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Complementary Data-driven Methods for Interbed Demultiple for Land and OBC Geometries
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Abstract
Interbed multiples occur in all types of seismic datasets and are difficult to address. These multiples can appear very similar to primaries due to comparable velocities, and may be difficult to differentiate from primary energy and/or distort the amplitude of primary reflections. Interbed multiple prediction (IMP)-based on the 1D earth assumption and applied to post-migration gathers has been partially successful in removing these complex multiples, but cannot be considered a full solution as it is applied late in the seismic data processing sequence, limiting the derivation of an accurate velocity, which is critical for imaging, time or depth, and for further reservoir characterization.
This problem is further compounded in onshore and OBC seismic data. These, in general, have wide acquisition geometries and suffer from poor sampling, especially for shallow reflectors, which adds to the challenges of multiple attenuation. In this paper, two complimentary data-driven multiple attenuation techniques are discussed (Deterministic interbed demultiple (DID) and Extended interbed multiple prediction (XIMP)). These address the various challenges posed by the complexity of acquired data and the generated interbed multiples.
We demonstrate complementary approaches to address the challenges of interbed multiple attenuation in land and OBC environment and show a case studies from seismic datasets. As there is little or no discrimination in velocity or dip, multiples cannot be easily attenuated using conventional methods based on periodicity and velocity or dip discrimination. To address the specific challenges of each survey, a careful analysis of the data is required and usually a combination of methods and approaches is the best solution. DID and XIMP are methods that naturally complement each other, allowing compensation for the limitations of land and OBC geometries and addressing the full interval of the multiple generators from top to bottom of the section.
Theory
In this paper, two methods to attenuate interbed multiples are discussed.Deterministic interbed demultiple (DID).Extended interbed multiple prediction (XIMP).
DID is a deterministic method of predicting the internal multiples that are created by a single layer in the earth's subsurface. Originally designed to handle shallow water-column-related multiples (Moore and Bisley, 2006), it was later adapted to attenuate interbed multiples. The prediction is accomplished by a wavefield extrapolation. The method predicts all multiples created by a targeted layer as shown in Figure 1. DID requires a model of the layer, including estimated reflection coefficients at top and bottom. The main assumption of the method is that the layer has a moderate complexity within the 3D gather. In other words, DID relies on a local 1D assumption for the layer. Nevertheless, it does account properly for the non-periodic moveout of multiples in traces at non-zero offsets. Because the layer is assumed to be flat, there are no azimuthal effects accounted for by the multiple prediction. DID works with 3D gathers and outputs multiple models for each trace of the input data. Overall, it can form a reliable 3D model as long as geological complexity is moderate.
Title: Complementary Data-driven Methods for Interbed Demultiple for Land and OBC Geometries
Description:
Abstract
Interbed multiples occur in all types of seismic datasets and are difficult to address.
These multiples can appear very similar to primaries due to comparable velocities, and may be difficult to differentiate from primary energy and/or distort the amplitude of primary reflections.
Interbed multiple prediction (IMP)-based on the 1D earth assumption and applied to post-migration gathers has been partially successful in removing these complex multiples, but cannot be considered a full solution as it is applied late in the seismic data processing sequence, limiting the derivation of an accurate velocity, which is critical for imaging, time or depth, and for further reservoir characterization.
This problem is further compounded in onshore and OBC seismic data.
These, in general, have wide acquisition geometries and suffer from poor sampling, especially for shallow reflectors, which adds to the challenges of multiple attenuation.
In this paper, two complimentary data-driven multiple attenuation techniques are discussed (Deterministic interbed demultiple (DID) and Extended interbed multiple prediction (XIMP)).
These address the various challenges posed by the complexity of acquired data and the generated interbed multiples.
We demonstrate complementary approaches to address the challenges of interbed multiple attenuation in land and OBC environment and show a case studies from seismic datasets.
As there is little or no discrimination in velocity or dip, multiples cannot be easily attenuated using conventional methods based on periodicity and velocity or dip discrimination.
To address the specific challenges of each survey, a careful analysis of the data is required and usually a combination of methods and approaches is the best solution.
DID and XIMP are methods that naturally complement each other, allowing compensation for the limitations of land and OBC geometries and addressing the full interval of the multiple generators from top to bottom of the section.
Theory
In this paper, two methods to attenuate interbed multiples are discussed.
Deterministic interbed demultiple (DID).
Extended interbed multiple prediction (XIMP).
DID is a deterministic method of predicting the internal multiples that are created by a single layer in the earth's subsurface.
Originally designed to handle shallow water-column-related multiples (Moore and Bisley, 2006), it was later adapted to attenuate interbed multiples.
The prediction is accomplished by a wavefield extrapolation.
The method predicts all multiples created by a targeted layer as shown in Figure 1.
DID requires a model of the layer, including estimated reflection coefficients at top and bottom.
The main assumption of the method is that the layer has a moderate complexity within the 3D gather.
In other words, DID relies on a local 1D assumption for the layer.
Nevertheless, it does account properly for the non-periodic moveout of multiples in traces at non-zero offsets.
Because the layer is assumed to be flat, there are no azimuthal effects accounted for by the multiple prediction.
DID works with 3D gathers and outputs multiple models for each trace of the input data.
Overall, it can form a reliable 3D model as long as geological complexity is moderate.
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