On eigenvalue distribution of constraint-preconditioned symmetric saddle point matrices

This paper is devoted to the analysis of the eigenvalue distribution of two classes of block preconditioners for the generalized saddle point problem. Most of the bounds developed improve those of previous published works. Numerical results onto a realistic test problem give evidence of the effectiveness of the estimates on the spectrum of preconditioned matrices

Numerical models for the large-scale simulation of fault and fracture mechanics

The possible activation of pre-existing faults and the generation of new fractures in the subsurface may play a critical role in several fields of great social interest, such as the management and the exploitation of groundwater resources, especially in arid areas, the hydrocarbon recovery and storage, and the monitoring of the seismic activity in the Earth’s crust. The sliding and/or opening of a fault can create preferential leakage paths for the pore fluid escape, causing a matter of great concern in the process of storing fluids and hydrocarbons underground. The most challenging effect connected to a fault activation is the possible earthquake triggering. Many earthquakes associated with the production and injection of fluids have been recently reported. Similar issues arise also in the development of unconventional hydrocarbon reservoirs, that has recently experienced a dramatic increase thanks to the deployment of the “fracking” technology, which is based on the massive generation of fractures through the injection of fluids at high pressures. The use of this technique in densely populated areas has raised a large scientific debate on the possible connected environmental risks. The over-exploitation of fresh aquifers in arid regions has caused the generation of significant ground fissures. In this thesis, a novel formulation based on the use of Lagrange multipliers has been developed for the stable and robust numerical modeling of fault mechanics. A fault or fracture is simulated as a pair of inner surfaces included in a 3D geological formation where Lagrange multipliers are used to prescribe the contact constraints. The standard variational formulation of the contact problem with Lagrange multipliers is modified to take into account the energy dissipated by the frictional work along the activated fault portion. This term is computed by making use of the principle of maximum plastic dissipation, whose application defines the direction of the limiting shear stress vector. The novel approach has been verified against analytical solutions and applied in a number of real-world problems. In particular, we test the novel approach in four cases: (i) mechanics of two adjacent blocks, to investigate the numerical properties of the algorithm; (ii-iii) ground fractures due to groundwater withdrawal, with different geometries; (iv) fault reactivation in an underground reservoir subject to primary production and Underground Gas Storage cycles. The results are analyzed and commented. In the fourth case, the possible magnitude of the seismic events triggered by fault reactivation is computed, in order to evaluate whether underground human activities may generate seismicity. The application of the fault model to large-scale problems gives rise to a set of sparse discrete systems of linearized equations with a generalized non-symmetric saddle point structure. The second part of this thesis is devoted to the development of efficient algorithms for the iterative solution of this kind of system. We focus on a preconditioning technique, denoted as “constraint preconditioning”, which exploits the native block structure of the Jacobian. The quality and performance of the preconditioner relies on two steps: (i) the preconditioning of the leading block and (ii) the Schur complement computation. In this work, novel preconditioning techniques for the leading block based on a multilevel framework are developed and tested. The main idea behind the multilevel preconditioner is to improve the quality of the factorized approximate inverses borrowing the scheme of incomplete factorizations, thus introducing some sequentially in perfectly parallelizable algorithms. The proposed approach is robust, from a theoretical point of view, and very efficient in parallel environment. As to the latter point, i.e. the Schur complement computation, it can be done with the aid of different approximations. The main difference is whether the Jacobian is symmetrized or not. The computation can be founded on the FSAI approximation of the leading block inverse or on a physically-based block diagonal block algorithm. The Schur complement must be inverted, thus other possibilities come in. The approximate Schur complement can be inverted through FSAI, if symmetric, or an incomplete factorization, if non-symmetric, but it can also be solved exactly, thanks to a direct solver. The performances of the proposed algorithms are finally investigated and discussed in a set of real-world numerical examples