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Near and far offset impedances: Seismic attributes for identifying lithofacies and pore fluids
Author(s) -
Mukerji Tapan,
Jørstad Arild,
Mavko Gary,
Granli John Reidar
Publication year - 1998
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/1998gl900187
Subject(s) - geology , offset (computer science) , lithology , electrical impedance , amplitude versus offset , reservoir modeling , acoustic impedance , seismology , stack (abstract data type) , facies , geotechnical engineering , petrology , amplitude , computer science , geomorphology , engineering , physics , optics , programming language , structural basin , electrical engineering
Reliably predicting lithologic and saturation heterogeneities is a key problem in reservoir characterization. This study shows how near and far offset seismic impedance can be used to classify lithologies and pore fluids. The near offset seismic stack approximates a zero offset section, giving an estimate of the normal incidence acoustic impedance (AI = ρV). The far offset stack gives an estimate of a V p /V S related elastic impedance (EI) attribute, equivalent to the acoustic impedance for non‐normal incidence. These attributes can be computed from log data. Well data can be used, prior to seismic inversions, to test the feasibility of using AI‐EI attributes for lithofacies identification. Bi‐variate AI‐EI probability distribution functions can be estimated from logs to obtain classification success rate for each facies. Success rate is a measure of the value of far‐offset data for reservoir characterization. Examples are presented from North Sea, Gulf of Mexico, and Australia.