Considerable effort has been devoted to the development of simulation algorithms for facies modeling, whereas a discussion of how to combine those techniques has not existed. The integration of multiple geologic data into a three-dimensional model, which requires the combination of simulation techniques, is yet a current challenge for reservoir modeling. This article presents a thought process that guides the acquisition and modeling of geologic data at various scales. Our work is based on outcrop data collected from a Jurassic carbonate ramp located in the High Atlas mountain range of Morocco. The study window is 1 km (0.6 mi) wide and 100 m (328.1 ft) thick. We describe and model the spatial and hierarchical arrangement of carbonate bodies spanning from largest to smallest: (1) stacking pattern of high-frequency depositional sequences, (2) facies association, and (3) lithofacies. Five sequence boundaries were modeled using differential global position system mapping and light detection and ranging data. The surface-based model shows a low-angle profile with modest paleotopographic relief at the inner-to-middle ramp transition. Facies associations were populated using truncated Gaussian simulation to preserve ordered trends between the inner, middle, and outer ramps. At the lithofacies scale, field observations and statistical analysis show a mosaiclike distribution that was simulated using a fully stochastic approach with sequential indicator simulation. This study observes that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The selection and implementation of different techniques customized for each level of the stratigraphic hierarchy will provide the essential computing flexibility to model carbonate settings. This study demonstrates that a scale-dependent modeling approach should be a common procedure when building subsurface and outcrop models.