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A new seismic attribute for ambiguity reduction in hydrocarbon prediction
Author(s) -
Liu Changcheng,
Ghosh Deva
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 - 10.1111/1365-2478.12367
Subject(s) - amplitude versus offset , ambiguity , seismic attribute , geology , seismic to simulation , amplitude , hydrocarbon exploration , bright spot , economic geology , lithology , seismic inversion , igneous petrology , offset (computer science) , data mining , algorithm , computer science , hydrogeology , petrology , seismology , engineering geology , metamorphic petrology , mathematics , geotechnical engineering , geophysics , programming language , physics , volcanism , azimuth , tectonics , geometry , quantum mechanics
Hydrocarbon prediction from seismic amplitude and amplitude‐versus‐offset is a daunting task. Amplitude interpretation is ambiguous due to the effects of lithology and pore fluid. In this paper, we propose a new attribute “ J ” based on a Gassmann–Biot fluid substitution to reduce ambiguity. Constrained by seismic and rock physics, the J attribute has good ability to detect hydrocarbons from seismic data. There are currently many attributes for hydrocarbon prediction. Among the existing attributes, far‐minus‐near times far and fluid factor are commonly used. In this paper, the effectiveness of these two existing attributes was compared with the new attribute. Numerical modelling was used to test the new attribute “ J ” and to compare “ J ” with the two existing attributes. The results showed that the J attribute can predict the existence of hydrocarbon in different porosity scenarios with less ambiguity than the other two attributes. Tests conducted with real seismic data demonstrated the effectiveness of the J attribute. The J attribute has performed well in scenarios in which the other two attributes gave inaccurate predictions. The proposed attribute “ J ” is fast and simple, and it could be used as a first step in hydrocarbon analysis for exploration.