The modeling & simulation (M&S) research theme focuses mainly on fundamental research of algorithms and mathematical models of computer graphics, visualization, and visual analytics, about static and dynamic descriptions in the data. Projects in M&S are either stand-alone or derived from/related to projects from the other four research themes.

(a) Vital Brazil et al. '10a; Proença et al. '07; (b) Streit et al. '05;
(c) Brosz et al. [
'06, '07b]; (d) Roberts et al. '10; (e) Hamdi et al. '15a.

To date, M&S projects from our group are organized into four categories:

  1. Mapping techniques including (1.1) Decal-mapping for multi-variate visualization (Rocha et al. 17a, from RT-3: Vis&VA); and (1.2) Texture synthesis for illustrative patterns (dos Passos et al. '10, from RT-1: NPR);
  2. Volume modeling for interactive volume data manipulation and visualization, in collaboration with medical researchers and clinicians (Chen et al. '08, also RT-2: SBIM,Patent: US20090322748), (Roberts et al. ['09, '10], Patent: US20110074780 A1);

  3. Geometric and topological modeling including four sub-categories: (3.1) Point-set sampling for reconstruction and rendering of implicit surfaces -- i.e., Proença et al. '07, Vital Brazil et al. '10a (from RT-1: NPR); (3.2) Modeling and rendering by-example for curve synthesis (Brunn et al. '07, from RT-1: NPR ), stippling marks (Kim et al. '09 from RT-1: NPR), and terrain synthesis (Brosz et al. ['06, '07b]); (3.3) Procedural modeling for plant growth (Streit et al. '05), in collaboration with botanical scientists; and (3.4) Multiresolution filters for image and mesh re-construction and focus+context visualization (Hasan et al. '15, also RT-3: Vis&VA);

  4. Computational methods for bridging geoscience and petroleum engineering. One of the major challenges in modeling petroleum reservoirs is to be able to integrate, visualize, and analyze various data of different types, which is susceptible to high uncertainty. This process is not a straightforward task and usually requires non-trivial and time-consuming workflows. Examples of such data integrations can be demonstrated in terms of SAGD modeling, well test calibration in conventional reservoirs or numerical rate transient modeling in tight and shale reservoirs. The primary objective of this research is to be able to create and adapt modern workflows to efficiently integrate dynamic and static data. Modern geostatistical simulations in combination with flow simulations are usually required to ensure consistent integrations. In addition, to enhance the integration workflow and reduce the computational costs, efficient optimization techniques are also needed to bring the computational efficiency to a next level. Our research include five sub-categories: (4.1) Geostatistical simulations with conditioning hard and soft data (Hamdi & Costa Sousa '16, Khani et al. ['17, '18 (a, b)]); (4.2) Geological well-test simulation (Hamdi et al. ['14, '15a]) including gas condensate system (Hamdi et al. ['13, '15b]); (4.3) Efficient optimization and uncertainty quantification for reservoir modeling (Hajizadeh et al. '13, Hamdi et al. ['15c, '17(a, b, c), '18]); (4.4) Global sensitivity analysis of complex reservoir models (Karami Moghadam et al. ['16, '18], with '18 from RT-3: Vis&VA); and (4.5) Flow diagnostics in unstructured grids integrated with geo-modeling (Zhang et al. ['17 (a, b), '18] , Rapid Reservoir Modeling project).

M&S Publications

G&PE = Geoscience & Petroleum Engineering venue

Theses (6)
Journal Articles (7)
Conference Papers (13)

Brosz J.





Chen H-L.



Hasan M.


In Prog.

Khani H.

PhD (G&PE)

In Prog.

Olsen L.



Roberts M.



Chen et al. '08
Hamdi et al. ['15 (
a, b), '17a] (G&PE)
Hasan et al. '15
Proença et al. '07
Streit et al. '05

Brosz et al. ['06, '07b]
Hajizadeh et al. '13 (G&PE)
Hamdi et al. [
'13, '15c, '17b] (G&PE)
Hamdi & Costa Sousa '16 (G&PE)
Karami Moghadam et al. '16 (G&PE)
Khani et al. '18a (G&PE)
Roberts et al. '10
Zhang et al. ['17 (
a, b), '18] (G&PE)

Ext Abst. / Posters (6)

Hamdi et al. ['14, '17c, '18] (G&PE)
Khani et al. [
'17, '18b] (G&PE)
Roberts et al. '09