Seismic Processing

We are committed to delivering broadband data of the highest quality – ready for quantitative interpretation and tailored to suit the needs of our clients.

We have developed key technologies in noise removal, deghosting and designature, 3D demultiple, data regularisation, imaging and post-migration processing to meet this goal.

Shot gather before and after DUG Deblend. Polarcus XArray™ – Penta source data before and after DUG Deblend.

Brute stack before and after DUG Deblend. Polarcus XArray™ – Penta source data before and after DUG Deblend.

DUG Deblend

Realise the full potential of blended acquisition without compromising data quality or amplitude fidelity with our inversion-based deblending algorithm.

DUG Broad

DUG’s deghosting technology: DUG Broad removes the amplitude and phase distortion caused by both source and receiver ghosts.

Before and After DUG Broad. Shot gather before and after source and receiver deghosting using DUG Broad. Note that the deghosted result has also been redatumed to mean sea level.

Input (left) and two zero-phased and debubbled datasets, using far field signatures (FFS) derived from the NFH recordings (right) and a single modelled FFS (centre). Each dataset has been bandpass filtered between 1-6 Hz. The water bottom horizon is shown dipping to the left near the top of the section. Accurate zero-phasing is achieved using the FFS derived from the NFH data, but not with the modelled FFS.

Source Signature Deconvolution using Near Field Hydrophone (NFH) data.

DUG recognises the use of high-quality relevant signatures in the effective deconvolution of the source wavelet from seismic data as an important part of high fidelity broadband processing. We use the NFH data to calculate notional signatures for every shot and subsequently use these for signature deconvolution and zero-phasing.

DUG SWAMI

DUG SWAMI (Shallow Water Attenuation of Multiples by Inversion) is our 3D multiple attenuation algorithm for shallow water settings. DUG SWAMI overcomes the issue of the lack of recorded near offsets by predicting these near offsets from the information present in the recorded multiples.

Shot gather and autocorrelation before and after DUG SWAMI. DUG SWAMI efficiently attenuates the shallow water multiples, including the reverberations present on the near offsets. (Data courtesy of Polarcus)

Brute stack and autocorrelation before and after DUG SWAMI. DUG SWAMI efficiently attenuates the shallow water multiples, including the reverberations present on the near offsets. (Data courtesy of Polarcus)

Stack section before (left) and after (right) DUG IME. In this case the water bottom horizon is acting as the multiple generator. Time range of the data shown is from 5300-6400 ms. (Data courtesy Spectrum Geo)

Stack section before interbed demultiple (left) and multiples predicted by DUG IME (right). In this case the water bottom horizon is acting as the multiple generator. Time range of the data shown is from 5300-6400 ms. (Data courtesy Spectrum Geo)

DUG IME (Interbed Multiple Elimination)

DUG’s interbed multiple elimination process – DUG IME – accurately models and subtracts interbed multiples. It can be used to predict the multiple model from a single generator or it can be applied in a cascaded (top-down) manner to eliminate interbed multiples resulting from a number of different generators.

DUG Pre-processing

In addition to the standard pre-processing tools, a full suite of conditioning algorithms is available to improve the final images and prepare the gathers for AVO and QI studies.

Before and after acquisition footprint removal. Timeslice (400 ms) before (left) and after (right) acquisition footprint removal.

Before and after anisotropic azimuthal moveout. Timeslice before (left) and after (right) anisotropic azimuthal moveout correction. This data is from Australia’s southern margin (courtesy Origin Energy).

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