Azimuth Moveout (AMO) for data regularization and interpolation. Application to shallow resource plays in Western Canada

Similar documents
P071 Land Data Regularization and Interpolation Using Azimuth Moveout (AMO)

Azimuth Moveout Transformation some promising applications from western Canada

Coherent partial stacking by offset continuation of 2-D prestack data

SEG/New Orleans 2006 Annual Meeting

3D angle gathers from wave-equation extended images Tongning Yang and Paul Sava, Center for Wave Phenomena, Colorado School of Mines

Residual move-out analysis with 3-D angle-domain common-image gathers

96 Alkhalifah & Biondi

Missing trace interpolation and its enhancement of seismic processes

G021 Subsalt Velocity Analysis Using One-Way Wave Equation Based Poststack Modeling

Prestack residual migration in the frequency domain

Stanford Exploration Project, Report 120, May 3, 2005, pages

Chapter 1. 2-D field tests INTRODUCTION AND SUMMARY

Angle Gathers for Gaussian Beam Depth Migration

Target-oriented wavefield tomography: A field data example

Wave-equation inversion prestack Hessian

Seismic reflection data interpolation with differential offset and shot continuation a

Source-receiver migration of multiple reflections

EARTH SCIENCES RESEARCH JOURNAL

Ray based tomography using residual Stolt migration

Generalized sampling and beyond Nyquist imaging

Selection of an optimised multiple attenuation scheme for a west coast of India data set

Directions in 3-D imaging - Strike, dip, both?

Equivalent offset migration: the implementation and application update

Seismic data interpolation with the offset continuation equation

Seismic reflection data interpolation with differential offset and shot continuation

3-D prestack migration of common-azimuth data

When is anti-aliasing needed in Kirchhoff migration? a

Stanford Exploration Project, Report 111, June 9, 2002, pages INTRODUCTION THEORY

IMAGING USING MULTI-ARRIVALS: GAUSSIAN BEAMS OR MULTI-ARRIVAL KIRCHHOFF?

Least-squares Wave-Equation Migration for Broadband Imaging

Attenuation of diffracted multiples with an apex-shifted tangent-squared radon transform in image space

Anisotropy-preserving 5D interpolation by hybrid Fourier transform

Seismic Time Processing. The Basis for Modern Seismic Exploration

Equivalence of source-receiver migration and shot-profile migration

Seismic Attributes on Frequency-enhanced Seismic Data

Stanford Exploration Project, Report 124, April 4, 2006, pages 49 66

GEOPHYS 242: Near Surface Geophysical Imaging. Class 5: Refraction Migration Methods Wed, April 13, 2011

Crosswell Imaging by 2-D Prestack Wavepath Migration

Target-oriented wave-equation inversion with regularization in the subsurface-offset domain

Converted wave dip moveout

Azimuthal binning for improved fracture delineation Gabriel Perez*, Kurt J. Marfurt and Susan Nissen

Angle-gather time migration a

Refraction Full-waveform Inversion in a Shallow Water Environment

Reverse time migration in midpoint-offset coordinates

y Input k y2 k y1 Introduction

Transformation to dip-dependent Common Image Gathers

G042 Subsalt Imaging Challenges - A Deepwater Imaging Analysis

Advances in radial trace domain coherent noise attenuation

Summary. Figure 1: Simplified CRS-based imaging workflow. This paper deals with the boxes highlighted in green.

Anatomy of common scatterpoint (CSP) gathers formed during equivalent offset prestack migration (EOM)

CLASSIFICATION OF MULTIPLES

Obstacles in the analysis of azimuth information from prestack seismic data Anat Canning* and Alex Malkin, Paradigm.

Amplitude and kinematic corrections of migrated images for non-unitary imaging operators

3-D vertical cable processing using EOM

Short Note. DMO velocity analysis with Jacubowicz s dip-decomposition method. David Kessler and Wai-Kin Chan*

Practical implementation of SRME for land multiple attenuation

Mitigating Uncertainties in Towed Streamer Acquisition and Imaging by Survey Planning

Angle-dependent reflectivity by wavefront synthesis imaging

Multifocusing. The Breakthrough in Seismic Imaging

Offset plane waves vs. common-azimuth migration for sub-salt imaging

Shot-based pre-processing solutions for wide azimuth towed streamer datasets

Inversion after depth imaging

The power of stacking, Fresnel zones, and prestack migration

SeisSpace Software. SeisSpace enables the processor to be able focus on the science instead of being a glorified data manager.

Improved Imaging through Pre-stack Trace Interpolation for missing offsets of OBC data A case study from North Tapti area of West Coast, India

Mitigation of the 3D Cross-line Acquisition Footprint Using Separated Wavefield Imaging of Dual-sensor Streamer Seismic

Model-space vs. data-space normalization for recursive depth migration

Three critical concerns for marine seismics with portable systems. Source strength and tuning Streamer length 2D vs. 3D

3-D prestack depth migration of common-azimuth data

Target-oriented computation of the wave-equation imaging Hessian

High resolution residual velocity analysis and application

Using Similarity Attribute as a Quality Control Tool in 5D Interpolation

We Fast Beam Migration Using Plane Wave Destructor (PWD) Beam Forming SUMMARY

Prestack Kirchhoff time migration for complex media

Plane-wave migration in tilted coordinates

Interpolation with pseudo-primaries: revisited

Y015 Complementary Data-driven Methods for Interbed Demultiple of Land Data

Illumination-based normalization for wave-equation depth migration

High Resolution Imaging by Wave Equation Reflectivity Inversion

13 Recursive prestack depth migration using CFP-gathers 1

A case study for salt model building using CFP full azimuth data W. Gao*, Z. Guo, M. Guo, Q. Zhang, S. Hightower, G. Cloudy Jr. and Z.

Target-oriented wave-equation inversion

Considerations in 3D depth-specific P-S survey design

Iterative resolution estimation in Kirchhoff imaging

Angle-domain parameters computed via weighted slant-stack

Multichannel deconvolution imaging condition for shot-profile migration

Simulations of Seismic Acquisition Footprint

Fast 3D wave-equation migration-velocity analysis using the prestack exploding-reflector model

Migration from a non-flat datum via reverse-time extrapolation

C014 Shot Based Pre-Processing Solutions for a WATS Survey An Example from a Field Trial in Green Canyon Gulf of Mexico

Stanford Exploration Project, Report 111, June 9, 2002, pages

Ray-based tomography with limited picking

Summary. Offset Vector Tiling for CBM

Angle-domain common image gathers for anisotropic migration

Introduction. Surface and Interbed Multtple Elimination

A Short Narrative on the Scope of Work Involved in Data Conditioning and Seismic Reservoir Characterization

Reconciling processing and inversion: Multiple attenuation prior to wave-equation inversion

Finite-difference calculation of direct-arrival traveltimes using the eikonal equation

Ground-roll characterization: Cold Lake 3-D seismic example

Wave Imaging Technology Inc.

Transcription:

Azimuth Moveout (AMO) for data regularization and interpolation. Application to shallow resource plays in Western Canada Dan Negut, Samo Cilensek, Arcis Processing, Alexander M. Popovici, Sean Crawley, Dimitri Bevc, 3DGeo Introduction Azimuth Moveout (AMO) is a wave-equation correct binning algorithm that accurately handles dipping geological strata and variable velocitites. AMO is a partial pre-stack migration operator, and can be effectively applied to interpolate and regularize seismic data. The operator (Biondi et al., 1998) is strictly derived from the wave equation and therefore carries the correct kinematic, phase and amplitude transformation. The dipping events are moved correctly when transforming or interpolating the data, in a manner that is consistent with the wave equation, and thus diffractions are better preserved than after normal or flex binning. This property sets AMO apart as a seismic interpolator from more conventional ones. Dipping events are especially important for migration, because they determine the increase in image resolution after 3-D prestack or poststack migration. Biondo and Chemingui (1994) show how AMO preserves the dipping events after stack, in comparison with the industry standard sequence of NMO, DMO and stack. Traditionally, AMO was designed to address the marine acquisition shortcomings, and regularize the data. Recent focus by exploration and production companies to exploit shallow resource plays has demanded new research into utilizing existing 3D data for mapping the shallow reservoirs. The land examples provided in this paper demonstrate the success of applying AMO to conventional land 3D data. Azimuth Moveout Theory AMO transforms data with a vector offset h1 into equivalent data with vector offset h2 where the vector offset represents the directional segment between a seismic source and a receiver. In other words AMO can transform a trace recorded with a source and receiver positioned at x s1,y s1,x g1,y g1 into a trace recorded with a source and receiver positioned at x s2,y s2,x g2,y g2. AMO can be applied to reduce the data size of a 3-D prestack dataset by coherently stacking traces with similar absolute offsets and azimuths, or it can be applied to interpolate missing offsets and regularize the geometry of the output dataset. The resulting 3-D prestack dataset can be used as input to Kirchhoff 3-D prestack migration or to other wave-equation 3-D prestack migration algorithms. The main applications of AMO as a wave-equation corrrect binning operator used to regularize and interpolate data: 1. Marine data imaging: 2. Use AMO to arrange data in common azimuth format for 3-D prestack wave-equation migration. 3. Marine and Land data imaging: 4. Use AMO to reduce data volume input to 3-D PSDM (partial stacking). 5. Fill acquisition gaps and balance input data (interpolation). The application of AMO to land data before full-prestack migration can be motivated by increasing the signal to noise ratio. Applying AMO before partial stacking improves the accuracy of partial stacking compared with conventional methods based on interpolations and binning. The main advantage of applying partial stacking after AMO, instead of global stacking after DMO, is a gain in robustness with respect to velocity variations. Partial stacking is less sensitive than global stacking to velocity variations because it averages reflections recorded with similar geometries and thus with similar propagation paths in the subsurface. Velocity variations affect those propagation paths similarly and thus do not degrade the coherency of partial stacks as much as of global stacks that average reflections with very different geometries. In areas with complex geology (e.g. steeply dipping reflectors) the conventional route of DMO followed by global stacking and poststack migration yields suboptimal results even in presence of a velocity function varying only with depth because of NMO velocity conflicts (Hawkins et al., 1995; Rietveld et al., 313

1997). In these cases partial stacks are more robust than global stacks, and furthermore, partial stacks after AMO are more robust than partial stacks after DMO (Biondi, 1998). When the velocity varies laterally, the advantages of partial stacking over global stacking are even greater than in v(z) media. However, in presence of severe velocity variations the sampling of the AMO binning cannot be too coarse. The kinematics of the AMO operator are exact only for constant velocity. Therefore, in the presence of severe velocity variations the average of the reflections must be kept localized in offset and azimuth to avoid the degradation of the coherency in the stack. When the spatial sampling of the data is irregular the application of partial stacking before migration can also improve the quality of the images compared with direct prestack migration of the raw data (Chemingui and Biondi, 1996). In this case AMO works as an accurate interpolator before migration. True-amplitude imaging True-amplitude imaging is necessary when the amplitudes of the seismic image are used as input for an estimation of the petrophysical properties of the reservoir rocks. Prestack imaging and AMO can be necessary for true-amplitude imaging even in presence of very simple velocity functions and subsurface structure. In these cases it is important to image as accurately as possible all the components of the wavefield. Even diffractions from a sand channel embedded in a perfectly flat geology must be properly focused. AMO Application Examples Figure 1 shows an example of AMO interpolation for Gulf of Mexico marine data, where missing offsets are filled in during the waveeqaution binning process. Figure 2 shows a time slice through the same Gulf of Mexico data after NMO and stacking of a standard binned and AMO binned dataset. Notice how the AMO stack has a higher signal to noise ratio and the diffractions around the salt dome are better preserved. Some steeper events have more coherency after AMO and stack. Figure 1: Offset gather after AMO interpolation. 314

Binning AMO Figure 2: Time slice through stacked data. Comparison of standard binning and AMO. (a) Time slice (320 ms) before AMO (b) Time slice (320 ms) after AMO (approx. Edmonton sands interval) Figure 3 demonstrates an example from a 3D volume from Winfield Alberta, where coverage in the data is limited based on 3D acquisition parameters. After the application of AMO, the data is more uniform as seen on the coherence slice (Figure 3(b)). Such applications will assume importance in analysis and mapping of shallow resource type plays, where acquisition limitations (cost) impede in the ability to extend the interpretation to very shallow targets. 315

(a) Time slice (830 ms) before AMO (b) Time slice (830 ms) after AMO ( approx. Lea Park interval ) Figure 4: Comparison of coherence slices from a 3D volume (a) before and (b) after AMO. At this interval coverage is adequate using the natural acquisition parameters for the target zone, however review of the coherence slice after AMO demonstrates the improved resolution of dominant features, while removing any residual footprint effects. (a) Time slice (1284 ms) before AMO (b) Time slice (1284 ms) after AMO ( approx. Lower Mannville interval) Figure 5: Comparison of coherence slices from a 3D volume (a) before and (b) after AMO. At this time interval the original data shows no residual effects of the acquisition footprint and generally identifies the major discontinuity trends. The coherence slice after AMO demonstrates two important observations: firstly, the sharpening of the major discontinuities and refining the minor discontinuities (see bottom right-hand corner), and secondly the AMO process has preserved the general integrity of the geological features without introduction of spurrious or random events. 316

References Chemingui, N., and Biondi, B., 1996, Handling the irregular geometry in wide-azimuth surveys, 66th Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 32--35. Biondi, B., and Chemingui, N., 1994, Transformation of 3-D prestack data by azimuth moveout: 64th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 1541-1544. Biondi, B., Fomel, S., and Chemingui, N., 1998, Azimuth moveout for 3-D prestack imaging: Geophysics, 63, 574 588. Biondi, B., 1998, Azimuth moveout vs. dip moveout in inhomogeneous media, 68th Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 1740-1743. Hawkins, K., Cheng, C.C., Sadek, S. A., and Brzostowski, M. A., 1995, A v(z) DMO developed with the North Sea Central Graben in mind, 65th Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 1429-1432. Rietveld, W. E. A., Marfurt, K. J. and Kommedal, J. H., 1997 The effect of 3-D prestack seismic migration on seismic attribute analysis 67th Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts 1367-1370. 317