Common-Reflection-Surface Stack for Converted Waves

The finite-offset (FO) common-reflection-surface (CRS) stack has been shown to be able to handle not only P-P or S-S but also arbitrarily converted reflections. It can provide different stack sections such as common-offset (CO), common-midpoint (CMP) and common-shot (CS) sections with significantly increased signal-to-noise ratio from the multi-coverage pre-stack seismic data in a data-driven way. It is our purpose in this paper to demonstrate the performance of the FO CRS stack on data involving converted waves in inhomogeneous layered media. In order to do this we apply the FO CRS stack for common-offset to a synthetic seismic data set involving P-P as well as P-S converted primary reflections. We show that the FO CRS stack yields convincing improvement of the image quality in the presence of noisy data and successfully extracts kinematic wavefield attributes useful for further analyses. The extracted emergence angle information is used to achieve a complete separation of the wavefield into its P-P and P-S wave components, given the FO CRS stacked horizontal and vertical component sections.     

Model-independent Travel-time Attributes for 2-D, Finite-offset Multicoverage Reflections

— In this paper, we provide a 5-parameter stacking formula to transform 2-D prestack data into a particular common-offset section. This requires the knowledge of the near-surface velocity only and it is expected that ray theory holds to describe primary reflections. The earth model can be arbitrarily inhomogeneous. The new stacking approach can be viewed as a generalization of the 3-parameter common-reflection-surface (CRS) stack, by which 2-D multicoverage data are stacked into a simulated zero-offset section. The new 5-parameter formula can handle P-P, P-S and S-S reflections.     

Operator-oriented CRS interpolation

In common‐reflection‐surface imaging the reflection arrival time field is parameterized by operators that are of higher dimension or order than in conventional methods. Using the common‐reflection‐surface approach locally in the unmigrated prestack data domain opens a potential for trace regularization and interpolation. In most data interpolation methods based on local coherency estimation, a single operator is designed for a target sample and the output amplitude is defined as a weighted average along the operator. This approach may fail in presence of interfering events or strong amplitude and phase variations. In this paper we introduce an alternative scheme in which there is no need for an operator to be defined at the target sample itself. Instead, the amplitude at a target sample is constructed from multiple operators estimated at different positions. In this case one operator may contribute to the construction of several target samples. Vice versa, a target sample might receive contributions from different operators. Operators are determined on a grid which can be sparser than the output grid. This allows to dramatically decrease the computational costs. In addition, the use of multiple operators for a single target sample stabilizes the interpolation results and implicitly allows several contributions in case of interfering events. Due to the considerable computational expense, common‐reflection‐surface interpolation is limited to work in subsets of the prestack data. We present the general workflow of a common‐reflection‐surface‐based regularization/interpolation for 3D data volumes. This workflow has been applied to an OBC common‐receiver volume and binned common‐offset subsets of a 3D marine data set. The impact of a common‐reflection‐surface regularization is demonstrated by means of a subsequent time migration. In comparison to the time migrations of the original and DMO‐interpolated data, the results show particular improvements in view of the continuity of reflections events. This gain is confirmed by an automatic picking of a horizon in the stacked time migrations.     

Common-reflection-surface (CRS) stack for common offset

We provide a data-driven macro-model-independent stacking technique that migrates 2D prestack multicoverage data into a common-offset (CO) section. We call this new process the CO common-reflection-surface (CRS) stack. It can be viewed as the generalization of the zero-offset (ZO) CRS stack, by which 2D multicoverage data are stacked into a well-simulated ZO section. The CO CRS stack formula can be tailored to stack P-P, S-S reflections as well as P-S or S-P converted reflections. We point out some potential applications of the five kinematic data-derived attributes obtained by the CO CRS stack for each stack value. These include (i) the determination of the geometrical spreading factor for reflections, which plays an important role in the construction of the true-amplitude CO section, and (ii) the separation of the diffractions from reflection events. As a by-product of formulating the CO CRS stack formula, we have also derived a formula to perform a data-driven prestack time migration.