Structural interpretation of sparse fault data using graph theory and geological rules Fault data interpretation

Abstract : Structural uncertainties arise partly from the association of sparse fault interpretations made from 2D seismic lines or limited outcrop observations. We propose a graph formalism to describe the problem of associating spatial fault evidence. A combinatorial analysis shows that the number of association scenarios is related to the Bell number and increases exponentially. This makes the complete exploration of the uncertainties computationally highly challenging. We formulate prior geological knowledge as numerical rules to reduce the number of scenarios and to make structural interpretation more re-peatable and objective. We use the Bron-Kerbosch graph algorithm to detect the major possible structures. This framework opens the way to a numerically assisted exploration of uncertainties during structural interpretation.
Complete list of metadatas

Cited literature [64 references]  Display  Hide  Download

https://hal.univ-lorraine.fr/hal-01879697
Contributor : Guillaume Caumon <>
Submitted on : Monday, September 24, 2018 - 11:07:56 AM
Last modification on : Monday, August 12, 2019 - 10:42:02 AM
Long-term archiving on : Tuesday, December 25, 2018 - 3:25:26 PM

File

GodefroyStochasticMathGeol_Pre...
Files produced by the author(s)

Identifiers

Citation

Gabriel Godefroy, Guillaume Caumon, Gautier Laurent, François Bonneau. Structural interpretation of sparse fault data using graph theory and geological rules Fault data interpretation. 2018. ⟨hal-01879697⟩

Share

Metrics

Record views

147

Files downloads

248