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A texture‐based region growing algorithm for volume extraction in seismic data
Author(s) -
OrozcodelCastillo M.G.,
CárdenasSoto M.,
OrtizAlemán C.,
CouderCastañeda C.,
UrrutiaFucugauchi J.,
TrujilloAlcántara A.
Publication year - 2017
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12381
Subject(s) - volume (thermodynamics) , geology , cube (algebra) , extraction (chemistry) , principal component analysis , algorithm , economic geology , amplitude , computer science , texture (cosmology) , hydrogeology , artificial intelligence , mathematics , geometry , image (mathematics) , telmatology , geotechnical engineering , chemistry , physics , chromatography , quantum mechanics
We present a novel approach to automated volume extraction in seismic data and apply it to the detection of allochthonous salt bodies. Using a genetic algorithm, we determine the optimal size of volume elements that statistically, according to the U ‐test, best characterize the contrast between the textures inside and outside of the salt bodies through a principal component analysis approach. This information was used to implement a seeded region growing algorithm to directly extract the bodies from the cube of seismic amplitudes. We present the resulting three‐dimensional bodies and compare our final results to those of an interpreter, showing encouraging results.