Discrete Fracture Network (DFN) models have advanced considerably, yet challenges remain for capturing attribute variation and uncertainty across scales. We highlight problems using examples from shale hydrocarbon reservoirs, and propose methods to tackle them. Adequate treatment of spatial organization is perhaps the most problematic gap in many DFN models. Analysis of spatial organization in horizontal image logs using a newly developed method yields insight on how to populate models by recognizing distinct patterns of clustering or even spacing. Fracture fill is absent or inadequately treated in most DFN models. We show recent progress on fill prediction, how fill history modifies fracture network flow characteristics and patterns, and how sealed fractures may govern potential interactions with hydraulic fractures. Heights and lengths remain difficult or impossible to measure in the subsurface and challenging to obtain from outcrops. To guide DFN construction, outcrop studies must extract meaningful length data and geomechanical models need to model the range of fracture sizes in 3D, simulate interfaces, and account for cement.
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Gaps in DFN Models and How To Fill Them
Paper presented at the 2nd International Discrete Fracture Network Engineering Conference, Seattle, Washington, USA, June 2018.
Paper Number: ARMA-DFNE-18-0857
Published: June 20 2018
Gale, Julia, Ukar, Estibalitz, and Stephen Laubach. "Gaps in DFN Models and How To Fill Them." Paper presented at the 2nd International Discrete Fracture Network Engineering Conference, Seattle, Washington, USA, June 2018.
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