Parallel geothermal numerical model with faults and multi-branch wells - Archive ouverte HAL Access content directly
Journal Articles ESAIM: Proceedings and Surveys Year : 2018

Parallel geothermal numerical model with faults and multi-branch wells


To answer the need for an efficient and robust geothermal simulation tool going beyond existing code capabilities in terms of geological and physical complexity, we have started to develop a parallel geothermal simulator based on unstructured meshes. The model takes into account complex geology including fault networks acting as major heat and mass transfer corridors and complex physics coupling the mass and energy conservations to the thermodynamical equilibrium between the gas and liquid phases. The objective of this Cemracs project is to focus on well modeling which is a key missing ingredient in our current simulator in order to perform realistic geothermal studies both in terms of monitoring and in terms of history matching. The well is discretized by a set of edges of the mesh in order to represent efficiently slanted or multi-branch wells on unstructured meshes. The connection with the 3D matrix and the 2D fault network at each node of the well is accounted for using Peaceman's approach. The non-isothermal flow model inside the well is based on the usual single unknown approach assuming the hydrostatic and thermodynamical equilibrium inside the well. The parallelization of the well model is implemented in such a way that the assembly of the Jacobian at each Newton step and the computation of the pressure drops inside the well can be done locally on each process without MPI communications.
Fichier principal
Vignette du fichier
CemracsGeothermy-HAL.pdf (854.36 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01472944 , version 1 (21-02-2017)



Laurence Beaude, Thibaud Beltzung, Konstantin Brenner, Simon Lopez, Roland Masson, et al.. Parallel geothermal numerical model with faults and multi-branch wells. ESAIM: Proceedings and Surveys, 2018, ⟨10.1051/proc/201863109⟩. ⟨hal-01472944⟩
772 View
269 Download



Gmail Facebook Twitter LinkedIn More