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Sören Naumann
Imaging Specialist
Nearer, Denser, Longer The Barents Sea Solution
A Clearer Image
Location
- Location
- Hammerfest Basin, Barents Sea
- Survey year
- 2018
- Survey type
- 3D GeoStreamer
- Streamer configuration
- uHD3D, 16 x 56.25 m spread, 7 and 10 km streamers
- Source configuration
- Triple source
- Area
- 4 172 sq. km
The Barents Sea is one of the remaining frontier exploration areas on the Norwegian Continental Shelf (NCS). According to the Norwegian Petroleum Directorate (NPD) the Barents Sea accounts for around half of the undiscovered resources on the NCS. This area is considered highly prospective at several target depths, which makes GeoStreamer broadband technology uniquely suitable. A new ultra high-density 3D dataset (orange outline) adds to existing 2D and 3D seismic and EM data coverage in the area.
Challenge
The south-western Barents Sea is characterized by a complex geological regime, with a heterogeneous overburden and different target depths (arrows). The combination of relatively shallow water depths and a hard, rugose sea floor, creates a tremendous amount of noise. This complicates using reflections in FWI for velocity updates. A key challenge in producing an accurate image of the subsurface is creating a reliable velocity model. Refraction based FWI has become the standard tool for velocity model building in the Barents Sea. However, due to the lack of recorded long offsets, model depths have been limited. Identifying porous carbonate buildups and sands has previously been difficult on legacy seismic data.
Solution
- Data
- High Density GeoStreamer 3D
- Hyperbolic front end
- Improved near offsets
- Dense bin size
- 6.25 m x 9.375 m
- Imaging
- Up to 200 Hz
- Velocity model building
- PGS FWI using additional long offsets
- Increased model depth
- From 2.5 km to 4 km
In 2018 PGS and TGS utilized a novel acquisition setup for acquiring an ultra-high-density 3D seismic dataset in the Barents Sea, covering parts of the Hammerfest Basin and Finnmark Platform. In addition to 16 densely spaced streamers, three streamers were extended from 7 km to 10 km length, allowing the recording of deeper diving waves (refractions) and therefore enabling FWI to produce velocity updates to greater depths.
Diving Deeper with FWI from 10 km Streamers
7 km Streamers
10 km Streamers
With the unique, long offset streamer configuration deployed for this survey, a sufficient amount of diving waves from deeper geological layers were recorded. This resulted in an extension of the model update depth from approximately 2.5 to 4 km depth. With a maximum frequency of 15 Hz for the FWI, a great amount of detail is included in the velocity model.
Results
This acquisition configuration was developed to enable the best solution to resolve the challenges of the Barents Sea. Thanks to the additional long offset streamers and therefore increased model depth, detailed attribute maps can be extracted for both shallow and deep target horizons. The velocity contrasts captured in the depth velocity model allow accurate imaging of the subsurface without being biased by distortion effects caused by the shallow heterogeneous overburden. The velocities derived from FWI include valuable information for reservoir characterization where low velocities can be an indication for porous sands, karstified carbonates, hydrocarbons or high porosity areas in general.
FWI Captures Reservoir and Shallow Gas Cloud Goliat Field
Fast track KPSTM stack with FWI velocity overlay through the Goliat reservoir. At the reservoir level, the model shows a clear low velocity anomaly, potentially indicating a porous and hydrocarbon filled sand body.
Gas from the reservoir has leaked upwards via a complex series of faults and accumulated higher in the section. FWI resolves this shallow gas cloud effectively highlighting a potential shallow hazard in the area.
This velocity depth slice shows how FWI clearly delineates the actual extent of the gas cloud above parts of the Goliat field. The details and large velocity contrasts captured in the depth velocity model allow accurate imaging of the subsurface without being biased by distortion effects caused by the shallow heterogeneous overburden.
Correlation Between Velocity and Amplitude Indicates Hydrocarbon Accumulations
Velocity
Amplitude
These stacks highlight a section around Top Realgrunnen at a depth of around 2.5 km. Within each fault block, low velocity zones are present at the top of the structure. These anomalous velocities correlate well with the seismic amplitude brightening and highlight areas of a potential increase in fluid accumulation.
FWI velocity model overlaid on a KPSDM stack. Both amplitude and velocity anomalies correlate well and therefore this can be an indication of hydrocarbon accumulations at the
structural highs.
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