Facies Heterogeneities in a Ramp Carbonate Reservoir Analogue: A New High‐resolution Approach for 3d Facies Modelling

Abstract

In contrast to the conventional view that facies distribution patterns on carbonate ramps are relatively simple, outcrop analogue studies point to a high degree of internal facies complexity. Depending on the diagenetic overprint, this complex pattern may result in reservoir compartmentalization due to the presence of interflow baffles. The often subseismic scale heterogeneities may not be included in conventional reservoir modelling. In order to evaluate how facies heterogeneities in shoal reservoirs can be modelled realistically, this paper presents a facies modelling workflow which includes a new approach to the design of training images for multiple‐point statistics (MPS). The workflow was developed in the course of a reservoir outcrop analogue study of a Ladinian (Middle Triassic) coquinadominated shoal complex in SW Germany which was deposited on an epicontinental, gently inclined carbonate ramp. The data set was based on an intensive field study and includes 3D facies and sequence stratigraphic analyses of the largest shoal complex in the Quaderkalk Formation (Upper Muschelkalk). This several metre thick shoal complex represents a subseismic scale, bioclast‐rich reservoir analogue and has a very heterogeneous facies pattern. Integrating 1D facies logs and sequence stratigraphic trends from tens of outcrop sections and cores, two nested 3D geocellular facies models were produced: (i) a large‐scale (30 × 30 km) model based on truncated Gaussian simulation (TGS); this formed the basis for (ii) a smaller‐scale (10 × 10 km), more detailed model based on multiple point statistics. In addition, a new approach for training image design was developed to honour small‐scale sequence stratigraphic trends and lateral facies patterns observed in modern analogues. Compared to facies patterns in modern analogues, the large‐scale model presents geologically‐feasible facies distribution patterns and geometries, and in addition shows a vertical facies distribution which is similar to the observed sequence stratigraphic architecture of the outcrop data‐set used. Due to the new training image design, the final small‐scale model has a distribution pattern of facies heterogeneities which looks similar to modern facies distributions in the offshore UAE and thus represents a valuable method of producing realistic reservoir facies models. The modelling workflow and the new approach for training image design presented will help to reduce uncertainties in the understanding and modelling of subsurface reservoirs by using a systematic combination of outcrop data and modern analogues, with the consistent application of sequence stratigraphic principles. In addition, this study emphasises the importance of careful training image design, derived from modern analogues, which can be used as realistic inputs in order to optimize multiple point simulations, and which may be applied to producing bioclastic reservoirs such as those located on the Arabian Plate or offshore Brazil.

Modelling the coupled heterogeneities of the lacustrine microbialite-bearing carbonate reservoir of the Yacoraite Formation (Salta, Argentina)

“…Such problematics of scale and representativeness were already emphasized by several authors who proposed different approaches. For example, in order to realistically simulate different heterogeneity levels in shoal reservoirs, Petrovic et al [2018] used two nested 3D geo-cellular facies models: (1) a large-scale (30 × 30 km) model based on truncated Gaussian simulation (TGS), forming the basis for (2) a smaller scale (10 × 10 km), more detailed model based on multiple point statistics. Amour et al [2013] also proposed a step-by-step methodology to simulate different orders of stratigraphic sequences and lithofacies.…”

Asymmetry of an epicontinental basin—facies, cycles, tectonics and hydrodynamics: The Triassic Upper Muschelkalk, South Germanic Basin

“…Additionally, 18 logged quarries and 15 logged borehole cores generated by previous studies (Braun, 2003;Köhrer et al, 2010;Kostic & Aigner, 2004;Palermo et al, 2010Palermo et al, , 2012Petrovic & Aigner, 2017;Petrovic et al, 2018;Ruf & Aigner, 2004) were revaluated by visiting outcrops and proof-checking existing logs to incorporate them into this study. Field logs were digitized and visualized in WellCad 5.0.…”

“…This study draws on a detailed stratigraphic framework stemming from nearly 200 years of scientific research within the German Muschelkalk Basin (von Alberti, 1834;Aust, 1969;Paul, 1936;Vollrath, 1955a,b,c;Wagner, 1913), three decades of modern sedimentology and sequence stratigraphic studies (Adams & Diamond, 2017;Aigner, 1985;Aigner & Bachmann, 1992;Aigner, Hornung, Junghans, & Pöppelreiter, 1999;Franz, Henniger, & Barnasch, 2013;Franz et al, 2015;Köhrer, Heymann, Prousa, & Aigner, 2010;Kostic & Aigner, 2004;Palermo, Aigner, Nardon, & Blendinger, 2010;Palermo, Aigner, Seyfang, & Nardon, 2012;Petrovic & Aigner, 2017;Petrovic, Aigner, & Pontiggia, 2018;Ruf & Aigner, 2004;Vecsei & Duringer, 2003) and includes new and/or revised outcrop and borehole data (this study). While these previous modern studies provide an extensive and unique database for the Upper Muschelkalk, they only do so for selected palaeogeographic locations and stratigraphic intervals.…”

Three-Dimensional Modeling and Fluid Flow Simulation for the Quantitative Description of Permeability Anisotropy in Tidal Flat Carbonate

“…Therefore, distinguishing the spatial and temporal patterns of sedimentary strata in the rock record provides insights into the controls on the permeability anisotropy in subsurface reservoirs (Meyer et al, 1996;Amour et al, 2011;Purkis and Vlaswinkel, 2012;Eltom et al, 2013;Stanley et al, 2014;Rankey et al, 2018). Previous works in modern tidal flat environments and in their equivalent strata in the rock record have recognized various geological parameters that can be used to develop predictive facies models that facilitate the understanding of permeability anisotropy in these environments (Verwer et al, 2009;Palermo et al, 2010;Amour et al, 2011;Petrovic et al, 2018).…”