Journal Reference : K. Tinto, L. Padman, C. Siddoway, S. Springer, H. Fricker, I. Das, F. Caratori Tontini, D. Porter, N. Frearson, S. Howard, M. Siegfried, C. Mosbeux, M. Becker, C.
Bertinato, A. Boghosian, N. Brady, B. Burton, W. Chu, S. Cordero, T. Dhakal, L. Dong, C. Mary Baker tries to get over an apocalyptic break-up with 13 varied partners.
Security II Short Drama. Extortion Action Adventure Crime. Captain Phillips Biography Drama Thriller. America; I Too Pirates of Somalia Biography Drama. The Toll I. Not yet released. Edit Cast Credited cast: Barkhad Abdi Caweys Jim Sarbh Jimmy Jameel Khan Vinay Meghana Mundkur Sabina Asheesh Kapur Darbaan Laura McCone Siren Ayman Emara Ayman Anwar Hussain Ramu Sandeep Sequeira Tariq Rest of cast listed alphabetically: Casey Shannon Salesman Megan Pormer Lucille Syed Shujat Security Manager Chuka Ekweogwu Security Guard Marian Dumitru Courier guy Danil Bornventure Edit Storyline A billboard repairman in Dubai tries to experience the products on his billboards as a con artist takes him under his wing.
Taglines: All good thieves are dreamers. So it is useful to have other seismic modeling capabilities in our arsenal, and it is natural to turn a well-calibrated Kirchhoff migration program into a modeling program. But not for the purpose of testing the original Kirchhoff migration program! In Figure 2, we show an example of elastic finite-difference modeling vertical component and acoustic, anisotropic Kirchhoff modeling on a thrust model, as well as isotropic and anisotropic Kirchhoff prestack migrations of the finite-difference data.
The modeled records are zero-offset records, and the migrations are stacks of all the migrated offsets. This model was originally acquired as a physical model Leslie and Lawton, to illustrate the problems that arise when we produce seismic images beneath dipping thrust sheets without considering the effects of seismic anisotropy.
The match between the finite-difference and Kirchhoff records is excellent, validating the anisotropic raytracer used in the Kirchhoff modeling and migration codes. Some of the minor differences in the records can be ascribed to mode conversions present on the finite-difference record but absent from the Kirchhoff record. Others can be used to explain the artifacts present on the Kirchhoff migration of the finite-difference data. Determining near-surface velocity structures is a crucial first step in seismic data processing and depth imaging.
An inadequate near-surface velocity model will result in incorrect statics corrections for time domain processing. For depth migration, even a modest inaccuracy in the near-surface velocity model can introduce large errors in both raypath and traveltime calculation, and can significantly deteriorate the seismic image at depth, especially in the areas with large lateral velocity variations. Many refraction methods have been developed over the years for near-surface velocity determination, primarily for the purpose of statics solutions.
Refraction methods are appealing because the shallowest portion of a seismic record is often dominated by source-generated noise, and accurate identification of reflections is difficult. The first arrivals, on the other hand, can be clearly identified and often represent the best data available for near-surface velocity estimation. As a result, these methods cannot model velocity inversions or vertical gradients within each layer, and may fail to accommodate strong lateral velocity variations. By treating first arrivals as refractions, they are also unable to determine the first layer velocity v0.
This results in a trade-off between interface depths and layer velocities in a derived velocity model, making the model inadequate for imaging processes such as depth migration which are more sensitive to local velocity variations than is the statics solution. An inversion method for the accurate determination of near-surface velocity structures has been introduced by Zhu and Cheadle , The velocity structure is represented by a grid model. Each node of the grid is assigned a velocity and the node velocities can vary in an arbitrary fashion capable of representing strong velocity variations in both vertical and horizontal directions.
Also, first arrivals are now treated as direct body waves propagating along turning rays, enabling the method to determine the first layer velocity as well. The node velocities are determined by solving a nonlinear least-squares problem which minimizes the differences between the observed traveltimes of first arrivals and those predicted from the grid model.
The nonlinear inverse problem is reduced to solving iteratively a regularized, linear least-squares problem using the LSQR algorithm introduced by Paige and Saunders The inversion is regularized by including in its matrix equation both smoothing and stepsize constraints; the former reduces the roughness of the velocity model and the latter limits the linear approximation within a trust region during each iteration.
As the inversion requires intensive raytracing, an accurate and efficient algorithm for traveltime and turning raypath calculation is essential for practical applications. The algorithm must also be robust and devoid of the shadow-zone problem which has hindered tomographic methods based on traditional raytracing techniques. We recently developed the grid raytracing GRT technique Zhu and Cheadle, specifically for this application.
This method calculates traveltimes and wave propagation vectors by tracing rays locally within a grid cell, and has been shown to be highly accurate and efficient in modeling turning rays in near-surface environments. Other traveltime modeling techniques such as wavefront construction and the fast marching algorithm can also model turning rays without shadow zone problems. Tests show that GRT is about two orders of magnitude more accurate than the fast marching method and up to eight times faster than wavefront construction.
These attributes make GRT ideal for an iterative inversion for complex near-surface velocities. We investigated effects of near-surface velocity estimation on depth migration using the 2D Canadian Foothills finite-difference model data set of Figure 1. The uppermost m section of this model is shown in Figure 3 a. The entire model is about First arrivals were picked from the synthetic data to a maximum offset of m. We first estimated the velocity with a conventional refraction method and smoothed with a m Hanning window in both vertical and horizontal directions.
The resulting velocity model is displayed in Figure 3 b. We used the smoothed model as an initial model for the tomographic inversion described in the previous section. The grid model consists of x 56 cells with a grid spacing of 25 m in both vertical and horizontal directions. The final velocity model shown in Figure 3 c was obtained after five iterations of tomographic calculation. A comparison of Figure 3 a and 3 c shows a close agreement between the true and inverted velocity models, even in some small details, indicating that the tomographic method is capable of recovering near-surface velocity structure in geologically complex areas.
To demonstrate the effects of the near-surface velocity model on prestack depth migration PSDM of the synthetic data, we constructed two velocity models by merging the near-surface models from Figures 3 b and 3 c respectively with the exact velocity model at m depth below highest elevation. Figure 1 b shows the PSDM section obtained with the exact velocity model while Figures 4 a and 4 b display respectively the sections produced by the models constructed with the near-surface models from Figures 3 b and 3 c. The results clearly show that inaccuracy in a near-surface velocity model can severely deteriorate the seismic image at depth and make the process of determining the deeper portions of the velocity model more difficult.
The near-surface velocity model determined by the tomographic inversion method has significantly improved the depth imaging, and increases the potential for deriving the deeper model by conventional reflection analysis techniques. Turning-ray tomography is a general procedure for near-surface model building, providing both static corrections and near-surface velocities as inputs into prestack migration.
For PSDM, we can choose to use either the static corrections or the velocities, but for prestack time migration PSTM , we simply apply the static corrections to the seismic data. In theory, this is more correct than applying static corrections to the seismic data, but in practice it carries a certain risk. This is the risk that the rapid variation between the low velocities in the near surface and the much higher velocities just below the near surface will cause problems with the depth migration program.
Extensive experimentation some of it on model data has shown this not to be the case: the raytracers used in both the tomographic inversion and the Kirchhoff migration program are extremely robust. Between the standard flow culminating in poststack time migration and the advanced PSDM flow lies PSTM, which represents a compromise between processing speed and interpretational resolution. In this flow, we perform the prestack time migration as a series of constant-velocity migrations, providing a cube of migrated stacks from which we can select spatially-varying imaging velocities by picking the velocity panel with the best-focused image at each location.
In 3D, we do this analysis along closely-spaced target lines. In doing this, we use criteria such as stack power and optimal diffraction collapse to guide our picking of the PSTM velocity field.
We then use the final velocity field to perform a final full volume migration. We have already mentioned that our advanced flow is interpretive, and we must also emphasize the interpretive nature of standard velocity picking for PSTM, at least for Foothills data. It is important for the seismic processor who actually does the PSTM to be aware of the structural style and seismic velocities of the area in order to discriminate between conflicting but plausible structures.
In practice, these decisions are left to the processor with varying amounts of guidance from the interpreter. The standard method for depth migrating Foothills data is Kirchhoff migration. As we mentioned earlier, we have tested our depth migration programs extensively on synthetic model data in order to optimize both accuracy and speed. Recently, migration methods with greater theoretical accuracy, such as finite-difference migration, have become available, and these will soon be competitive economically with Kirchhoff migration.
For PSDM, we can choose to use either the static corrections or the velocities, but for prestack time migration PSTM , we simply apply the static corrections to the seismic data. However, since the activity is continuing and indicating ongoing magmatic activity in the lower curst and upper mantle. DPReview Digital Photography. Email alerts New issue alert. The water injection induced events were monitored in the near field. Get the best of The New Yorker in your in-box every day. View all.
Many details need to be worked out, however, before these methods can be used for production processing. Technical issues with these methods include their ability to migrate accurately from topography and to produce common image gathers that can be analyzed for velocity updating. The greatest barrier to their use, though, will be their need for regular spatially sampled data, which can be accomplished today only at great expense, during either acquisition or preprocessing. For the Blackstone data set discussed below, the inverted velocities are shown in the upper m to m of Figure 5 a.
These velocities, computed without assuming a layered model and without constraining the inversion, are certainly plausible. Velocities along the floating datum marking the base of the near-surface correspond well with the expected formation velocities in the initial model.
It is common practice to use an initial model based on a Dix inversion of the imaging velocities used for time migration. For areas as structurally complex as the Foothills, however, we find that equating the imaging velocities used in time migration with RMS velocities can lead to significant errors in PSDM. Instead, our initial model might be a heavily smoothed version of what we initially believe the structural model to be more interpretation!
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Velocity model updates for subsequent iterations are performed using an interactive reflection tomography tool Gray et al. This tool represents the velocity as a gridded model between horizons that separate major geologic units. Proceeding from the top down, we update the velocity in one or more of these units before we repeat the migration.
At selected locations, we use raypaths shot upwards from the base of a target geologic unit Figure 5 a. Velocities in overlying layers remain fixed at values determined from previous iterations. The effects of a velocity change along the ray segments within the active unit are computed and registered on the displayed depth-migrated image gathers Figure 5 b and 5 c. The crucial feature of this tool is its interactive nature. Applying a percentage velocity change within a unit produces an immediate change in the moveout on the image gather.
The velocity change might make the gather more flat a good thing , it might make it smile or frown a bad thing - velocity too slow or too fast , or it might even destroy the continuity of the event.
Many different velocities may be tried, and most of them rejected, in just a few seconds, before the velocity that flattens the gather is accepted.