Curriculum

Carlo Janna graduated in Civil Engineering at the University of Padova in October 2nd, 2003 with 109 points over 110 and in the same University he got his PhD defending a thesis entitled "Numerical modeling of the mechanical behavior of regional faults in the geological sequestration of anthropogenic CO2 sequestration". Since December 2011 he is assistant professor at the Department ICEA. The main scientific interests concern on one hand the mathematical and numerical modeling of the mechanics of porous media in both saturated and unsaturated conditions with specific applications in subsurface hydrology and petroleum industry, on the other the numerical linear algebra. His main activity is the development and implementation of numerical models based on the Finite Element method for the simulation of subsurface coupled and uncoupled geomechanical and fluid dynamical processes in the exploitation of deep aquifer or reservoir resources. As to the linear algebra, Carlo Janna studies and develops numerical techniques for the solution of large sparse linear systems and eigenproblems and more specifically iterative methods and preconditioners. For sequential computers, he studied and developed several ad hoc preconditioners for the solution to specific problems arising in subsurface simulations. From 2010 to 2012, Carlo Janna joined the HPC research projects PARPSEA (PARallel Preconditioners for large Size Engineering Applications), SCALPREC (SCALable PREConditioners), OPTIDAS (OPTImization and Data ASSimilation) e SPREAD (Scalable PREconditioners for Advanced Discretizations) studying and developing new preconditioners for massively parallel computers.

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  Publications

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  Research Activity

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  Proposals of thesis

 1- Defining a better heuristic for the Newton method in reservoir simulation

Typical reservoir simulation involves the repeated solution in time of highly non-linear systems of equations as several quantities, such as relative permeability, capillary pressure, elastic storage, depend on the unknown solution at the current time. The Newton method, on its side, is an
iterative scheme requiring the solution of a sequence of linearized system at each step, which are typically solved through preconditioned iterative methods, e.g., algebraic multigrid (AMG).

In principle, since the systems change at every Newton step, the most conservative strategy is that of setting-up a new preconditioner for every non-linear solve. However, since the preconditioner set-up stage could be quite expensive, a more efficient alternative could be that of computing a new preconditioner or updating an existing one only when the system matrix changes significantly.

The present proposal focuses on studying optimal choices for preconditioner reset or update in reservoir simulation. The thesis will be carried out in collaboration with ENI and will involve an extensive use of Echelon, the ENI-proprietary reservoir simulation model, on modern parallel computers. The student will learn how to run an up-to-date reservoir simulator on real or realistic field, will learn how to work on a parallel computer using a load-leveler and finally will learn the basis of parallel programming and numerical methods.

External co-supervisors:
Alberto Cominelli, Mario Tacconi, ENI E&P
Leonardo Patacchini, Stone Ridge Technology

 

2 - Improving the iterative solution of linear systems arising from reservoir simulation models

Reservoir simulation software requires the solution in time of several non-linear systems of the equations, which are typically solved with the Newton method. Newton, in turn, involves the solution of a sequence of large and sparse linear systems which are very often solved through algebraic multigrid (AMG). Though being extremely efficient, the time spent for the AMG solve accounts for up to 90% of the total simulation time in real world problems, so that it is of paramount importance increasing its efficiency.

For instance, Echelon, the reservoir simulation software used in ENI, relies on the linear solver in the GAMPACK library which guarantees excellent performance. However, other solver packages are available offering promising improvements in the context of AMG, such as aggressive coarsening techniques, extended and long-range prolongations, filtering or advanced smoothers.

The aim of this thesis is exploring the effectiveness of these approaches, currently implemented in other packages such as Hypre (https://computing.llnl.gov/projects/hypre-scalable-linear-solvers-multigrid-methods) or Chronos (https://www.m3eweb.it/chronos) and evaluate their impact on real world reservoir and geomechanical models.

The thesis will be carried out in collaboration with ENI and will involve the use of GAMPACK and other linear solvers on modern parallel computers. The student will learn how to use and customize state-of-the-art parallel linear solvers, will learn how to work on a parallel computer using a load-leveler and, finally, will learn the basis of parallel programming.

External co-supervisors:
Alberto Cominelli, Silvia Monaco, Mario Tacconi, ENI E&P
Leonardo Patacchini, Stone Ridge Technology