3D modeling from outcrop data in a salt tectonic context: Example from the Inceyol minibasin, Sivas Basin, Turkey

Abstract

We have developed a 3D modeling strategy of the encased minibasin of Inceyol in Sivas (Turkey). The challenge lies in the combination of sparse outcrop data and the complex interpretive geometry of geologic structures that come from salt tectonics. We have succeeded in modeling the convoluted salt surface using an explicit indirect surface patch construction method followed by a manual mesh improvement. Then, we modeled the minibasin sediments with an implicit approach. The result highlighted the remarkable geometry of the convoluted salt horizon and its associated minibasin by extending in 3D the geologist's interpretive 2D sections. This case study proved that building complex geometries is feasible with the existing tools and a good expertise in the various geomodeling techniques. Our work also underlined the need for new methods to ease the modeling of such tectonic features from sparse data. We have developed a 3D view of the model thanks to WebGL technology, as well as downloadable data to constitute a reference case study.

3-D Structural geological models: Concepts, methods, and uncertainties

“…Heuristic approaches based on thickness considerations have been proposed to address this problem. (Caumon et al, 2013a;Collon-Drouaillet et al, 2015;Collon et al, 2016). Alternatively, in the case where enough data are available for the problem to be well posed, the increment of the scalar field can be estimated as differences to some reference value (Lajaunie et al, 1997;Chilès et al, 2004;Calcagno et al, 2008;De la Varga et al, 2018;Renaudeau et al, 2018).…”

“…With these criteria in mind, we now highlight some distinctions between explicit and implicit models, summarized in Table 1. We also refer to Jessell et al (2014) and to Collon et al (2016) for comparisons and discussions of the relative merits of the various numerical approaches.…”

“…As compared to surface-based methods, interpolation can also change the topology of the implicit surfaces. This may be a strength when the topology is unknown (e.g., for karst or ore body modeling), but may also be a problem when the topology should be controlled (for instance to prevent stratigraphic surfaces to form blobs), see (Collon et al, 2016). Another capability of implicit methods is to honor several types of structural data without any projection (Calcagno et al, 2008;Caumon et al, 2013a;Hillier et al, 2014).…”

Geological Objects and Physical Parameter Fields in the Subsurface: A Review

“…Implicit surfaces also offer very nice ways to consider geometric model perturbations needed to address inverse problems in geosciences (Cardiff and Kitanidis 2009;Caumon et al 2007;Noetinger 2013;Zheglova et al 2013). A major distinction between explicit and implicit surface models is about topological control: the surface topology has to be chosen before interpolation in explicit methods, whereas it emerges from the interpolation in implicit models, see also Collon et al (2016) for more discussions.…”

Assessing the workflow for regional-scale 3D geologic modeling: An example from the Sullivan time horizon, Purcell Anticlinorium East Kootenay region, southeastern British Columbia

“…These bodies have variable thicknesses, a wide range of shapes, and complex topologies with rare at depth constraints provided by sparse drillhole intercepts. Similar to working with salt bodies, these features prove difficult to model (Collon et al, 2016). Thicker accumulations of Moyie dikes, much more prevalent in Lower Aldridge turbidites, are imaged along the 2D seismic profiles (Cook and Van der Velden, 1995; Figure 11b), which provided anisotropy information and more textural information than discrete marker data used in modeling faults and horizons.…”