CRS tomography and CRS gathers for improving 3D salt resolution in depth

Henning Trappe, Guido Gierse, Juergen Pruessmann, Eliakim Schuenemann, Philip Schlueter (TEEC)Alfredo Caballero, Rodolfo Ballesteros (Geoprocesados)

Gerardo Clemente (PEMEX CNPS)

OverviewA Common-Reflection-Surface (CRS) depth imaging workflow is demonstrated in a case study whichuses high-resolution CRS attribute volumes for improving the model building and imaging in salt geologyfor 3D seismic land data from Mexico. Initial CRS time processing provides both, an improved initialoutline of the salt body, and general information for constructing the depth model. CRS tomographyderives a smooth velocity depth model from the CRS attributes that is well suited as a reliable startingpoint for further depth model building in prestack depth migration (PreSDM). PreSDM also benefits fromthe CRS-based noise suppression and regularisation of the prestack data, which provides so-called CRSgathers by partial CRS stacking. The increased signal-to-noise ratio leads to clearer depth structuresespecially in zones of low fold or strong noise, and facilitates the iterative model refinement by a clearerdepth moveout. This CRS depth processing approach finally leads to a 3D PreSDM volume with astrongly increased resolution and signal-to-noise ratio both above and below the salt (Figure 1).

Figure 1 PreSDM inline sections from conventional workflow (left), versus CRS workflow: Note the increaseddepth resolution due to CRS velocity model building and CRS prestack data enhancement in the low-fold tertiaryoverburden, at the top of salt, at the salt body definition, and in the sub-salt reflector continuity.

CRS method and attributesThe CRS method was developed within the concept of macro-model independent imaging (e.g.Gelchinsky 1988, Jger et al. 2001). CRS stacking assumes local reflector elements with dip andcurvature in the subsurface that give rise to the seismic reflections. The corresponding CRS stackingparameters, the so-called CRS-attributes, accordingly comprise the wavefield dip together with wavefrontcurvatures observed at the surface. They define hyperbolic CRS stacking surfaces that extend acrossseveral CMP locations, and thus collect high-fold contributions from the prestack data.

Initial depth model building by CRS tomographyThe densely sampled CRS attributes from timeprocessing contain abundant information on thesubsurface, making them well suited for a fastreconstruction of a reliable initial velocity-depthmodel by CRS tomography, or NIP-wave tomography(Duveneck 2004). In this 3D data case from Mexico,the CRS tomography model corresponds much betterto the structures of an associated PostSDM volume,than a Dix model (Figure 2). This improvement ismainly due to the inversion of structural dip from theemergence angle contained in the inverted CRSattributes. The smooth CRS tomography model isespecially well suited for depth migration, serving as an advanced initial model for further depthprocessing, that cuts down the number of PreSDM and model updating cycles significantly.CRS gathers for depth imaging and model updateSince the CRS attributes describe the kinematics of seismic events in detail, they can also be used for alocal regularization and noise suppression in the prestack data by partial CRS stacking before depthmigration (Eisenberg et al. 2008). A CRS-based PreSDM strategy can include a regularisation of theoffset distribution, and of the azimuth distribution. Figure 1 compares the result of a conventio-nalstrategy of model building and Kirchhoff PreSDM to a CRS-based approach. The noise reduction bypartial CRS stacking reveals additional structural features, and especially improves the salt definition.ConclusionsCRS time processing provides detailed local information on the seismic reflection events in the form ofkinematic wavefield attributes. These so-called CRS attributes can be inverted into a depth model by CRStomographic inversion which is much better constrained than vertical Dix inversion. The CRStomography model can be used as a good initial approximation of the subsurface velocity for both,poststack depth migration (PostSDM) and further model update in prestack depth migration (PreSDM).Significant CRS-based improvements in depth imaging are achieved by using CRS attributes for dataregularization and noise suppression in PreSDM.AcknowledgementsWe thank PEMEX for the permission to present their data.

ReferencesDuveneck, E., 2004, Tomographic determination of seismic velocity models with kinematic wavefield attributes:

Phd thesis, University of Karlsruhe, Logos Verlag Berlin.Eisenberg-Klein, G., J. Pruessmann, G. Gierse, H. Trappe, 2008, Noise reduction in 2D and 3D seismic imaging by

the CRS method: The Leading Edge, 27, 258-265.Gelchinsky, B., 1988, The common reflecting element (CRE) method (non-uniform asymmetric multifold system):

ASEG/SEG Conference, Exploration Geophysics, Extended Abstracts, 71-75.Jaeger, R., Mann, J., Hoecht, G., Hubral, P., 2001: Common-reflection-surface stack: Image and attributes.

Geophysics 66 (1), 97-109.

Figure 2: Dix model (left) versus CRS tomographymodel (right) with CRS-PostSDM sections.