Anisotropic seismic velocity models from modeling and inversion of walkaway VSP data

In this study we develop a practical method for the location of microseismic events in anisotropic media. The velocity anisotropy is taken into account in the additional step after the conventional location procedure. In this step, the isotropic velocity model and corresponding estimated locations serve as an initial model, and the anisotropy parameters as well as resulting location misfits are inverted simultaneously due to the coupling of velocity model and hypocenter parameters in calculation. After obtaining the anisotropic velocity model, one can relocate all the events around their isotropic velocity based locations. The method is ray theory based and only consider transversely isotropic layered model. The nonlinear inversion problem is solved by using Gauss-Newton method. The results of synthetic example closely fit with the true values and event depths are better determined than radial distances. Real data test shows that the estimated Thomsen parameters are consistent with previous study, and the isotropic velocity based locations are significantly corrected with large decrease of average misfit from 52m to 6m.

Anisotropic velocity models are poorly constrained by surface seismic data alone. Rock physics anisotropic modelling of shale compaction and digenesis provides information which can be used to constrain anisotropic velocity model building. We demonstrate this new anisotropic model building methodology which incorporates shale compaction model, check shot data and tomography to build a 3D spatially varying anisotropic velocity model in the North Sea. The initial rock model is built by analysing well log data, temperature gradient and additional geologic information. Tomography with checkshots (local tomography) which takes into account both residual moveout of surface seismic data and vertical traveltime from checkshot data was used to calibrate rock model to predict a similar anisotropy profile. After calibration a 3D anisotropic model is built to produce spatially varying anisotropic parameters consistent with both rock model and checkshot data.

Summary In 2014 we proposed a new technique that used well information to correlate anisotropy with velocity for localized lithology dependent anomalies (Birdus at al., 2014). It is based on the assumption that in appropriate geological settings localized variations in both velocity and anisotropy are caused by changes in the lithology. This results in some correlation between anisotropy and velocity anomalies. We used well information to establish such a correlation for tomographic PSDM imaging anisotropic velocity models. In this paper we extend our approach to high resolution FWI depth velocity modeling. We use a real 3D seismic dataset from the NW Australian shelf to illustrate how our technique produces more realistic anisotropic velocity models and reduces depth misties.

An accurate knowledge of salt flank structure is important for mapping the extent of reservoir rock and successfully placing development wells. Highly irregular and nearly vertical salt flanks are very difficult to image with surface seismic methods. Borehole seismic salt proximity surveys (SPS) have been commonly used to delineate and map salt flanks adjacent to a borehole by estimating seismic wave's exit points at the salt-sediment interface. Presently, most salt-exit–point calculations from SPS data are based on 3D isotropic ray-tracing algorithms which use isotropic sedimentary velocity models. It has been well recognized however, that many sedimentary rocks exhibit vertical transverse isotropy (or VTI anisotropy) to seismic waves. Both propagation direction and velocity of seismic waves in anisotropic VTI media can be drastically different from those in isotropic media. Neglecting anisotropy could significantly affect the accuracy of the computed salt exit positions determined from SPS data. This paper presents a 3D anisotropic ray-tracing methodology to determine salt-face exit points from VSP salt proximity survey data. We calculate and trace exact ray paths by deriving an analytic 3D vector ray equation across arbitrary interfaces in an anisotropic layered velocity model. As ray paths are correctly defined and traced for any complex anisotropic layers, this 3D ray-tracing methodology can accurately and efficiently produce stable salt-face exit point solutions. Through numerical tests imitating typical SPS examples we demonstrate the effectiveness of our methodology and significant impact of anisotropy in determining 3D salt-face exit points from SPS data.

Page Not Found - If you're seeing this page, it's because the URL you requested cannot be located. It might not exist or maybe you mistyped it into your browser. But, if you think it's our mistake, please let us know. Otherwise, you have a few options: try using our navigation bar at the top of this page, visit our home page, or browse our products below. - Homepage Basic Content,

As anisotropic depth imaging is widely used in the industry, anisotropic velocity models are routinely being constructed and applied. However, the degree of accuracy of the anisotropic velocity model needed to correctly position the horizons is not well defined. To that end, we tested four anisotropic parameter estimation scenarios and performed depth imaging using a realistic synthetic sedimentary seismic data that included an irregularly shaped salt body. Although similar images derived from the data using those four different anisotropic input models were obtained, a quantitative analysis indicates that systematic differences do exist. They enable us to relate the degree of accuracy needed in the image to the effort needed to build the anisotropic velocity model.

Understanding the distribution and mobility of crystal mushes within modern magmatic systems is crucial to volcanic hazard assessments as distinct pockets of mobile magma may become interconnected and lead to melt accumulation on shorter time scales than magma that is broadly distributed in a homogeneous mush. Here, we reveal that Yellowstone's upper-crustal magma reservoir in the top 20 km is heterogeneous in both melt concentration and texture. We exploit ambient noise in an unprecedented dense temporary seismic network to jointly constrain vertically- and horizontally-polarized shear wave speeds to create enhanced 3D isotropic and anisotropic shear velocity models. Our models show an exceptionally low-velocity (>20% reduction) layer 4–7 km beneath the surface, situated near the top of the reservoir previously-imaged by earthquake P-wave tomography. The presence of strong radial anisotropy (20%) within this layer indicates the uppermost portion of the modern Yellowstone reservoir is organized as a sill complex, with up to 28% of melt fraction in horizontally-elongated volumes at depths where rhyolite was commonly stored before past eruptions. The findings demonstrate that high-resolution anisotropic imaging through a dense seismic network can constrain both magma distribution and reservoir texture, which are important to understand the evolution and hazard assessment of volcanic systems like Yellowstone.

Combining PP-waves with mode-converted PS reflections in migration velocity analysis (MVA) can help build more accurate VTI (transversely isotropic with a vertical symmetry axis) velocity models. To avoid problems caused by the moveout asymmetry of PS-waves and take advantage of efficient MVA algorithms designed for pure modes, here we generate pure SS-reflections from PP and PS data using the PP þ PS ¼ SS method. Then the residual moveout in both PP and SS common-image gathers is minimized during iterative velocity updates. The model is divided into square cells, and the VTI parameters VP0, VS0, e, and δ are defined at each grid point. The objective function also includes the differences between the migrated depths of the same reflectors on the PP and SS sections. Synthetic examples confirm that 2D MVA of PP- and PS-waves may be able to resolve all four relevant parameters of VTI media if reflectors with at least two distinct dips are available. The algorithm is also successfully applied to a 2D line from 3D ocean-bottom seismic data acquired at Volve field in the North Sea. After the anisotropic velocity model has been estimated, accurate depth images can be obtained by migrating the recorded PP and PS data.

Anisotropic depth migration (ADM) has become more commonplace over the past four years. The data-processing examples detailed here illustrate the robustness of the method in a variety of structured settings in the Alberta Foothills. The public-domain structural line, the Husky/Talisman dataset, illustrates subtle improvements in imaging with a dramatic improvement in accuracy of horizon depths when ADM is applied to these data. A 3D survey in a difficult imaging area, Nordegg/Chungo, shows significant healing of broken basement reflectors when we correct for anisotropy in the complex-dipping clastic overburden. Finally, in the Blackstone area where we observe intense folding in the near surface, comparisons between poststack time migration, prestack time migration, prestack depth migration, and prestack anisotropic depth migration show the similar step-change improvements as we imrove the technology of our algorithm. Introduction Traditional depth migration corrects only for lateral velocity heterogeneity. Current anisotropic depth migration algorithms also correct for velocity changing with direction in the dipping clastic overburden. Seismic anisotropy is a well-quantified physical characteristic of clastic rocks. Studies of anisotropic behaviour in clastic rocks include Thomsen (1986), Vernik and Liu (1997), Leslie et al (1997). Several papers over the past seven years illustrate the improvements in imaging when we stop ignoring anisotropy and begin to correct for it (Ball, 1995; Vestrum and Muenzer, 1997; Vestrum, et al., 1998; Ferguson and Margrave, 1998; Schmid et al., 1998; Dai et al., 1998; Fei et al., 1998; Vestrum et al., 1999, Kirtland Grech et al, 2001; etc.). The seismic data processing case histories presented here outline the improvements in seismic imaging and structural positioning when we correct for seismic anisotropy in depth migration. Benjamin Creek The Husky/Talisman dataset is the focus of our first processing case history. In this example, I illustrate the improvement in correlation between well depths and seismic depths. Figure 1 shows this improvement. Isotropic depth migration for this line (Figure 1a) shows a typical result (Shultz and Canales, 1997; Etris et al., 2001) of isotropic depth migration where the seismic depths are deeper than the well depths. When we ignore anisotropy, we need to use a velocity faster than the vertical velocity if we are to flatten the image gathers and obtain a quality image. The anisotroic migration (Figure 1b), models the velocity behavour changing with direction, so it produces a clear image and correlates to the well depths. One can see in Figure 1b that there is still some uncertainty in the correlation, but we have removed a systematic error from the depth correlation. We could now go back and adjust our imaging velocities so that our final depth migration matched perfectly with well depths, without needing a separate depth-conversion step after the depth migration. We can now consider well depths as a constraint on our imaging velocity model. There are also several imaging improvements on the anisotropic depth migration over the isotropic depth migration. Figure 1: (a) isotropic depth migration and (b) anisotropic depth migration and overlain well depths to top and bottom of the carbonate sheet. Nordegg/Chungo The Nordegg/Chungo 3D is a Time Seismic data volume acquired in the Alberta Foothills. A more difficult imaging area than the Benjamin Creek area, this volume shows imaging problems that arise when the anisotropic overburden has dramatically changing dip. Figure 2 shows the comparison between isotropic and anisotropic depth migrations for a line out of this volume. Note the improvement in basement continuity beneath the steeply dipping near-surface when we use anisotropic depth migration (Figure 2b). Several other potential hydrocarbon-target events show similar improvement. Note that the target event, as indicated by the red arrow, shows more consistent imaging over the range of dips from the back limb over the crest of the structure and into the forelimb. The anisotropic velocity model more accurately represents the velocity structure of the overburden. With more accurate raytracing over a larger range of reflector angles, the migration is better able to image the range of reflector dips on this structure. Blackstone This Talisman dataset is a very dramatic anisotropic imaging example. The extensive folding of the clastic overburden creates difficulties imaging structures below. Figure 3 shows a comparison between poststack time migration (Figure 3a), prestack time migration (Figure 3a), prestack depth migration (Figure 3c), and prestack anisotropic depth migration (Figure 3d). Each step forward in complexity of the migration

Heterogeneity is a common phenomenon that needs to be taken into account when characterizing the elastic anisotropic properties of formations. Anisotropic elastic properties can be obtained from comprehensive borehole sonic datasets consisting of monopole compressional, dipole fast and slow shear, and Stoneley shear velocities. This can be done successfully through a methodology involving careful binning of the velocity data on the basis of independent, petrophysical information, followed by an inversion process that is carried out on each bin individually. The resulting table of anisotropic parameters per bin can then be used to derive, among other results, correlations between formation petrophysical and anisotropic properties. A new workflow was successfully applied to determine the elastic, transversely isotropic properties of heterogeneous sand-shale sequences. The results of the methodology have significant practical implications. One of these is that synthetics based on the anisotropy-corrected deviated well logs yield stronger and more apparent reflections, as well as a significantly different time-depth relation. Additional applications include the use of the inversion workflow results as inputs into anisotropic seismic velocity models and AVOs.

As the leading edge of the Indian–Asian collision, the eastern Himalayan syntaxis region has experienced extensive tectonic activities, resulting in complex crustal uplift and deformation in the corner area of the southeastern pathway for the extrusion of Tibetan plateau materials. Despite considerable efforts, the corresponding deformation mechanisms remain uncertain. This study presents a new 3D high-resolution azimuthal anisotropic shear-wave velocity model in the crust and uppermost mantle derived from ambient noise dispersion data. Results show that the upper crustal anisotropy aligns with the geological boundaries and major faults nearby, suggesting shape-preferred orientations. The upper crustal low velocity and weak anisotropy beneath the core of the eastern Himalayan syntaxis (EHS) are closely associated with the high fragmentation of shallow rocks and the upwelling of hot materials during the ongoing subduction of the Indian plate. Our model also reveals relatively complex anisotropic patterns in the midlower crust. The eastern Lhasa terrane, in particular, exhibits low velocity and strong anisotropy with a northwest–southeast-oriented fast axis, supporting the local scale midlower crustal “channel flow” model. In addition, a conspicuous, elongated low-velocity zone along the northwest–southeast direction is observed in the midlower crust and uppermost mantle beneath the Bangong–Nujiang suture. The anisotropy in this region increases with depth, and the fast directions are consistently parallel to the northeast subduction of the Indian plate. We infer that this low-velocity zone may result from partial melting under local compression driven by the Indian–Asian collision. On the basis of newly revealed anisotropic model and previous studies, we construct a new dynamic model, which reveals that the migration of mechanically weak material in the midlower crust and the significant contribution of the northeast subduction of the Indian plate jointly control the crustal deformation of the EHS region.

Seismic imaging of the magmatic plumbing system and geothermal reservoir of the Los Humeros caldera (Mexico) using anisotropic shear wave models

Summary Anisotropy can have a large impact on the accuracy of microseismic events associated with hydraulic fracture monitoring. Processing of such data relies on the detection of compressional and shear arrivals with a receiver array in a nearby monitor well. The location of these microseisms is then determined via ray tracing through a known velocity structure. Such velocity models are often assumed to be isotropic even though the sedimentary rocks such as shales, through which these p and s-waves travel, can be highly anisotropic. Significant error in the location of these microseisms can occur if anisotropy is ignored. A solution to this issue, proposed here, is to use an anisotropic ray-tracing algorithm. Knowledge of anisotropic rock parameters are required for this approach to work effectively. Typically, such parameters are determined from source shots in known locations to calibrate the velocity model along the ray paths the energy would take based on the acquisition geometry. However, such methods may be non-unique and could be impacted by potential positioning error effects in the acquisition geometry versus anisotropy effects in the rock. This method can be calibrated using the measurement of anisotropic parameters from an advanced sonic array tool. The results of a field application of this technology come from a gas shale reservoir exhibiting 10% polar anisotropy that was characterized using sonic data in a vertical pilot hole. A comparison of the microseismic events using isotropic versus anisotropic velocity models clearly demonstrate that acoustic velocity anisotropy can mislocate microseismic events by several hundred feet if

Recent seismic acquisition and anisotropic velocity modeling has resulted in improved salt definition and sub‐salt imaging at Puma and Mad Dog Fields in the Gulf of Mexico. For these fields, wide‐azimuth towed‐streamer (WATS) surveys, isotropic imaging, vertical transverse isotropy (VTI) imaging, and tilted transverse isotropy (TTI) imaging were carried out sequentially. This series offers a great opportunity to understand the impact of different levels of anisotropy approximation and why TTI reverse time migration (RTM) should be used for future WATS imaging.

The coupling–ray–theory tensor Green function for electromagnetic waves or elastic S waves is frequency dependent, and is usually calculated for many frequencies. This frequency dependence represents no problem in calculating the Green function, but may represent a great problem in storing the Green function at the nodes of dense grids, typical for applications such as the Born approximation. This paper is devoted to the approximation of the coupling–ray–theory tensor Green function, which practically eliminates this frequency dependence within a reasonably broad frequency band. In the vicinity of a given prevailing frequency, we approximate the frequency–dependent frequency–domain coupling–ray–theory tensor Green function by two dyadic Green functions corresponding to two waves described by their travel times and amplitudes calculated for the prevailing frequency. We refer to these travel times and amplitudes as the coupling–ray–theory travel times and the coupling–ray–theory amplitudes. This “prevailing–frequency approximation” of the coupling ray theory for electromagnetic waves or elastic S waves allows us to process the coupling–ray–theory wave field in the same way as the anisotropic–ray–theory wave field. This simplification may be decisive when storing the tensor Green function at the nodes of dense grids, which is typical for applications such as the Born approximation. We test the accuracy of the proposed prevailing–frequency approximation of the coupling ray theory numerically using elastic S waves in eight anisotropic velocity models. The additional inaccuracy introduced by the prevailing–frequency approximation is smaller than the inaccuracy of the standard frequency–domain coupling ray theory, and smaller than the additional inaccuracy introduced by many other approximations of the coupling ray theory.