Proceedings ArticleDOI
5D anti-aliasing interpolation: Application on an unconventional shale play
TLDR
Chiu et al. as discussed by the authors proposed a new anti-aliasing minimum weighted norm interpolation (MWNI) method to overcome the aliasing artifacts in MWNI and applied it to a field data acquired from an unconventional shale play and carried out a comprehensive evaluation of interpolated data through the processes of pre-stack analyses, prestack time migration, and prestack depth migration.Abstract:
Fourier-based minimum weighted norm interpolation (MWNI) has been widely used to regularize land seismic data. It is relatively fast computationally, and easily extends to higher dimensions. However, it has difficulty interpolating regular missing data that are spatially aliased. Chiu and Anno (2012) proposed a new anti-aliasing MWNI method to overcome the aliasing artifacts in MWNI. Their interpolation scheme expands the capability of the conventional MWNI to handle aliased data that are often associated with steeply dipping structures, and produces more reliable interpolation results. A 2D synthetic data example clearly shows that anti-aliasing MWNI outperforms the conventional MWNI method. We apply it to a field data acquired from an unconventional shale play and carry out a comprehensive evaluation of interpolated data through the processes of pre-stack analyses, pre-stack time migration, and pre-stack depth migration. The 5D interpolation yields considerable uplifts to the improvements of image qualities. The pre-stack gathers after the 5D interpolation are more suitable for azimuthal AVO and velocity analysis.read more
Citations
More filters
Journal ArticleDOI
5D dealiased seismic data interpolation using nonstationary prediction-error filter
TL;DR: The results show that although the NPEF method is less effective than the rank-reduction method in interpolating irregularly missing traces especially in the case of a low signal-to-noise ratio, it outperforms theRank-Reduction method on interpolating an aliased 5D data set with regularly missing traces.
Proceedings ArticleDOI
Minimum weighted norm interpolation with an angular weighted deconvolved prior
TL;DR: In this paper, the angular deconvolved prior MWNI (AdMWNI) was proposed, which further stablizes the previous angular weighted prior (AwMWNI), which is significantly better than the conventional MWNI method.
Proceedings ArticleDOI
Fast antialiasing Fourier inversion for 5D seismic data regularization
Proceedings ArticleDOI
6D Interpolation by Incorporating Angular Weight Constraints into 5D MWNI
Mark Ng,Xi-Shuo Wang,Dan Negut +2 more
TL;DR: In this article, an additional dimension along multiangular directions is added to the 5D minimum weighted norm interpolation (MWNI) to guide the a priori model in the frequencywavenumber domain.
Journal ArticleDOI
Efficient 3D seismic data acquisition in deep water
Joakim O. Blanch,Jessica Hapney,Margaret Ishak,Aurora Rodriguez,Andreas Laake,Nick Moldoveanu +5 more
TL;DR: A dual-source vessel acquisition configuration is employed, which doubles the acquisition rate and significantly reduces cost and, with the help of modern processing techniques, produces images with the same quality as a conventional configuration.
References
More filters
Journal ArticleDOI
Minimum weighted norm interpolation of seismic records
Bin Liu,Mauricio D. Sacchi +1 more
TL;DR: In this article, a wavefield reconstruction scheme for spatially band-limited signals is proposed, where a finite domain regularization term is included to constrain the solution to be spatially bounded and imposes a prior spectral shape.
Journal ArticleDOI
3D interpolation of irregular data with a POCS algorithm
Ray Abma,Nurul Kabir +1 more
TL;DR: The Gerchberg-Saxton projection onto convex sets (POCS) algorithm as mentioned in this paper interpolates irregularly populated grids of seismic data with a simple iterative method that produces high-quality results.
Journal ArticleDOI
Five-dimensional interpolation: Recovering from acquisition constraints
TL;DR: In this article, a sparseness constraint on the 4D spatial spectrum obtained from frequency slices of five-dimensional windows is proposed to improve the convergence of the inversion algorithm.
Journal ArticleDOI
Multistep autoregressive reconstruction of seismic records
TL;DR: In this article, a two-stage algorithm is proposed to reconstruct the unaliased part of the data spectrum using a Fourier method (minimum-weighted norm interpolation) and prediction filters for all the frequencies are extracted from the reconstructed low frequencies.
Proceedings ArticleDOI
Rank-Reduction-Based Trace Interpolation
TL;DR: In this article, a family of multidimensional filters to suppress random noise based on matrix-rank reduction of constant-frequency slices is described. But the authors do not consider the problem of rank reduction when some, perhaps most of the matrix elements are unknown.