Pre-stack Depth Migration Velocity Analysis Research Articles

Tomographic velocity inversion for ADCIGs in areas with a rugged surface

Pre-stack depth migration velocity analysis is one of the key techniques influencing image quality. As for areas with a rugged surface and complex subsurface, conventional prestack depth migration velocity analysis corrects the rugged surface to a known datum or designed surface velocity model on which to perform migration and update the velocity. We propose a rugged surface tomographic velocity inversion method based on angle-domain common image gathers by which the velocity field can be updated directly from the rugged surface without static correction for pre-stack data and improve inversion precision and efficiency. First, we introduce a method to acquire angle-domain common image gathers (ADCIGs) in rugged surface areas and then perform rugged surface tomographic velocity inversion. Tests with model and field data prove the method to be correct and effective.

Residual curvature migration velocity analysis for angle domain common imaging gathers

Pre-stack depth migration velocity analysis is one of the keys to influencing the imaging quality of pre-stack migration. In this paper we cover a residual curvature velocity analysis method on angle-domain common image gathers (ADCIGs) which can depict the relationship between incident angle and migration depth at imaging points and update the migration velocity. Differing from offset-domain common image gathers (ODCIGs), ADCIGs are not disturbed by the multi-path problem which contributes to imaging artifacts, thus influencing the velocity analysis. On the basis of horizontal layers, we derive the residual depth equation and also propose a velocity analysis workflow for velocity scanning. The tests to synthetic and field data prove the velocity analysis methods adopted in this paper are robust and valid.

Fast model-based migration velocity analysis and reflector shape estimation

Migration velocity analysis can be made more efficient by preselecting the traces that contribute to a series of common-reflection-point (CRP) gathers and migrating only those traces. The data traces that contribute to a CRP for one reflection point on one layer are defined in a two-step procedure. First, poststack parsimonious Kirchhoff depth migration of zero-offset (or stacked) traces defines approximate reflector positions and orientations. Then, ray tracing from the reflection points for nonzero reflection angles defines the source and receiver locations of the data traces in the CRP gather. These traces are then prestack depth migrated, and the interval velocity model adjustment is obtained by fitting the velocity that maximizes the stack amplitude over the predicted (nonhyperbolic) moveout. A small number (2–3) of iterations converge to a 2D model of layer shape and interval velocity. Further efficiency is obtained by implementing layer stripping. The computation time is greatly reduced by combining parsimonious migration with processing only the salient portions of the whole seismic data set. The algorithm can handle lateral velocity variation within each layer as well as constant velocity. The computation time of the proposed algorithm is of the same order as that of the standard rms velocity scan method, but it does not have the inherent assumptions of the velocity scan method and is faster than current iterative prestack depth migration velocity analysis methods for typical field data.

Exploration at the eastern edge of the Precaspian basin: Impact of data integration on Upper Permian and Triassic prospectivity

The Temir license area of western Kazakhstan lies at the eastern edge of the Precaspian salt basin, a prolific emerging basin of the former Soviet Union. The recent exploration phase resulted in the discovery of an oil field that shed a new light on postsalt (Triassic and Upper Permian) hydrocarbon plays. Geologically, the area is dominated by salt tectonics. Typical salt-related structures are the site of potential hydrocarbon accumulations charged from presalt source rocks. These structures were evaluated using conventional data sources such as gravity, wells, and seismic lines. New information was gained from the combination of topography, seismic data, and satellite imagery: (1) the relationship between surface morphology and underlying structure, (2) comparison between faulting and seepage information, and (3) an understanding of salt withdrawal history. The best reservoirs are Triassic and Tatarian continental sandstones. Older Kazanian sandstones, a mixed evaporite-clastics succession, show very poor reservoir parameters. The integration of well results (cores, wire-line logs), outcrop information, and seismic data indicates (1) seismic facies studies are not sufficient to discriminate between Tatarian (reservoir-rich) and Kazanian (reservoir-poor) sequences because both successions commonly exhibit comparable seismic characters; (2) evaluation of reservoir potential based on the analysis of stacking velocities can be erroneous, particularly in narrow salt withdrawal minibasins and on seismic lines close to salt structures; and (3) reservoir prediction in the Tatarian and Kazanian successions can be estimated based on the analysis of prestack depth migration (PSDM) velocity models on conventional two-dimensional seismic lines. For example, fast PSDM velocity value ranges derived from the model correspond mostly to Kazanian mixed clastics-evaporite sequences that have poor reservoirs. (Begin page 400) Slower velocities, however, indicate sections that have better quality reservoirs. Thus, we recommend using PSDM velocity analysis coupled with core calibrations to predict reservoir potential and quantify porosity values in complex salt-related prospects such as salt overhangs and salt flank traps.

Applications of Pre-Stack Depth Migration

Complex shallow faulting is a common problem which can lead to poor results when using the CDP assumption. Wave-field distortion makes it impossible to select a stacking velocity that does not deteriorate stack response. The only way to achieve a high-quality stack is to predict and remove the wave-field distortion before stack, that is, by correctly migrating the pre-stack gather. Predicting the distortion is difficult, as it requires the estimation of the actual interval velocity field. Many methods have been proposed for estimating velocities, three of which are iterative pre-stack depth migration, ray-trace modelling, and interactive interval velocity analysis. Each of these has advantages and disadvantages, but iterative pre-stack depth migration is generally the most useful. Reflection tomography can also be useful. Once accurate velocities have been obtained, many algorithms are available to do the actual migration. Two methods are compared; a shot-record finite-difference algorithm and a common-offset, Kirchhoff algorithm. The latter algorithm has practical advantages that lends itself more to iterative pre-stack depth-migration velocity analysis and generally makes it more attractive. Pre-stack depth migration, with both algorithms, is demonstrated on a real data set from offshore north-western Australia. The examples show that iterative pre-stack depth migration can successfully improve seismic images in difficult areas.