CHARACTERIZATION OF UPPER PALAEOZOIC ORGANIC‐RICH UNITS IN SVALBARD: IMPLICATIONS FOR THE PETROLEUM SYSTEMS OF THE NORWEGIAN BARENTS SHELF

Recent discoveries of hydrocarbons along the western margin of the Norwegian Barents Shelf have emphasised the need for a better understanding of the source rock potential of the Upper Palaeozoic succession. In this study, a comprehensive set of organic geochemical data have been collected from the Carboniferous – Permian interval outcropping on Svalbard in order to re‐assess the offshore potential. Four stratigraphic levels with organic‐rich facies have been identified: (i) Lower Carboniferous (Mississippian) fluvio‐lacustrine intervals with TOC between 1 and 75 wt.% and a cumulative organic‐rich section more than 100 m thick; (ii) Upper Carboniferous (Pennsylvanian) evaporite‐associated marine shales and organic‐rich carbonates with TOC up to 20 wt.%; (iii) a widespread lowermost Permian organic‐rich carbonate unit, 2–10 m thick, with 1–10 wt. % TOC; and (iv) Lower Permian organic‐rich marine shales with an average TOC content of 10 wt.%. Petroleum can potentially be tied to organic‐rich facies at formation level based on the gammacerane index, δ¹³C of the aromatic fraction and/or the Pr/Ph ratio. Relatively heavy δ¹³C values, a low gammacerane index and high Pr/Ph ratios characterize Lower Carboniferous non‐marine sediments, whereas evaporite‐associated facies have lighter δ¹³C, a higher gammacerane index and lower Pr/Ph ratios.     

DEPOSITIONAL FACIES,PORE TYPES AND ELASTIC PROPERTIES OF DEEP‐WATER GRAVITY FLOW CARBONATES

Quantitative petrographic analyses of deep‐water resedimented carbonates from the Gargano Peninsula (SE Italy) were integrated with petrophysical laboratory measurements (porosity, P‐and S‐wave velocities) to assess the impact of sedimentary fabrics and pore space architecture on velocity‐porosity transforms. Samples of Upper Cretaceous carbonate came from the Monte Sant'Angelo, Nevarra and Caramanica Formations and can be classified into four depositional facies associations: F1, lithoclastic breccias; F2, bioclastic packtones to grainstones; F3, interbedded grainstones‐packstones and wackestones; and F4, (hemi‐) pelagic mudstones. Five pore type classes were distinguished: I and II, dominant intercrystalline microporosity; IIIa, dominant intergranular macroporosity; IIIb, dominant mouldic macroporosity; and IIIc, mixed intergranular and mouldic macroporosity. Pore type was found to strongly control velocity‐porosity transforms, unlike depositional facies associations. The equivalent pore aspect ratio (EPAR), derived from differential effective medium models, is proposed to identify pore types from elastic properties. The EPAR originates from the bulk modulus or shear modulus of the samples (K‐ and μ‐EPAR, respectively). Regardless of porosity values and depositional facies, microporous samples (type I) and samples with dominant intergranular porosity (type IIIa) are characterized by low values of K‐ and μ‐EPAR (<0.22) and by K‐EPAR > μ‐EPAR By contrast, samples with dominant mouldic porosity (type IIIb) display high values of K‐ and μ‐EPAR (>0.25 and 0.4 respectively) and K‐EPAR < μ‐EPAR. High permeability limestones with dominant intergranular porosity cannot be discriminated from low permeability microporous carbonates. The petrophysical classes derived from elastic properties are shown to be distinct from reservoir property‐driven rock types. In the present case, a seismic‐based poro‐elastic model does not match the reservoir property model. Hence, a sedimentary facies model for the studied carbonates cannot accurately represent the petrophysical properties, which are determined by pores types and pore network architecture.