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3‐D shallow‐water seismic survey evaluation and design using the focal‐beam method: a case study offshore Abu Dhabi
Author(s) -
Ishiyama Tomohide,
Blacquière Gerrit
Publication year - 2016
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 - 10.1111/1365-2478.12335
Subject(s) - geology , economic geology , amplitude , offset (computer science) , environmental geology , submarine pipeline , data acquisition , regional geology , sampling (signal processing) , geophysical imaging , amplitude versus offset , engineering geology , data quality , stack (abstract data type) , seismology , remote sensing , optics , computer science , engineering , geotechnical engineering , detector , metric (unit) , operations management , physics , metamorphic petrology , telmatology , programming language , operating system , volcanism , tectonics
ABSTRACT For 3‐D shallow‐water seismic surveys offshore Abu Dhabi, imaging the target reflectors requires high resolution. Characterization and monitoring of hydrocarbon reservoirs by seismic amplitude‐versus‐offset techniques demands high pre‐stack amplitude fidelity. In this region, however, it still was not clear how the survey parameters should be chosen to satisfy the required data quality. To answer this question, we applied the focal‐beam method to survey evaluation and design. This subsurface‐ and target‐oriented approach enables quantitative analysis of attributes such as the best achievable resolution and pre‐stack amplitude fidelity at a fixed grid point in the subsurface for a given acquisition geometry at the surface. This method offers an efficient way to optimize the acquisition geometry for maximum resolution and minimum amplitude‐versus‐offset imprint. We applied it to several acquisition geometries in order to understand the effects of survey parameters such as the four spatial sampling intervals and apertures of the template geometry. The results led to a good understanding of the relationship between the survey parameters and the resulting data quality and identification of the survey parameters for reflection imaging and amplitude‐versus‐offset applications.