratigraphic model based on regional studies, seismic interpretation, fieldwork, and well correlations………………………………………………….….. 293Figure 5- 12. Coverage of the forward stratigraphic model for the northern part of the Levant Basin…..... 294Figure 5- 13. Schematic block-diagrams illustrating the Miocene depositional environments for the Levant Basin and its eastern margin………………………………………………………...……………….. 295Figure 5- 14. Results of carbonate production modelling at the margin and in the basin based on the best-fit model (from Hawie et al., in press)……………………………………..…………………………… 296Figure 5- 15. Results of the Levant Basin best-fit stratigraphic model (from Hawie et al., in press)…….... 297Figure 5- 16. Best fit simulation for the Levant Basin stratigraphic filling between 16 and 6Ma…………. 298Figure 5- 17. Northward view of the Levant basin model with simplified lithological facies…………...… 299Figure 5- 18. TemisFlowTM Map Editor depth map to the top of the Triassic rock series………………..... 300Figure 5- 19. Illustration of the followed workflow to transfer the facies distribution resulted from the DionosisTM stratigraphic model into the TemisFlowTM model………………………...…………….. 301Figure 5- 20. Bathymetry map (in meters) of present day seabed and onshore surface (Top Pliocene – Quaternary)………………………………………………………..…………………………………. 302Figure 5- 21. Thermal calibration in based on well data and surface exposed Cretaceous rocks……….…. 304Figure 5- 22. Basal heat flow variation through time for the six pseudo wells within the Levant Basin…... 305Figure 5- 23. Transformation ratio map of the Permian Type III source rocks across the Levant Basin and margin…………………………………………………………………………………...…………… 309Figure 5- 24. Transformation ratio history of the Permian source rocks at the six pseudo wells…….…….. 309Figure 5- 25. Transformation ratio map of the Kimmeridgian source rocks across the Levant Basin and margin (Bou Daher et al., submitted)…………………………………………………………….………….. 310Figure 5- 26. Transformation ratio history of the Kimmeridgian source rocks at the six pseudo wells….… 310xiFigure 5- 27. Transformation ratio map of the Neocomian source rocks across the Levant Basin and margin (Bou Daher et al., submitted)………………………………………………………………………... 311Figure 5- 28. Transformation ratio history of the Neocomian source rocks at the four pseudo wells….….. 311Figure 5- 29. Transformation ratio maps of two Campanian source rocks with distinct activation energies across the Levant Basin………………………………………………………………………..……………. 312Figure 5- 30. Transformation ratio history curves of the two distinct Campanian source rocks across the Levant Basin…………………………………………………………………………………………...…….. 312Figure 5- 31. Palaeogeographic map of the Levant region showing depositional environments in the Late Cretaceous times (Bou Daher et al., submitted)…………………………..…………………………. 313Figure 5- 32. EW section across the constructed model showing the calculated vitrinite reflectance at present day (Bou Daher et al., submitted)………………….………………………………………………… 315Figure 5- 33. Future perspectives for integrated stratigraphic-structural and fluid flow geomodels……..... 317Figure 5- 34. Plot of activation Energy (E), preexponential factor (A), and error function, for one of the analyzed samples (12/134), showing the different possible E and A couples for a minimum error function… 318Figure 5- 35. From left to right these are the P10, P50, and P90 transformation ratio maps using one of the analysed soure rock samples…………………………………………………………………...……. 318Chapter 6: Conclusions and general perspectivesFigure 6- 1. Proposed future operational workflow for tackling diagenesis: (A) Conceptual studies of diagenesis – for example hydrothermal or high temperature dolomitization (HTD; Nader et al., 2004, 2007); (B) Quantitative diagenesis methods – e.g. micro-computed tomography (micro-CT) image analyses (De Boever et al., 2012); and (C) Numerical simulations of diagenetic processes such as reactive transport modelling of dolomitization (e.g. Consonni et al., 2010)……………………………………………. 373Figure 6- 2. My research strategy on the general theme of “multi-scale integrated numerical modeling of diagenesis” for the coming three years (until 2018). Two parallel clusters of programmes are indicated (Diagenesis and Geological models). Principal cross-cluster themes are also indicated (upscaling, REV; scales and methods; case studies and validation). The regional expertise and related academic projects; such as supervising PhD projects are also listed per cluster.…………………………………..……. 379xiixiiiLIST OF TABLESChapter 2: Characterization of diagenesisTable 2- 1. Total list of material used throughout a typical diagenetic study (Nader, 2003)………………. 17Chapter 3: Quantitative diagenesisTable 3- 1. Various lithological and textural categories for describing carbonate microfacies ……………. 101Table 3- 2. Categories for describing cement in microfacies (thin sections)…………………………….… 101Table 3- 3. Categories for describing reservoir properties in microfacies (thin sections)………………….. 102Chapter 4: Numerical modelling of diagenesisTable 4- 1. The quantitative impact of diagenesis on reservoir quality for the various depositional facies and rock textures in PS3……………………………………………………………………..…………… 202Table 4- 2. The simulation method and variogram values for the rock textures distribution of PS3………. 207Table 4- 3. The simulation method and variogram values for the SCOC distribution of PS3…………..….. 210Table 4- 4. Variogram model for the porosity (FFT-MA) simulations……………………...……………… 217Table 4- 5. Parameters for the collocated cokriging simulations of the SCOC distribution in packstone rock-textures across the study area, and constraints for the variogram model…………….……………… 217Table 4- 6. Parameters for the collocated cokriging simulations of the SCOC distribution in grainstone rock-textures across the study area, and constraints for the variogram model……………………...…….. 217Table 4- 7. Applied conditional formulas for calculating permeability values based on simulated porosity per rock texture (facies) taking into account the SCOC distribution…………..……………………… 218Table 4- 8. Geochemical compositions of the fluids (associated to dolomite dissolution and anhydrite precipitation) used in reaction path calculations……………………………………….……………. 221Table 4- 9. Quantitative diagenesis of three samples from the Arab Formation (Abu Dhabi – UAE) by means of micro-CT image analyses and XRD (from De Boever et al., 2012)…………..…………………….. 222Table 4- 10. Sample chemical and physical input parameters for reaction path simulations. In gray: values of input parameters that were varied for a sensitivity study………………………………….………… 222xivChapter 5: Petroleum systems and basin evolutionTable 5- 1. Results of bulk rock analysis with Rock-Eval6 for selected source rock samples………….….. 306Table 5- 2. Pure organic matter Rock-Eval6 results for selected source rocks samples after acid treatment and DCM extraction (from Bou Daher et al., submitted)……………………………………..………….. 306Table 5- 3. XRD results pre- and post-acid treatment of source rocks……………………………….……. 307Table 5- 4. Mean activation energies and frequency factors for selected source rock samples……….…… 308xvDEFINITIONSArXim Open source program for multiphase speciation, equilibrium and reaction calculations between minerals, aqueous solutions and gases (EMSE and IFPEN).AvizoTM 3D analysis software application for exploring and understanding materials structures and properties, in a wide range of materials science research areas (FEI).CobraFlowTM Software for performing geologically meaningful simulations using geostatistical algorithms (IFPEN and Centre of Geostatistics of the Paris School of Mines).CooresTM (CO2 Reservoir Environmental Simulator), a research code designed to study CO2 storage processes from the well to the basin scale (IFPEN). It simulates multi-component three-phase and 3-D fluid flow in heterogeneous porous media. To take into account mineralogy changes, the transport model is coupled with ArXim.DionisosFlowTM (Diffusion Oriented Normal and Inverse Simulation Of Sedimentation), a deterministic 3D multi-lithology stratigraphic modelling software that simulates depositional processes in a sequence of steps moving forward in time (IFPEN)..EasyTraceTM A multi-disciplinary 1D data processing and editing tool, featuring advanced spreadsheets and a wide range of functionalities for geologists and geophysicists (IFPEN).EOR Enhanced Oil Recovery.FracaTM Software capable of characterizing, modelling and calibrating faults and fractures. It builds consistent fracture networks, constrained in 3D by seismic and geological attributes.GOCAD (Geological Object Computer Aided Design), a software package used for building and update, geo-referenced 3D subsurface models (Gocad Research Group, Georessources UMR 7359, Géologie - Université de Lorraine).InterWellTM Software capable to analyse post, pre stack and 4D seismic data, to compute multi cubes seismic wavelet calibrated at wells and to build a priori seismic impedance cubes honouring wells and stratigraphic data (IFPEN).JMicroVision A freeware designed to describe, measure, quantify and classify components of all kinds of images allowing to analyze high definition images of rock thin-sections (http://www.jmicrovision.com).MatlabTM A high level programming language and interactive environment capable of advanced numeric computation, data analysis and visualization, programming and algorithm development and application (Mathworks).PHREEQ-C. A computer program designed to perform a wide variety of aqueous geochemical calculations. It implements several types of aqueous models and is capable of undertaking speciation, saturation-index, and transport calculations (USGS).TemisFlowTM Basin modelling software package for assessing regionally controlled petroleum systems and basin evolutions. It calculates the generation, migration and accumulation of fluids (IFPEN).xvi