2018/01/25 by A. Hobé, Alex Hobé, D. Vogler +9 · 1 citation
Engineering · Environmental Science · Mathematics · Physics and Astronomy · #Algorithm #Computer science #Engineering #Flow (mathematics) #Flow network #Fluid dynamics #Fracture (geology) #Geology #Geometry #Geotechnical engineering #Graph #Groundwater flow and contamination studies #Hydraulic Fracturing and Reservoir Analysis #Intersection (aeronautics) #Materials science #Mathematical optimization #Mathematics #Mechanics #Path (computing) #Physics #Range (aeronautics) #Shortest path problem #Soil and Unsaturated Flow #Theoretical computer science #Volumetric flow rate #msc:8604 #msc:8608 #physics.geo-ph
paper · pdf · doi:10.1016/j.advwatres.2018.10.002
arxiv created 2018/01/25 · openalex created_date 2018/02/02 · openalex publication_date 2018/10/02 · crossref created 2018/10/02 · arxiv updated 2018/11/14 · crossref issued 2018/12/01 · crossref published 2018/12/01 · crossref published-print 2018/12/01 · crossref deposited 2019/03/18 · crossref indexed 2025/10/11 · openalex updated_date 2026/08/05
To enable fast uncertainty quantification of fluid flow in a discrete fracture network (DFN), we present two approaches to quickly compute fluid flow in DFNs using combinatorial optimization algorithms. Specifically, the presented Hanan Shortest Path Maxflow (HSPM) and Intersection Shortest Path Maxflow (ISPM) methods translate DFN geometries and properties to a graph on which a max flow algorithm computes a combinatorial flow, from which an overall fluid flow rate is estimated using a shortest path decomposition of this flow. The two approaches are assessed by comparing their predictions with results from explicit numerical simulations of simple test cases as well as stochastic DFN realizations covering a range of fracture densities. Both methods have a high accuracy and very low computational cost, which can facilitate much-needed in-depth analyses of the propagation of uncertainty in fracture and fracture-network properties to fluid flow rates.