The accuracy of seismic imaging is largely determined by the ability to produce a subsurface velocity model that accurately predicts the seismic travel time from subsurface imaging points to seismic sources and receivers. The imaging velocity models are commonly estimated by finding a model that can predict the residual depth error in prestack migrated surface seismic gathers. Residual depth error is a measure of the inconsistency of prestack migrated surface seismic data as a function of some imaging gather variable. Examples of imaging gather variables include source-receiver offset distance and subsurface angle of incidence. If the velocity model used in the prestack migration is accurate then the depths of reflections in the image should be consistent as a function of the imaging gather variable. Otherwise the depth inconsistency can be used as information to update the migration velocity model.
Basing a velocity model on prestack migration residual depth error can be a problem if:                1. The seismic gather traces, from the current estimate of the velocity model, are so noisy that residual depth error cannot be accurately measured (i.e. coherent events cannot be seen), or        2. The maximum angle of incidence at the reflector of interest is limited due to overburden anomalies (e.g. salt bodies in the overburden tend to limit maximum angle of incidence). Image gathers then exhibit very little depth inconsistency, even if the velocity model is significantly inaccurate. Thus, the information from these gathers is of little value for updating the velocity model.        
These limitations can often be overcome by fitting the imaging model to information derived from prestack migration velocity scans. A prestack migration velocity scan is simply a set of images created using a suite of test velocity models. Each image is obtained by migrating the surface seismic data with a test velocity model and stacking (summing) the resulting gather traces. This is in contrast to migrating with a single estimate of the velocity model and looking at the gather traces before stacking, as discussed above. Migration velocity scans help solve problem (1) above, because one common cause of noisy imaging is that the current estimate of the subsurface velocity model is too inaccurate to produce a clean image of the subsurface. By comparing the images, one can choose the velocity model that produces the best image. Velocity scans can mitigate both problems identified above, because when the character of the gathers cannot be used to determine an optimal velocity, one can use the geologic reasonableness of the different images in the velocity scan as a type of information on which to base velocity model updating. Examples of geologic reasonableness are that reflectors should not cross in the image, and faults should be sharply focused.
When using velocity scan data to update a velocity model, the seismic processing analyst typically chooses the velocity model, from the scan suite, that produces the optimal image. Criteria for determining the optimal image include greatest stacked image power, greatest signal-to-noise ratio, most geologically reasonable image and greatest resolution. Typically the optimal image at one location is not the optimal image at another location—the choice of optimal velocity in the scan will vary spatially (including in the depth dimension) in the image volume. One major problem with using velocity scans to update a velocity model is that it is not straightforward to accurately update the current migration velocity model based on the information implied by the spatially varying optimal velocity model choices. This invention pertains to this problem of updating a velocity model based on velocity scan data. Next, the aforementioned concepts are discussed in somewhat more detail.
The quality of a seismic image is determined largely by the accuracy with which the seismic travel time between all surface and sub-surface locations can be computed. Thus, the goal of velocity estimation and model building is to build a model that will produce accurate traveltimes. I should be noted that there are many velocity models that will produce essentially the same travel times. So a goal of producing accurate travel times is easier to achieve than a goal to produce accurate velocities. In other words, an inaccurate velocity model can still produce accurate travel times resulting in an image that is just as accurate as if the correct velocity model had been used.
Velocity Model Data Types
There are many types of data that can be used to constrain a velocity model. Table 1 provides a listing of the most commonly available types of data. It is advantageous to constrain models with as many different types of data as possible, since each data type has different strengths and weaknesses.
TABLE 1DescriptionSurfaceDifferences in travel time between traces corresponding to someSeismicimaging gather variable (such as source-receiver offset) provideReflectionsinformation about the subsurface velocity. When the velocitymodel is correct then images should all be consistent as a functionof the imaging gather variable.VerticalMeasurements of travel time from a source at the surface placedCheckshotsvertically over receivers in a well.SurfaceMeasurements of travel time for a source at the surface directlySeismic Direct(without reflection) to a receiver at the surface. These are usuallyArrivalsthe first arrival on a seismic trace.FormationMeasurements of depths to a subsurface rock formation.TopsOffsetMeasurements of travel time from sources at the surface toCheckshotsreceivers in a well. The sources are positioned at a variety oflateral offsets relative to the receiver location.Sonic LogsFine-scale direct measurements of seismic velocities in a well.
Surface seismic data are the primary piece of data used to constrain velocity models, because they are almost always the only piece of data that provide information covering the entire model both laterally and in depth. For unmigrated surface seismic data, differences in travel time between seismic traces having a common midpoint but different offsets are used to infer the subsurface velocity. FIG. 1 shows ray 11 corresponding to a relatively long offset 13, and ray 12 corresponding to a short offset (source-receiver spacing). Since rays corresponding to different offsets travel through different parts of the subsurface, differences in surface seismic travel times for sources and receivers at different offsets can be used to constrain the subsurface velocity. For prestack depth migrated surface seismic data, differences in imaged depth between traces corresponding to different offsets (residual depth error) are used to infer subsurface velocity.
Velocity Model Building Strategy
Velocity models are frequently built in a region stripping manner. Region stripping means that the model is partitioned into regions (see FIG. 2), often corresponding to major velocity discontinuities (e.g. sediments and salt). The velocity in each region is then determined in a hierarchical manner, i.e. before determining the velocity in a given region the velocity is estimated in all regions through which rays from that region of interest must pass. Typically this implies a top-down workflow as shown in FIG. 2, where ray 25 is shown reflecting from subsurface reflector 26, passing through four distinct (in terms of their sound propagation velocity) regions in the process. The velocity is first determined in region 21. This is followed by determining the velocity in region 22, then in region 23. At this point the travel time along the solid part of the ray is approximately correct (depending on the accuracy of the velocities estimated in regions 21 to 23). Determining accurate travel times for the dashed part of the ray path is the goal of determining the velocity in region 24. In some cases, it is useful to perform migration with a suite of different velocities in the region where velocities are being estimated. These are called migration velocity scans. A typical workflow for region stripping is shown in FIG. 3.
In FIG. 3, the bold arrows indicate the region-stripping portion of the workflow. This workflow uses iterative 3D prestack depth migration to update the velocity within each region. Region boundaries are defined by interpreting them from data that are depth migrated with the current version of the model. Some initial velocity model is assumed at 34. The iterative cycle 31-34 is performed in region 21 (using FIG. 2 as an example). This determination is based on interpreting in the seismic data a reflection event corresponding to the interface between regions 21 and 22. At step 33, the velocity model is adjusted (updated) based on prestack migration residual depth error. When the acoustic velocity in region 21 is determined, the steps 35-38 are performed. At step 36, the interface between regions 22 and 23 is identified in the depth migrated data and added to the known region boundaries at 37, defining region 22 in the model at step 38. The inner iteration loop in FIG. 3 is then implemented until a velocity function (of the spatial variables) for region 22 is determined, and so on region-by-region.
Layer stripping strategy is a subset of the region stripping strategy. In layer stripping, the regions used are chosen to have sufficiently limited vertical extent so that a very simple parameterization of the vertical change in velocity can be used (e.g. the velocities are vertically constant or a linear function of depth). Layer stripping also implies that seismic information from deep regions is not used to update the velocity in shallower layers. The combination of thin layers and discarding of information from deep regions leads to some degree of vertical instability in layer stripping and also makes it impossible for layer stripping to determine velocity models in some geologic situations. An example of a geologic situation that cannot be solved by layer stripping is a shallow gas anomaly which generates no reflection, and therefore the only information about the velocity in the anomaly is in the deeper reflections.
Velocity Estimation Methods
Table 2 describes several specific velocity estimation techniques that can be used in the strategies discussed in the previous section. Each technique is described in somewhat more detail in the paragraphs that follow Table 2.
TABLE 2DescriptionVertical UpdatingMeasure residual curvature in common image gathers(Deregowski)and convert to interval velocity using Dix equationModel BasedForward model all data types, visualize fit to data,Manual Updatingand interactively adjust model to improve fitTomographyMeasure residual curvature in common image gathersand use mathematical optimization to find best fitmodelVertical Updating (Deregowski)
Most velocity model updating packages support some sort of vertical updating procedure (Deregowski, “Common-offset migration and velocity analysis,” First Break 8, 225-234 (1990)). Vertical updating means that velocity function updates at a location are based on migrated seismic data in the vicinity of that location. FIG. 4 shows the conventional method used for performing vertical updating. Residual depth error is picked on common image gathers. Depth error is converted back to time moveout using the migration velocity. Time moveout is converted to interval velocity using the well known Dix equation. Note that vertical updating is an iterative process, with prestack depth migration applied once during each iteration. Vertical updating also requires smoothing to mitigate errors introduced due to instability of the method. Step 41 is often hidden from the user.
Model Based Manual Updating
FIG. 5 illustrates an implementation of model based manual updating (see U.S. Pat. No. 6,253,157 to Krebs). The method uses forward modeling to predict, from the current model, the data that would be measured if that model were correct. The synthetic data are then compared to the measured data, and the user adjusts the model to improve the match. The updated model becomes the initial model for the next iteration. This process is employed at a sparse set of locations, and the model is smoothly interpolated between those locations.
Tomography
Tomography is very similar to model based manual updating. The main difference is that tomography employs mathematical optimization to update the model, rather than having an interpreter manually adjust the model. Tomography can be implemented in either the migrated or unmigrated domain. However, most modern tomography approaches are implemented in the migrated domain, because it improves stability. FIG. 6 is a diagram illustrating a possible implementation of the tomographic method. The updated model becomes the initial model for the next iteration.
Migration Velocity Scans
There are two significant problems associated with constraining subsurface velocity models using surface seismic data:                1. An incorrect initial velocity model can leave the migrated data so disorganized that a velocity analysis display having satisfactory signal-to-noise ratio (S/N) cannot be produced. This can happen even if the velocities in the regions above the region of interest are largely correct.        2. In some situations the maximum angle of incidence for reflection raypaths below a velocity anomaly (see the ray path 25 in FIG. 2) is quite small. The ability to accurately resolve velocities from residual depth error in a migrated gather decreases when this maximum angle of incidence decreases.Both of these problems can be addressed by constraining the model using migration velocity scans. A migration velocity scan is a set of seismic migrations performed with a suite of different velocity models. Usually, the suite of velocity models is formed by holding constant the velocity outside the region being updated, while varying the velocity within that region.        
Migration velocity scans help solve problem (1) above, because there is a good chance that one of the velocity models in the suite will be accurate enough to provide satisfactory S/N imaging that can be used to constrain the velocity model. Note that the suite of models, in the scan, does not have to contain the actual subsurface velocity to get this S/N enhancement. As a matter of fact, typically one model in the suite will enhance S/N in one portion of the region of interest, while another model in the suite will enhance some other portion of the region. Another way that migration velocity scans solve problem (1) is that the interpreter often interprets the stack of the scanned images rather than the common image gathers themselves. Stacking provides an added boost to S/N.
Migration velocity scans can also solve problem (2) above, because indicators other than image gather residual depth error can be used to determine which velocity in the scan is producing the best image. In particular, the geologic feasibility and increased image resolution of the resulting images can be used to judge that one velocity model in the suite is superior to others. An example of a geologically infeasible image would be one that has reflections that cross. An example of increased image resolution is the focusing of faulted reflections to sharp terminations. Image gather residual depth error is controlled only by specular reflection ray paths. However, geologic feasibility and resolution are controlled by the combination of specular reflection and diffraction rays. This addition of diffraction rays makes it possible for migration velocity scans to provide information about travel times over a larger range of propagation angles, leading to increase velocity resolution.
Velocity Model Updating using Migration Velocity Scans
Recent publications propose a direct updating of the velocity model using the layer stripping strategy. See Pica, “Velocity scan for 3D-PreSDM model building: Fast traveltime reconstruction for isotropic and anisotropic media,” 71st SEG meeting, Expanded Abstracts (2001); Fei and McMechan, “Fast model-based migration velocity analysis and reflector shape estimation,” Geophysics 70, U9-U17 (2005); and X. Wang, et al., “Model based processing (IV): migration velocity analysis,” 75th SEQ meeting, Expanded Abstracts, 2261-2264 (2005). They simply perform a migration velocity scan within each layer and then choose a laterally varying optimal velocity from the scans. This is an obvious use of migration velocity scans, but suffers from the vertical instability and geologic regime limitations of layer stripping discussed above.
Use of migration velocity scans in the more general region stripping strategy is not so obvious. Migration velocity scan data cannot be input directly to the model updating procedures discussed in the Velocity Estimation Methods section above. Therefore, the velocity scans must first be analyzed to produce data that are compatible with the chosen model updating method. Typically this analysis involves determining, throughout the image volume, which velocity in the scan produced the optimal image (see FIG. 7). This spatially varying optimal velocity data is then converted to the type of information required for the chosen model updating method. The converted data required at step 71 could be, for example, either hyperbolic velocity or residual depth error. This conversion usually involves some significant approximation. Examples of updating techniques at step 72 include Deregowski updating and tomography.
Audebert proposed converting optimal velocity scan picks to time moveout picks by using the time moveout corresponding to the RMS average of the picked optimal velocity model at the pick location. See Audebert, et al., “CRP-scans from 3D Pre-Stack Depth Migration: a powerful combination of CRP-gathers and velocity scans,” 66th SEG Meeting, Expanded Abstracts, 515-518 (1996). These residual curvatures are then input to a Deregowski updating method. Note that this conversion to residual curvature assumes the subsurface velocities are laterally invariant, an assumption that is usually significantly violated in most regions where velocity scans are of greatest value.
In U.S. Pat. No. 6,577,955, Guillaume proposes picking the depth error and reflector dip on migrated gathers from the optimal velocity in a migration velocity scan. These depth errors are then kinematically inverse migrated to produce unmigrated reflection travel times. These unmigrated travel times are tomographically inverted to produce an updated velocity model. Note that this method cannot be applied to stacks of the optimal velocity scan images, thus some of the S/N enhancement advantage of migration velocity scans is lost. Furthermore this method deals exclusively with specular reflection rays and therefore loses some of the increase in velocity resolution available from migration velocity scans. B. Wang et al. propose a further refinement of this technique, suggesting inverse kinematic migration to a datum at the base of a velocity anomaly rather than the Earth's surface (“A 3D subsalt tomography based on wave-equation migration-perturbation scans,” Geophysics 71, pages E1-E6 (2006)). This has the advantage of simplifying the tomographic update of the model below the anomaly, but again suffers from incomplete exploitation of the S/N and velocity resolution advantages of migration velocity scans.