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3D GSMP

General surface multiple prediction

Superior imaging regardless of sparse, missing, or irregular field seismic data

3D GSMP general surface multiple prediction algorithm is a full-3D true-azimuth implementation of the surface-related multiple elimination (SRME) technique. It is used for accurately predicting complex multiples, including diffracted and scattered multiple energy.

Solution for complex imaging challenges

3D GSMP algorithm preserves double bounces and other complex primary events for removal with complementary techniques, such as conventional or shifted-apex Radon demultiple. This approach enables correctly migrating these events by using imaging algorithms, including reverse time migration (RTM), for the best-possible reservoir image.

Gulf of Mexico wide-azimuth data example.

Images performed by 3D GSMP algorithm over a common receiver gather. Highlighted areas show complex and diffracted surface multiples attenuated by our algorithm.

Suitable for all survey types: conventional, wide-azimuth, towed-streamer, ocean bottom seismic (OBS), single- and multivessel full azimuth acquisition, and land surveys.

High-amplitude surface multiple (left) is completely removed after 3D GSMP general surface multiple prediction is used in Coil Shootin acquisition.

Shot gather from a survey acquired with Coil Shooting single-vessel full-azimuth acquisition. The high-amplitude surface multiple (left) is removed after using 3D GSMP algorithm (right). Using this technique, the underlying primary data is preserved—eliminating the need for further multiple attenuation processing.

High-quality multiple modeling

Minimal preprocessing is required because interpolation, regularization, and extrapolation are conducted with the 3D GSMP prediction algorithm. To produce a high-quality multiple model, 3D GSMP algorithm realizes the multiples at true azimuth to ensure an accurate match with the multiples in the input data.

Optimal input data selection

In areas where there are multiple overlapping vintages of data or large infill volumes, datasets can differ in their signal-to-noise ratio, offset distribution, and other characteristics. The 3D GSMP algorithm uses the highest-grade input data to refine modeling of multiples for multisurvey and 4D or time-lapse seismic projects.

Malaysia 2020 Licensing Round

19,000 km2 of 3D broadband seismic data

Enhance your prospectivity assessments in Block SB 2T offshore Sabah, Malaysia.

Offshore Brazil Equatorial Margin

2D and 3D seismic data surveys

Make better-informed decisions in the Potiguar, Ceará, Barreirinhas, and Pará-Maranhão Basins.

Offshore Brazil Southern Basin

2D and 3D datasets from East Margin

Get newly reprocessed survey data from the Santos, Campos, and Espirito Santo Basins.

Extended Internal Multiple Prediction (XIMP)

Data-driven algorithm that ensures analysis integrity

Achieve a true-azimuth internal multiple model utilizing both seismic data and interpreted horizons.

Weighted Least-Squares Radon Transform

Improved attenuation of multiple energy

Optimize separation by delineating primaries and multiples based on differences in their moveout.

General Deterministic Water-Layer Demultiple

Effective attenuation of shallow-water-layer multiples

Overcome limitations of conventional demultiple approaches using a model-based method.

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Industry Article Multisensor Streamer Recording and Its Implications for Time-Lapse Seismic and Repeatability

3D dealiased, reconstructed, and deghosted pressure wavefield can be obtained that permits wavefield matching to prior positions.