Integration of FWI-derived reflectivity in seismic interpretation

Abstract Full-waveform inversion (FWI) processing provides an improved and higher-resolution velocity model. This study focuses on how to use FWI products in seismic interpretation. One such product is FWI-derived reflectivity (FDR), which often has better illumination than migrated seismic images. We want to go beyond structural interpretation and utilize FDR data in reservoir characterization (e.g., fault imaging, resolution, and amplitude fidelity). FWI can be performed up to the maximum frequency available in the input seismic data. However, in the case of our study area in offshore Trinidad, the FDR data set is based on acoustic FWI with frequency only up to 10 Hz. While comparing amplitude extractions from full-stack and FDR data, we observe complementary amplitude distribution. Similar complementary information is found when we decompose the data in frequency bands (higher-frequency migrated seismic data and lower-frequency FDR data). We discuss the integration of the FDR volume in seismic interpretation with data examples. We combine FDR data with full-stack seismic data in two ways to generate new attributes for reservoir mapping and to reduce vertical and lateral uncertainty.

Authors

Institutions

Publication Details

Journal
The Leading Edge
Published
2024-12-01
DOI
https://doi.org/10.1190/tle43120836.1
Citations
4
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
2.14
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integration of FWI-derived reflectivity in seismic interpretation

Dhananjay Kumar, Ali Rahmat
4 citations
The Leading Edge
Seismic Imaging and Inversion Techniques
2.14
article

Integration of FWI-derived reflectivity in seismic interpretation

Dhananjay Kumar, Ali Rahmat
article en
4 citations

Abstract

Abstract Full-waveform inversion (FWI) processing provides an improved and higher-resolution velocity model. This study focuses on how to use FWI products in seismic interpretation. One such product is FWI-derived reflectivity (FDR), which often has better illumination than migrated seismic images. We want to go beyond structural interpretation and utilize FDR data in reservoir characterization (e.g., fault imaging, resolution, and amplitude fidelity). FWI can be performed up to the maximum frequency available in the input seismic data. However, in the case of our study area in offshore Trinidad, the FDR data set is based on acoustic FWI with frequency only up to 10 Hz. While comparing amplitude extractions from full-stack and FDR data, we observe complementary amplitude distribution. Similar complementary information is found when we decompose the data in frequency bands (higher-frequency migrated seismic data and lower-frequency FDR data). We discuss the integration of the FDR volume in seismic interpretation with data examples. We combine FDR data with full-stack seismic data in two ways to generate new attributes for reservoir mapping and to reduce vertical and lateral uncertainty.

The Leading EdgeVol. 43(12)
BP (United Kingdom) (GB), Port of Spain General Hospital (TT), College of Science, Technology and Applied Arts of Trinidad and Tobago (TT), Hanby Environmental (United States) (US), University of the Southern Caribbean (TT), Caribbean Public Health Agency (TT), BP (United States) (US)
Openalex Percentile: Top 13%
Seismic Imaging and Inversion Techniques
2.14
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Integration of FWI-derived reflectivity in seismic interpretation — Dhananjay Kumar, Ali Rahmat · The Leading Edge (2024) | TGRS Research Map | TGRS