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The redatuming approach, often referred to as up-down deconvolution, is well-known and applied to remove water-layer and source-signature effects in seabed seismic surveys. The upgoing wavefield can be expressed as the multidimensional convolution of the downgoing wavefield with the earth’s reflectivity. Consequently, deconvolving the downgoing wavefield from the upgoing wavefield, gives us the earth’s reflectivity response. The deconvolution process requires solving a multidimensional integral equation but, in a laterally invariant medium, after that wavefields are decomposed into plane-wave components, deconvolution can be enormously simplified if performed as a spectral division in the Fourier or Radon domain. It has been experimentally observed that deconvolution carried out one plane-wave component at a time gives good results, even in the presence of complex subsurface structures, provided that the seabed is relatively flat. When this geological condition is not satisfied, the same problem can be formulated in terms of interferometric redatuming using multidimensional deconvolution, where the integral equation solution is achieved by introducing the point-spread function concept. We present a methodology based on numerical simulations to determine when the integral equations associated with the problem of up-down deconvolution can be solved under the assumption of shift-invariant wavefields and when it requires multidimensional deconvolution. In the latter case, we propose a regularized inverse procedure that mitigates the numerical problems due to the typically ill-posed nature of the inversion and that, combined with an interpolation strategy for the downgoing, enables the application of multidimensional deconvolution within the range of sampling scenarios considered so far. We apply this methodology to synthetic data, and we discuss on the potential to extend up-down deconvolution to a broader range of geological conditions.
The redatuming approach, often referred to as up-down deconvolution, is well-known and applied to remove water-layer and source-signature effects in seabed seismic surveys. The upgoing wavefield can be expressed as the multidimensional convolution of the downgoing wavefield with the earth’s reflectivity. Consequently, deconvolving the downgoing wavefield from the upgoing wavefield, gives us the earth’s reflectivity response. The deconvolution process requires solving a multidimensional integral equation but, in a laterally invariant medium, after that wavefields are decomposed into plane-wave components, deconvolution can be enormously simplified if performed as a spectral division in the Fourier or Radon domain. It has been experimentally observed that deconvolution carried out one plane-wave component at a time gives good results, even in the presence of complex subsurface structures, provided that the seabed is relatively flat. When this geological condition is not satisfied, the same problem can be formulated in terms of interferometric redatuming using multidimensional deconvolution, where the integral equation solution is achieved by introducing the point-spread function concept. We present a methodology based on numerical simulations to determine when the integral equations associated with the problem of up-down deconvolution can be solved under the assumption of shift-invariant wavefields and when it requires multidimensional deconvolution. In the latter case, we propose a regularized inverse procedure that mitigates the numerical problems due to the typically ill-posed nature of the inversion and that, combined with an interpolation strategy for the downgoing, enables the application of multidimensional deconvolution within the range of sampling scenarios considered so far. We apply this methodology to synthetic data, and we discuss on the potential to extend up-down deconvolution to a broader range of geological conditions.
The ultra-shallow water-depth and hard water bottom of offshore Abu Dhabi are responsible for generating a complex multiple wavefield. Removing this energy is critical for accurate imaging of the subsurface. Almheiri et al. (2022), demonstrated the effectiveness of up/down deconvolution to attenuate multiple energy on Ocean bottom sensor (OBS) data from offshore Abu Dhabi. In this paper we detail recent advances to this workflow, leading to enhanced imaging results from offshore Abu Dhabi. Amundsen (2001) showed that deconvolving the up-going wavefield by the down-going wavefield produces an estimation of the Earth's reflectivity series. While this technique gives a step-change in demultiple results from OBS data offshore Abu Dhabi, it suffers from high noise levels – particularly in the higher frequencies. Advances in linear noise removal enable the attenuation of mud-roll from the input data without harming the water-wave – an essential ingredient to up/down deconvolution. Removal of the mud-roll consequently enables better attenuation of shear-wave noise from the vertical geophone component. The advanced workflow leads to improved wavefield separation and superior data for up/down deconvolution.The advanced pre-processing flow was applied to an OBS dataset from Offshore Abu Dhabi and used as input to up/down wavefield deconvolution. The up/down deconvolution results were benchmarked against a previous result from the same OBS dataset, without the application of the improved pre-conditioning flow. Reverse time migration (RTM) imaging using both datasets showed a clear improvement in signal-to-noise ratio on the new results, with improved reflector focusing, especially at the reservoir target level. Frequency band splitting showed better phase alignment across the bandwidth in the new data compared to the legacy results. These results confirm that advanced de-noising techniques, allowing for the removal of high-amplitude mud-roll and shear-wave noise, without harming the water-wave, refraction energy or primary reflections, leads to improved wavefield separation and consequently improved up/down deconvolution results. The improved results exhibit reduced noise content, better event focusing and improved phase alignment across the frequency spectrum.
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