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Quantitative interpretation using facies-based seismic inversion

Ehsan Zabihi Naeini and Russell Exley
Quantitative interpretation using facies-based seismic inversion
Interpretation (Tulsa) (May 2017) 5 (3): SL1-SL8


Quantitative interpretation (QI) is an important part of successful exploration, appraisal, and development activities. Seismic amplitude variation with offset (AVO) provides the primary signal for the vast majority of QI studies allowing the determination of elastic properties from which facies can be determined. Unfortunately, many established AVO-based seismic inversion algorithms are hindered by not fully accounting for inherent subsurface facies variations and also by requiring the addition of a preconceived low-frequency model to supplement the limited bandwidth of the input seismic. We apply a novel joint impedance and facies inversion applied to a North Sea prospect using broadband seismic data. The focus was to demonstrate the significant advantages of inverting for each facies individually and iteratively determine an optimized low-frequency model from facies-derived depth trends. The results generated several scenarios for potential facies distributions thereby providing guidance to future appraisal and development decisions.

ISSN: 2324-8858
EISSN: 2324-8866
Serial Title: Interpretation (Tulsa)
Serial Volume: 5
Serial Issue: 3
Title: Quantitative interpretation using facies-based seismic inversion
Affiliation: Ikon Science, London, United Kingdom
Pages: SL1-SL8
Published: 201705
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 7
Accession Number: 2017-074487
Categories: Economic geology, geology of energy sourcesApplied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. block diags., sects., sketch maps
Secondary Affiliation: Summit Exploration and Production, GBR, United Kingdom
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2017, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 201739
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