Integration of OBS data and surface data for OBS multiple removal

Verschuur, D.J.; Neumann, Erik

doi:10.1190/1.1820762

Cited by 15 publications

(7 citation statements)

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“…The RM map of Bingham & Shakeshaft shows a circular structure of about the size of their beam (∼ 2 • ) where RM ≈ −5 rad m −2 , in a region where RM s are −1 rad m −2 < ∼ RM < ∼ 0 rad m −2 . Verschuur (1968) reobserved this region at higher angular resolution (∼ 40 ′ ) with the 250ft MkI telescope at Jodrell Bank at 408 MHz. Verschuur found that it is a ring-like structure of low polarized intensity (50% less than in its surroundings) with a radius of a few degrees, and with a small region (about one beam) of almost zero polarization at the southwestern edge of the ring.…”

Section: Introductionmentioning

confidence: 76%

Multi-frequency polarimetry of the Galactic radio background around 350 MHz

Haverkorn¹,

Katgert²,

Bruyn

2003

A&A

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Abstract. With the Westerbork Synthesis Radio Telescope (WSRT), multi-frequency polarimetric images were taken of the diffuse radio synchrotron background in a ∼5• × 7• region centered on (l, b) = (161• ) in the constellation of Auriga. The observations were done simultaneously in 5 frequency bands, from 341 MHz to 375 MHz, and have a resolution of ∼5.0 × 5.0 cosec δ. The polarized intensity P and polarization angle φ show ubiquitous structure on arcminute and degree scales, with polarized brightness temperatures up to about 13 K. On the other hand, no structure at all is observed in total intensity I to an rms limit of 1.3 K, indicating that the structure in the polarized radiation must be due to Faraday rotation and depolarization mostly in the warm component of the nearby Galactic interstellar medium (ISM). Different depolarization processes create structure in polarized intensity P. Beam depolarization creates "depolarization canals" of one beam wide, while depth depolarization is thought to be responsible for creating most of the structure on scales larger than a beam width. Rotation measures (RM) can be reliably determined, and are in the range −17 < ∼ RM < ∼ 10 rad m −2 with a non-zero average RM 0 ≈ −3.4 rad m −2 . The distribution of RMs on the sky shows both abrupt changes on the scales of the beam and a gradient in the direction of positive Galactic longitude of ∼1 rad m −2 per degree. The gradient and average RM are consistent with a regular magnetic field of ∼1 µG which has a pitch angle of p = −14• . There are 13 extragalactic sources in the field for which RMs could be derived, and those have |RM| < ∼ 13 rad m −2 , with an estimated intrinsic source contribution of ∼3.6 rad m −2 . The RMs of the extragalactic sources show a gradient that is about 3 times larger than the gradient in the RMs of the diffuse emission and that is approximately in Galactic latitude. This difference is ascribed to a vastly different effective length of the line of sight. The RMs of the extragalactic sources also show a sign reversal which implies a reversal of the magnetic field across the region on scales larger than about ten degrees. The observations are interpreted in terms of a simple single-cell-size model of the warm ISM which contains gas and magnetic fields, with a polarized background. The observations are best fitted with a cell size of 10 to 20 pc and a ratio of random to regular magnetic fields B ran /B reg ≈ 0.7 ± 0.5. The polarization horizon, beyond which most diffuse polarized emission is depolarized, is estimated to be at a distance of about 600 pc.

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Section: Introductionmentioning

confidence: 76%

Multi-frequency polarimetry of the Galactic radio background around 350 MHz

Haverkorn¹,

Katgert²,

Bruyn

2003

A&A

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“…After deghosting, regularization and interpolation, the next step is to predict the multiple models, which we do for SRME and MWD individually. With the regularized/interpolated streamer data, , and OBN data, , we obtain the SRME model ( Figure 1a) as follows (Ikelle, 1999;Verschuur and Neumann, 1999):…”

Section: Methodsmentioning

confidence: 99%

“…However, it requires significant modifications to work with OBN data due to the sparse sampling of the receivers (nodes) and the significant datum difference between sources and receivers. To address such issues, a modified SRME scheme was proposed by Ikelle (1999) and Verschuur and Neumann (1999), in which OBN and streamer data were combined to predict surface-related multiples for OBN data (Zhong et al, 2014). Like surfacestreamer SRME, the OBN SRME also suffers from limited offset and azimuth coverage of streamer data and limited bandwidth due to an extra source wavelet.…”

Section: Introductionmentioning

confidence: 99%

Joint SRME and model-based water-layer demultiple for ocean-bottom node

Huang

Wang

Yang

et al. 2016

SEG Technical Program Expanded Abstracts 2016

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Ocean bottom node (OBN) SRME that combines OBN and streamer data is known to be an effective way to predict surface-related multiples in OBN data. However, the available streamer data often have limited offset/azimuth coverage. Additionally, the double source wavelets due to the convolution of OBN and streamer data limit the bandwidth (loss of low and high frequency) of the predicted multiples. OBN model-based water-layer demultiple (MWD) overcomes such limitations and is a good complement of OBN SRME; MWD replaces the streamer data with the water-bottom Green's function that has no offset/azimuth limitation and keeps the full bandwidth of the input data. With Gulf of Mexico (GOM) OBN data over the Atlantis field, we illustrate the benefit of joint SRME and MWD over SRME alone with the improved attenuation of low-frequency multiples and water layer-related multiples.

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“…The prediction of multiples on sea-bed data by combining streamer and sea-bed data using the SRME method was introduced by Verschuur and Neumann (1999) and applied to well-sampled 2D acquisition geometries. Zhong et al (2014) applied this method to a 3D OBN survey in deep water Gulf of Mexico, combining data from individual OBN nodes with streamer data from a wideazimuth (WAZ) survey.…”

Section: Introductionmentioning

confidence: 99%

OBN multiple attenuation using OBN and towed-streamer data: Deepwater Gulf of Mexico case study, Thunder Horse Field

Castelan

Kostov

Saragoussi

et al. 2016

SEG Technical Program Expanded Abstracts 2016

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We report case study results for attenuation of free-surface multiples from deep-water ocean bottom node (OBN) data using a data-driven multiple prediction method that combines OBN and towed-streamer data through multidimensional convolution, similar to the well-known surface-related multiple elimination (SRME) method. We illustrate the properties of the proposed multiple prediction method using synthetic and field data and note that availability of suitably acquired and processed streamer data is critical to the success of this approach. In our case study, we have data from five streamer surveys with offsets up to 10 km and broad range of azimuths. Correspondingly, the results of data-driven multiple attenuation are good for the OBN data with offsets up to about the maximum offset of the streamer data. We also compute a model-based prediction of the free-surface multiples using the anisotropic velocity model and prior depth images available for this field. The data-driven and the model-based approaches of predicting free-surface multiples have complementary properties. We combine models computed with both approaches to attenuate free-surface multiples in the OBN upgoing and downgoing data, as needed for subsalt imaging.

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Integration of OBS data and surface data for OBS multiple removal

Cited by 15 publications

References 0 publications

Multi-frequency polarimetry of the Galactic radio background around 350 MHz

Multi-frequency polarimetry of the Galactic radio background around 350 MHz

Joint SRME and model-based water-layer demultiple for ocean-bottom node

OBN multiple attenuation using OBN and towed-streamer data: Deepwater Gulf of Mexico case study, Thunder Horse Field

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