Modeling Stratigraphic and Spatial Heterogeneity of a Lower Jurassic Carbonate Ramp Outcrop Using Multiple Point Statistics
Outcrop exposures offer continuity, correlation, and resolution of geological data well beyond that of the subsurface. However, questions remain regarding the value added from digitization of detailed outcrop data, especially when addressing reservoir challenges. To test this, measured sections, photomosaic mapping, DGPS, and LIDAR data were collected along a 38 km dip-view exposure of Lower Jurassic carbonate ramp strata in the High Atlas of Morocco, and converted into a 3D model using multiple point statistics (MPS). The modeling goal was to capture multiple scales of vertical and lateral heterogeneity within the ramp system during both transgressive (TST) and highstand (HST) conditions, and for each of the facies belts observed (inner, middle, outer, transgressive drape, and basinal ramp settings).
The MPS approach uses combinations of hard data constraints (i.e. well data) and soft geologic concepts (i.e. depositional models) to populate 3D grid space. The inputs for MPS simulation are training images and Facies Probability Cubes, which together capture juxtaposition relationships, spatial proportions, and the spatial likelihoods of the facies belts [in plan view and cross section] whilst honoring hard data constraints (measured sections). Using this technique, the stratigraphic and spatial heterogeneity observed in the outcrop was successfully simulated, including ramp progradation and retrogradation at different hierarchical scales, facies belt contraction and expansion, and TST draping of HST deposits with variable updip extents.
This outcrop-based modeling effort provides parameters and strategies that can be incorporated into less-constrained subsurface-based models. For example, dynamic facies belt contraction and expansion was modeled using high degrees of interfingering, which enabled migration of facies belts across the grid while preserving juxtaposition rules. Vertical facies belt partitioning was captured using only two training images (TST and HST) and subdividing the grid into according regions. Another key finding was generating the TST training image by merging HST and ‘transgressive drape’ training images, allowing maximum flooding sediments to blanket the extent of the ramp and juxtapose with all HST facies belts. In addition to these best practices, high-resolution outcrop models help identify the impact of data density on the preservation of geological heterogeneity that controls subsurface flow.
AAPG Search and Discovery Article #90090©2009 AAPG Annual Convention and Exhibition, Denver, Colorado, June 7-10, 2009