Conceptual limitations of existing gridding technologies often lead to undesirable simplifications to the modeling of structurally complex areas, and consequently poor predictions. We present a structural modeling and gridding workflow that limits these modeling compromises. A volume-based 3D structural model based on fault and horizon surfaces is constructed from input data that has undergone basic quality checking using a variety of techniques. The critical step in the grid creation is the definition of a flattened (‘depositional’) space that deforms the structural model mesh under mechanical constraints. A 3D ‘unstructured’ grid is created in the depositional space, based on ‘cutting’ a property-populated, regular cuboidal grid by the geological discontinuities. The tectonic consistency and better preservation of geodetic distance make the flattened space ideal for a range of property modeling approaches. The forward-deformation of the grid into true geological space tends to preserve the layer-orthogonality of the grid columns and makes the grid more suited to numerical simulation approximations. The final grid is unstructured, high quality and an accurate representation of the input structural model. The 3D structural model, depositional space transform and grid geometries all provide valuable information on the structural quality of the input data. The stretching and deforming of the orthogonal local axes in the transformation from depositional space to geological space are used to focus further effort on structural model quality assurance (QA). The key step in generating accurate property population and simulation models is the application of QA metrics on the grid geometry; the transformation from depositional space to geological space is used to generate a set of grid properties that highlight potential structural inconsistencies or data quality issues back in the structural model. We present several examples based on a range of structurally complex models, and demonstrate the downstream impact of applying this QA workflow throughout the stages of input data validation, structural model creation and grid creation.

Historically it has been a challenge to rapidly produce a geomodel that can honor the detailed form of complex faulting and folding, while enabling sensible property modeling and that is tailored to fluid flow simulations. In structurally complex areas, the construction of accurate 3D geological models is often impeded by the complexity of the fault framework, the resulting layer segmentation, "multi-z" horizons in compressive settings and steeply dipping to overturned layers. In particular, standard geocellular models, such as pillar grids, may fail to honor complex structural features. To address those issues, methodologies using a mapping between the geological space and a 3D parametric space — often referred to as depositional space — have been described in the literature for geological grid construction and property population. Using case examples of structurally complex settings, we illustrate a depositional unstructured grid construction workflow. Compared to known methodologies, the depositional space is computed using a geomechanically-based approach. We illustrate that the methodology allows for complex structural configurations to be effectively modeled and transformed into a geocellular model honoring the full structural complexity. Our depositional unstructured model can then be populated with properties and used directly for flow simulations.

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As the oil and gas industry is moving toward tapping reserves in more complex structural environments, there comes the challenge for the reservoir modeling platform to accurately and robustly build and simulate a model to aid in making more trustworthy reserve estimates and field development plans. The 3D geocellular model sits at the core of an integrated seismic-to-simulation workflow, within which one can characterize and predict the behavior of reservoirs and can make confident quantitative decisions about one's assets. In structurally complex areas, the construction of accurate 3D models is often impeded by fundamental limitations of standard geocellular modeling technologies. With these limitations in mind, a new cut-cell unstructured grid has been developed that honors the geological structure precisely, enables accurate property modeling in a flattened, un-faulted, pseudo-depositional space, and can be simulated directly in a next-generation simulator; we call this unstructured grid built in depositional space a ‘depogrid’. The polyhedral, cut-cell nature of the depogrid arises when the regularly gridded volume in depositional space is cut by the structural model features (faults and unconformities) before being forward-deformed into geological space. By construction, the grid cell columns are orthogonal to the local stratigraphy, yet they can accurately represent complex structures and volumes, independent of the grid resolution. A next-generation high resolution reservoir seamlessly consumes the globally unstructured grid topology, with the structural complexity and non-neighbor connections, and honors the flow dynamics accurately. This ensures a more geologically consistent simulation model, realistic parameters to tune for history matching workflows and the ability to make reliable predictions. We present some particular reservoir modeling and simulation considerations where the depogrid approach improves on typical gridding technologies. The seismic-to-simulation workflow is then applied to several structural examples to demonstrate how the depogrid is best suited to model the geological structure and properties in a variety of reservoirs and subsequently improves the accuracy and efficiency of field development planning and risk mitigation.