Macro velocity model estimation through model‐based globally‐optimized residual‐curvature analysis

Abstract

In the past few years, significant progress has been made on new velocity analysis algorithms. In the first part of this paper, we will briefly summarize recent advances on velocity analysis. Then we describe a new model-based globally-optimized residual curvature analysis algorithm we have just developed. Like conventional residual curvature analysis, the algorithm is based on the principle that after prestack migration with a correct velocity model, an image in the common image point (CIP) gather is aligned horizontally regardless of structure. Unlike conventional residual curvature analysis, this algorithm uses not only the interpreted CIP gathers, but also the interpreted migrated depth section as input. The algorithm is model-based, and uses modelbased CIP ray tracing to relate residual moveouts in CIP gathers to errors in the velocity model. Residual moveouts measured in CIP gathers are globally used in the optimization process for updating the whole velocity model. Also model-based normal incident ray tracing is used for updating the reflector boundaries. REVIEW OF RECENT ADVANCES OF VELOCITY ANALYSISRecent advances of velocity analysis can be summarized into two categories: 1) traveltime inversion; 2) migration velocity analysis. Traveltime inversionTraveltime Inversion (TI) (Bishop et al., 1985; Stork and Clayton, 1991) estimates a depth velocity model from traveltimes picked from prestack data. The main advantage of TI is that it is formulated as an optimization problem and therefore model updating is very effective and efficient. However, in areas of complex geological structure, picking prestack traveltimes in surface seismic data is almost unfeasible. Picking prestack traveltimes may have the following problems: 1) in the case of complex reflector geometry, seismic energies reflected from different parts of a reflector may arrive at the same receiver location; 2) reflection arrivals contaminated by diffraction energy; 3) low signal-to-noise ratio often associated with complex structure.In the past few years, a few researchers tried to solve the traveltime picking problem. IFP (Institut Francais du Petrole) developed a method called SMART (Sequential Migration Aided Reflection Tomography) (Delprat-Jannaud and Lailly, 1993) to solve the traveltime picking problem. The main idea of SMART is to use an approximate velocity model to migrate seismic data, then pick the imaged reflectors in the cube of migrated shot gathers, finally trace rays that propagate in the same velocity model as the one used for the migration and that are reflected on the picked imaged reflectors. They claimed that because the ray tracing undoes what the migration has done, even with an approximate velocity model they can recover traveltimes. More recently DATAID (1994) used a similar approach as IFP, but performed migration and raytracing in the common-offset gather instead of common-shot gather. The main point of these approaches is that instead of directly picking events in the time domain, picking is done after depth migration...

Multipathing in three‐parameter common‐image gathers from reverse‐time migration

“…Ray-based prestack migration velocity analysis (e.g., Stork 1992;Wang, Pann, and Meek 1995;Liu 1997;Montel and Lambaré 2013) is efficient, but the amplitude and angle information can be affected by the limitations of ray theory in complex media (Operto et al 2000;Xu et al 2001). Ray-based prestack migration velocity analysis (e.g., Stork 1992;Wang, Pann, and Meek 1995;Liu 1997;Montel and Lambaré 2013) is efficient, but the amplitude and angle information can be affected by the limitations of ray theory in complex media (Operto et al 2000;Xu et al 2001).…”

“…Angle-domain common-image gathers (ADCIGs) can be produced by any type of pre-stack migration. Ray-based prestack migration velocity analysis (e.g., Stork 1992;Wang, Pann, and Meek 1995;Liu 1997;Montel and Lambaré 2013) is efficient, but the amplitude and angle information can be affected by the limitations of ray theory in complex media (Operto et al 2000;Xu et al 2001). Three different forms of wave-equation-based ADCIG algorithms have been proposed: direction-vector-based methods (e.g., Yoon et al 2011;Zhang and McMechan 2011a,b;Dickens and Winbow 2011;Vyas, Nichols, and Mobley 2011), local plane-wave decomposition methods (e.g., Xie and Wu 2002;Xu et al 2011;Xie 2011, 2012), and local-shift imaging condition methods (e.g., Sava andFomel 2003, 2005a,b;Xu et al 2014).…”

A 3D subsalt tomography based on wave-equation migration-perturbation scans

“…Nevertheless, most velocity model building is still performed using Kirchhoff migration combined with ray-based, finite-offset tomography (Wang et al, 1995;Zhou et al, 2001Zhou et al, , 2003; (Guillaume et al, 2001(Guillaume et al, , 2003. Combining wave-equation migration with ray-based tomography still represents a challenge because of their different methods for simulating wave propagation in complex velocity media.…”

Automated 3D tomographic velocity analysis of residual moveout in prestack depth migrated common image point gathers

“…Where velocity varies smoothly along a cable length, the CIP gathers may be converted to time and local interval velocity updates calculated from conventional, interactive stacking-velocity analysis (Deregowski, 1990). Where velocity varies more rapidly, a full postmigration reflection tomography problem must be solved, with independent raypaths traced for each picked offset of each picked reflector (Stork, 1992;Wang et al, 1995). This paper offers an example of the second method, applied to a Gulf Coast data set.…”