Permanent Faculty: Sinésio Pesco

Sinésio Pesco

PhD, Pontifícia Universidade Católica do Rio de Janeiro, Brasil, 1997
Office: 872
Position: Associate Professor
Phone: (21) 3527-1740
E-mail: sinesio
Computational Mathematics and Mathematics Applied to Industry.

Lattes CV | Personal Homepage

Sinésio Pesco is Associate Professor of the Department of Mathematics at PUC-Rio and his main research interests are in Computational Modeling, Scientific Visualization and Petroleum reservoir modeling. Since 1996, he has been working in reservoir characterization and research projects related to the oil industry. He received his PhD degree in Applied Mathematics at Pontificial Catholic University of Rio de Janeiro (PUC-Rio) in 1997.

He worked at SCI Institute - Univertity of Utah in 2004, Scientific visualization group at Lawrence Livermore National Laboratory in July/September 2003 and NYU - New York University - Polytechnic Institute in 2012 as a visiting professor.

Research Results

Together with Abelardo Barreto and Renan Vieira Bela, I have been worked on injectivity test which consists a procedure in the area of formation evaluation used to collect information about oil reservoir. Important reservoir properties can be estimated by this technique, such as equivalent permeability. More specifically we worked on the development of new models involving vertical, horizontal and multi-layer wells [Bela 2019].

Together with Lis Custódio (PUC-Rio), Cláudio Silva (NYU-Poly) and Thiago Etiene (SCI-Institute), we studied the Marching Cubes 33 algorithm to ensure the extracted isosurface topology of the trilinear interpolant. The first results were presented in [Custódio et al. 2013] and follow in [Custodio et ,. Al 2019].


An extended triangulation to the Marching Cubes 33 algorithm
Lis Ingrid Custodio, Sinesio Pesco and Claudio Silva
Journal of the Brazilian Computer Society 25:6, pp. 1-18 (June 2019)

Modeling falloff tests in multilayer reservoirs
Renan Vieira Bela, Sinesio Pesco and Abelardo Barreto
Journal of Petroleum Science and Engineering 174 , pp. 161-168 (March 2019)