Gullfaks 4D seismic: 10 years of experience
Structured case brief
Gullfaks Main Field
Track pressure and saturation changes to identify bypassed oil, compartment behaviour, and better infill-well targets.
- Location
- North Sea, Norway
- Monitoring system
- Streamer
- Repeat interval
- 3 years
- Repeatability
- 23.5% (2016 re-processing)
- Main signal driver
- Saturation & Pressure
- Water depth
- 135m
Time-lapse interpretation supported multiple infill decisions and established 4D seismic as a recurring reservoir-management input.
A legacy acquisition system can still create material value when processing, uncertainty, and the decision question are managed together.
Gullfaks 4D seismic: 10 years of experience
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discovery record · reviewed 2026-08-03
Open source recordThe case supports repeated use of streamer 4D for reservoir-management decisions across a mature field and includes lessons from later reprocessing.
- Legacy survey repeatability is lower than modern permanent or node-based systems and requires careful separation of acquisition noise from reservoir change.
- Reported field value combines multiple decisions over time and should not be treated as a simple return estimate for another asset.
Decision context
Gullfaks is a mature, faulted North Sea field where reservoir compartments, water movement, and bypassed oil created repeated uncertainty for infill drilling. The value question was whether time-lapse seismic could reduce that uncertainty often enough to become part of routine asset management.
Monitoring approach
The field used repeated conventional streamer surveys rather than a permanent receiver system. This created repeatability constraints from changing geometry, weather, and acquisition conditions, so processing and interpretation had to separate reservoir change from survey differences.
Evidence
- Saturation and pressure response: Time-lapse amplitudes helped track water movement and depletion effects across fault blocks.
- Bypassed oil: The interpretation identified unswept compartments that were not sufficiently clear in the static model.
- Reprocessing value: Later processing improved the usability of legacy surveys and extended the decision value of the historical dataset.
Operational outcome
The field used 4D evidence to support infill-well planning and waterflood management. Over time, the workflow shifted from an experimental study to a recurring input into reservoir decisions.
Transferable lesson
High repeatability improves confidence, but it is not the only route to value. A project can extract useful 4D evidence from legacy streamer data when the expected signal, processing limits, and decision threshold are made explicit.
Community review
What supports this interpretation, and what limits transfer?
This section preserves technical feedback, counterexamples, and deployment lessons from the issue-backed forum. Maintainers may synthesize the strongest points into the two cards below.
Supporting signals
Maintainer synthesis- Landmark case that matured 4D seismic from research to standard practice.
- Massive value creation ($1B+), a key benchmark for 4D ROI.
Limits and counterexamples
Maintainer synthesis- Legacy streamer data has lower repeatability compared to modern PRM/OBN.
- Geologic complexity in some segments required intensive re-processing to extract the 4D signal.
4D Forum
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