Interval Velocity Model Research Articles

Unified imaging of multichannel seismic data: Combining traveltime inversion and prestack depth migration

Imaging 2D multichannel land seismic data can be accomplished effectively by a combination of traveltime inversion and prestack depth migration (PSDM), referred to as unified imaging. Unified imaging begins by inverting the direct-arrival times to estimate a velocity model that is used in static corrections and stacking velocity analysis. The interval velocity model (from stacking velocities) is used for PSDM. The stacked data and the PSDM image are interpreted for common horizons, and the corresponding wide-aperture reflections are identified in the shot gathers. Using the interval velocity model, the stack interpretations are inverted as zero-offset reflections to constrain the corresponding interfaces in depth; the interval velocity model remains stationary. We define a coefficient of congruence [Formula: see text] that measures the discrepancy between horizons from the PSDM image andtheir counterparts from the zero-offset inversion. A value of unity for [Formula: see text] implies that the interpreted and inverted horizons are consistent to within the interpretational uncertainties, and the unified imaging is said to have converged. For [Formula: see text] greater than unity, the interval velocity model and the horizon depths are updated by jointly inverting the direct arrivals with the zero-offset and wide-aperture reflections. The updated interval velocity model is used again for both PSDM and a zero-offset inversion. Interpretations of the new PSDM image are the updated horizon depths. The unified imaging is applied to seismic data from the Naga Thrust and Fold Belt in India. Wide-aperture and zero-offset data from three geologically significant horizons are used. Three runs of joint inversion and PSDM are required in a cyclic manner for [Formula: see text] to converge to unity. A joint interpretation of the final velocity model and depth image reveals the presence of a triangle zone that could be promising for exploration.

Cenozoic basin evolution beneath the southern McMurdo Ice Shelf, Antarctica

Fifty-two kilometres of multi-channel seismic reflection data were acquired from the southern McMurdo Ice Shelf (SMIS) during potential drill site investigations for the Antarctic Drilling (ANDRILL) program. The survey was acquired atop 110 to 220 m of floating ice and extended across ablation and accumulation zones of the ice shelf. Seismic processing was tailored to the ice shelf environment, including: datum static corrections to account for changes in the thickness and average velocity of the near-surface firn layer, and changes in the surface elevation across the survey area; residual static corrections to account for near-surface ice shelf irregularities; and two-step predictive deconvolution to suppress ice and firn layer multiples. A model for the ice shelf thickness was also incorporated in the interval velocity model during depth conversion to ensure that the ice shelf structure did not impose non-static shifts on the seismic section. The depth converted CMP stacked sections reveal several N to NE trending normal faults, that offset reflective horizons by up to 150 m within the lower part of the section and form a broad east-dipping, half-graben structure. The seafloor possesses trough and arch morphology in parallel with the half-graben structure. These features are interpreted as the southern extension of the Terror Rift. The rift succession comprises a dislocated (?)early-Miocene synrift package and a relatively undeformed (?)late-Miocene post-rift package separated by an erosional unconformity. The post-rift package infills and onlaps the rift topography, and drapes over the graben system, reaching a maximum thickness of 400 m. Throughout the post-rift phase, the basin was also influenced by Neogene volcanism, evidenced by three small volcanic features within the seismic profiles, and associated successions of inferred volcanic material. An angular unconformity within the post-rift succession is interpreted as a flexural horizon related to the load of Mount Discovery and/or Mount Morning. Up to 150 m of flexural moat fill occurs above this surface at ~ 20 km from the load centres. The post-rift succession also includes several glacio-geomorphic features, the orientation and morphology of which indicate an approximately SW to NE ice flow direction during a mid-Miocene grounding event and a SE to NW ice flow direction during Quaternary ice sheet grounding events. The thickness and lower extent of the rift succession was not able to be determined because signal-to-noise ratio and vertical resolution were low at these depths. Strata from an earlier, Paleogene, rift episode may underlie the Terror Rift succession, or it may be directly underlain by acoustic basement. A Paleogene rift episode has previously been proposed based on the occurrence of Eocene fossiliferous erratics around the margin of the SMIS and the structural setting revealed by the SMIS seismic reflection profiles is consistent with this hypothesis.

Resolving fault shadow problem by Fault Constrained Tomography

In many areas, so-called, Fault Shadows is a serious hindrance to successful seismic imaging. The major part of this problem is caused by large velocity variations in fault zones. Fault zones contain different types of geological and imaging velocity anomalies that cause seismic image distortions and non-hyperbolic moveout. Pre-stack depth migration with the proper velocity model is the only method that can solve this problem and improve the seismic image below fault zones. We have developed a special and novel technique, Fault Constrained Tomography, to build high-resolution interval velocity models that are required for fault areas. Fault Constrained Tomography takes into account the nature of velocity variation within fault zones. Combined with Pre-Stack Depth Migration it can successfully remove fault shadow distortions from seismic images.

Interval velocity estimation via NMO-based differential semblance

The differential semblance method of velocity analysis flattens image gathers automatically by updating interval velocity to minimize the mean square difference of neighboring traces. We detail an implementation using hyperbolic normal moveout correction as the imaging method. The algorithm is fully automatic, accommodates arbitrary acquisition geometry, and outputs 1D, 2D, or 3D interval velocity models. This variant of differential semblance velocity analysis is effective within the limits of its imaging methodology: mild lateral heterogeneity and data dominated by primary events. Coherent noise events such as multiple reflections tend to degrade the quality of the velocity model estimated by differential semblance. We show how to combine differential semblance velocity analysis with dip filtering to suppress multiple reflections and thus improve considerably the accuracy of the velocity estimate. We illustrate this possibility using multiple-rich data from a 2D marine survey.

Velocity and AVO analysis for the investigation of gas hydrate along a profile in the western continental margin of India

The occurrence of gas hydrate has been inferred from the presence of Bottom-Simulating Reflectors (BSRs) along the western continental margin of India. In this paper, we assess the spatial and vertical distribution of gas hydrates by analyzing the interval velocities and Amplitude Versus Offset (AVO) responses obtained from multi-channel seismics (MCSs). The hydrate cements the grains of the host sediment, thereby increasing its velocity, whereas the free gas below the base of hydrate stability zone decreases the interval velocity. Conventionally, velocities are obtained from the semblance analysis on the Common Mid-Point (CMP) gathers. Here, we used wave-equation datuming to remove the effect of the water column before the velocity analysis. We show that the interval velocities obtained in this fashion are more stable than those computed from the conventional semblance analysis. The initial velocity model thus obtained is updated using the tomographic velocity analysis to account for lateral heterogeneity. The resultant interval velocity model shows large lateral velocity variations in the hydrate layer and some low velocity zones associated with free gas at the location of structural traps. The reflection from the base of the gas layer is also visible in the stacked seismic data. Vertical variation in hydrate distribution is assessed by analyzing the AVO response at selected locations. AVO analysis is carried out after applying true amplitude processing. The average amplitudes of BSRs are almost constant with offset, suggesting a fluid expulsion model for hydrate formation. In such a model, the hydrate concentrations are gradational with maxima occurring at the base of hydrate stability zone.

Residual stereotomographic inversion

Depth migration requires highly accurate knowledge of the subsurface velocity field. Different traveltime tomographic methods are used for this purpose. Stereotomography is a tomographic method that uses local dip estimates in addition to traveltimes for velocity model estimation. We present a new methodology for velocity model updating. It combines poststack stereotomography and residual moveout velocity inversion. The former is used for initial model construction and the latter for updating the velocity model. Residual inversion is a kind of stereotomographic inversion applied to common reflection point (CRP) gathers after model-based moveout correction. Velocity analysis can be made more efficient by preselecting the traces that contribute to a series of CRP gathers and using only these traces for inversion. The algorithm is defined in a two-step procedure. First, ray tracing from the reflection point for nonzero reflection offsets defines the source and receiver locations of the data traces in the CRS gather. Then these traces are moveout corrected according to the calculated traveltimes and residual moveout is estimated. The interval velocity model is updated by fitting the velocity that minimizes estimated residuals. Application of the proposed technique demonstrates its robustness and reliability for fast and automatic velocity model estimation.

Velocity-independent layer stripping of PP and PS reflection traveltimes

Building accurate interval velocity models is critically important for seismic imaging and AVO (amplitude variation with offset) analysis. Here, we adapt the [Formula: see text] method to develop an exact technique for constructing the interval traveltime-offset function in a target zone beneath a horizontally layered overburden. All layers in the model can be anisotropic, with an essential assumption that the overburden has a horizontal symmetry plane (i.e., up-down symmetry). Our layer-stripping algorithm is entirely data-driven and, in contrast to the generalized Dix equations, does not require knowledge of the velocity field anywhere in the medium. Important advantages of our approach compared to the Dix-style formalism also include the ability to handle mode-converted waves, long-offset data, and laterally heterogeneous target layers with multiple, curved reflectors. Numerical tests confirm the high accuracy of the algorithm in computing the interval traveltimes of both PP- and PS-waves in a dipping, transversely isotropic layer with a tilted symmetry axis (TTI medium) beneath an anisotropic overburden. In combination with the inversion techniques developed for homogeneous TTI models, the proposed layer stripping of PP and PS data can be used to estimate the interval parameters of TTI formations in such important exploration areas as the Canadian Foothills. Potential applications of this methodology also include the dip-moveout inversion for the P-wave time-processing parameter [Formula: see text] and stable computation of the interval long-spread (nonhyperbolic) moveout for purposes of anisotropic velocity analysis.

Pre-stack 3-D Tau migration and velocity analysis: application to 3-D seismic data from offshore Abu Dhabi, United Arab Emirates

ABSTRACT A pre-stack 3-D Tau migration was applied to a 3-D seismic data set acquired in offshore Abu Dhabi, United Arab Emirates. The velocity model was built through an initial series of 2-D Tau migration velocity analysis, and supplemented by 3-D subset migration. A 3-D Tau migration velocity analysis was used for the final two updates of the model. The final interval velocity model provided low residuals in the common-image gathers from different offsets and was consistent with velocities from four wells located in the region. This velocity model included the main known features of the region including a low-velocity zone and a major fault. A final 3-D pre-stack Tau migration was applied using the velocity model and a relatively moderate aperture. This migration imaged the region including part of the critical poor data quality region, which includes the reservoir as well as reflections from the fault. Based on the derived velocity model, we concluded that the major cause for the poor image is the presence of a shallow high-velocity anomaly separated by a fault from a low-velocity anomaly.

Traveltime inversion of vertical radar profiles

Traveltimes of direct arrivals in vertical radar profiles (VRPs) are tomographically inverted to estimate the earth’s electromagnetic (EM) velocity between a surface transmitter and a downhole receiver. We determine the 1D interval velocity model that best fits the first-arrival traveltimes by using a weighted, damped, least-squares inversion scheme. We assess the accuracy of the velocity model using synthetic traveltimes from a known velocity-distribution model simulating an unconfined aquifer. The inverted velocity profile closely matched the velocity profile of the input model in the synthetic examples. Using vertical radar profile data from an unconfined aquifer near Boise, Idaho, we inverted traveltimes to obtain velocity estimates at the well location. The velocity change at a depth of [Formula: see text] corresponds well with the measured depth to the water table of [Formula: see text], and at depths between 2 and [Formula: see text], the velocities ranged between 0.06 and [Formula: see text]. Our estimates approximately match the velocity distribution determined from neutron-derived porosity logs at depths greater than about [Formula: see text]. An important function of inverse methods is to assess (quantitatively and qualitatively) the uncertainty of inverted velocity estimates. We note that the velocity values in the upper and lower parts of the inverted model are not as well constrained compared to those between the depths of 4 and [Formula: see text]. From the model resolution and model covariance matrices of the real-data inversion, we determine the uncertainty in our velocity model, leading to more reliable interpretations of the subsurface.

Straight-rays redatuming: A fast and robust alternative to wave-equation-based datuming

Wave-equation-based redatuming is expensive and requires a detailed knowledge of the shallow velocity field. We derive the analytical expression of a new prestack wavefield extrapolation operator, the Topographic Datuming Operator (TDO), which applies redatuming based on straight-rays approximation above and below a chosen datum. This redatuming operator is directly applied to common-source gathers to downward continue the source and the receivers, simultaneously, to the datum level without resorting to common-receiver gathers. As a result, the method is far more efficient and robust than the conventional wave-equation-based redatuming and does not require an accurate depth-domain interval velocity model. In addition, TDO, unlike wave-equation-based redatuming, requires effective velocities above datum, and thus can be applied using attributes valid for static correction methods. Effective velocities beneath the datum permit us to replace the surface integral, which is needed for wave-equation redatuming with a line integral. In the particular case of infinite (in practice, very high with respect to the shallow layers) velocity beneath the datum, the TDO impulse response collapses to a point, and TDO redatuming is equivalent to conventional static correction, which may, therefore, be regarded as a special case of the newly derived operator. The computational cost of applying TDO is slightly larger than static corrections, yet provides higher quality results partially attributable to the ability of TDO to suppress diffractions emanating from anomalies above datum. Since TDO is an operation based on geometrical optics approximation, velocity after TDO is not biased by the vertical shift correction associated with conventional static correction. Application to a synthetic data set demonstrates the features of the method.

τ‐migration and velocity analysis: application to data from the Red Sea

ABSTRACTImaging pre‐salt reflections for data acquired from the coastal region of the Red Sea is a task that requires prestack migration velocity analysis. Conventional post‐stack time processing lacks the lateral inhomogeneity capability, necessary for such a problem. Prestack migration velocity analysis in the vertical time domain reduces the velocity–depth ambiguity that usually hampers the performance of prestack depth‐migration velocity analysis. In prestack τ‐migration velocity analysis, the interval velocity model and the output images are defined in τ (i.e. vertical time). As a result, we avoid placing reflectors at erroneous depths during the velocity analysis process and thus avoid inaccurately altering the shape of the velocity model, which in turn speeds up the convergence to the true model. Using a 1D velocity update scheme, the prestack τ‐migration velocity analysis produces good images of data from the Midyan region of the Red Sea. For the first seismic line from this region, only three prestack τ‐migration velocity analysis iterations were required to focus pre‐salt reflections in τ. However, the second line, which crosses the first line, is slightly more complicated and thus required five iterations to reach the final, reasonably focused, τ‐image. After mapping the images for the two crossing lines to depth, using the final velocity models, the placements of reflectors in the two 2D lines were consistent at their crossing point. Some errors occurred due to the influence of out‐of‐plane reflections on 2D imaging. However, such errors are identifiable and are generally small.

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.

Bedrock imaging using post-critical shallow seismic reflection data

We acquired shallow seismic reflection data in an unusual range of offsets greater than critical distance, and examined the feasibility and consequences of processing these post-critical reflections using conventional seismic reflection procedures. The main motivations to develop this work were: (i) the reflections observed at larger offsets are sharper and stronger than at near offsets, and (ii) it is possible to select a broad optimum offset window, which will speed up the execution of a seismic reflection survey. In order to accomplish the proposed task, refraction data and elastic reflection modelling were integrated into processing of reflection data and their interpretation. The information from the refracted arrivals was used to image the shallower reflector (dry unconsolidated overburden), to estimate the interval velocity model above the bedrock, and to perform static correction. The elastic reflection modelling was decisive to perform the post-critical seismic reflection survey, and to check the reliability of our interpretation. The lithologic log information corroborated the feasibility of imaging subsurface structure from post-critical reflection data by conventional processing, provided additional velocity-depth information is integrated in the reflection processing.

Incorporating geologic information into reflection tomography

In areas of complex geology, prestack depth migration is often necessary if we are to produce an accurate image of the subsurface. Prestack depth migration requires an accurate interval velocity model. With few exceptions, the subsurface velocities are not known beforehand and should be estimated. When the velocity structure is complex, with significant lateral variations, reflection‐tomography methods are often an effective tool for improving the velocity estimate. Unfortunately, reflection tomography often converges slowly, to a model that is geologically unreasonable, or it does not converge at all. The large null space of reflection‐tomography problems often forces us to add a sparse parameterization of the model and/or regularization criteria to the estimation. Standard tomography schemes tend to create isotropic features in velocity models that are inconsistent with geology. These isotropic features result, in large part, from using symmetric regularization operators or from choosing a poor model parameterization. If we replace the symmetric operators with nonstationary operators that tend to spread information along structural dips, the tomography will produce velocity models that are geologically more reasonable. In addition, by forming the operators in helical 1D space and performing polynomial division, we apply the inverse of these space‐varying anisotropic operators. The inverse operators can be used as a preconditioner to a standard tomography problem, thereby significantly improving the speed of convergence compared with the typical regularized inversion problem. Results from 2D synthetic and 2D field data are shown. In each case, the velocity obtained improves the focusing of the migrated image.

Tau migration and velocity analysis: Theory and synthetic examples

Prestack migration velocity analysis in the time domain reduces the velocity‐depth ambiguity usually hampering the performance of prestack depth‐migration velocity analysis. In prestack τ migration velocity analysis, we keep the interval velocity model and the output images in vertical time. This allows us to avoid placing reflectors at erroneous depths during the velocity analysis process and, thus, avoid slowing down its convergence to the true velocity model. Using a 1D velocity update scheme, the prestack τ migration velocity analysis performed well on synthetic data from a model with a complex near‐surface velocity. Accurate velocity information and images were obtained using this time‐domain method. Problems occurred only in resolving a thin layer where the low resolution and fold of the synthetic data made it practically impossible to estimate velocity accurately in this layer. This 1D approach also provided us reasonable results for synthetic data from the Marmousi model. Despite the complexity of this model, the τ domain implementation of the prestack migration velocity analysis converged to a generally reasonable result, which includes properly imaging the elusive top‐of‐the‐reservoir layer.

Multiple prediction without prestack data - an efficient tool for interpretive processing

Multiple-attenuation during data processing does not guarantee a 'multiple-free' final section. Although a great deal of effort has been given to the problem of multiple-suppression (Berryhill and Kim 1986; Wiggins 1988; Verschuur et al. 1992; and others), perfect solutions still do not exist. When the subsurface structure is complex, the remaining multiples will be difficult to recognize, especially after the data have been migrated. In addition, many of the available multiplesuppression techniques are restricted to two-dimensional geometries and do not attempt to handle interbed and complex multiples (which consist of a combination of interbed and surface-related multiples). These restrictions further increase the possibility of obtaining undesired multiple energy in the final sections. Generally speaking, multiple prediction is used as an initial step for multiple suppression. The predicted multiples must be very accurate, both kinematically and dynamically, since the suppression operation involves subtraction of multiple energy from the recorded data. Therefore, standard multiple-prediction algorithms require manipulation of prestack data or an accurate forward-modelling technique based on a given interval velocity model of the subsurface. While interpreting data from areas where significant multiple energy has been recorded, the interpreter must rely on the success of the multiple-suppression operation. When it is suspected that a certain event is a multiple, it is difficult to verify this using standard interpretation tools. We believe that multiple prediction and identification can play an important role in seismic interpretation. The main obstacle preventing multiple-prediction procedures from being routinely used by interpreters is the necessity to access prestack data. Velocity analysis in an interpretive process that may become difficult to carry out in the presence of multiples (Gasparotto and Lau 2000). It is often the analyst's decision to distinguish between primary and multiple energy while picking velocities. If the multiple-prediction procedure can provide information on the velocity that will optimally stack the multiple energy, it could be used as a guideline during velocity analysis to help in avoiding erroneous velocity picks. This study is based on the assumption that if the prediction is not aimed at providing input to multiple-suppression algorithms, then it can become a purely kinematic procedure. Furthermore, without prestack data, interactive algorithms, highly suitable for interpretive work, can be developed on the basis of the proposed procedure. In the following, we briefly describe the concept of the prediction method. We then show how the need to access prestack data is avoided, thus permitting fast interactive prediction after stack and/or migration. Finally, we suggest a practical workflow to promote prediction during interpretation and standard velocity-analysis sessions. All the above procedures will be illustrated using synthetic and field data examples.

3D Pre‐Stack Depth Migration V0 Analysis and Monte Carlo Automatic Velocity Picking in Depth

AbstractThe key issue for the success of 3D pre‐stack depth migration is how to make a reasonable interval velocity model in depth. In this paper, a robust method has been developed to effectively set up velocity‐depth models. According to Deregowski loop, the best migration velocity can be approached by cascade migration based on the sensibility of seismic imaging to velocity variation. Within CRP gather, the concept of squared residual slowness semblance was first proposed that is similar with the routine stack velocity semblance of CDP gather in time, and it had been put into practice. The relationship between stack velocity and interval velocity was deduced in depth. On cascade migration, the initial velocity, residual velocity, and modified velocity are mathematically united during the migration iterations. Within squared residual slowness semblance, the velocity picking is automatically achieved by Monte Carlo nonlinear optimizing. In order to make the picked velocity reasonable in geology, velocity constraints are given in velocity picking and convergence criteria are forced during the Monte Carlo nonlinear optimizing. Data tests with SEG‐EAEG data and 58km2 Hailaer 3D seismic data have shown good prospects of this method, some improved seismic imaging and accurate velocity models were achieved. This algorithm can be used to quickly establish a velocity model in depth, and it also will reduce the processing costs, which makes the method suitable for velocity analysis of large area 3D survey.

Migration Velocity Analysis Using Seismic Multiples

Migration velocity analysis (MVA) is a powerful tool for determining the interval velocity model in regions of complex geology. It is based on the fact that the migration process is sensitive to changes in the velocity model. Only when the migration velocity is equal to the interval velocity of a layer will that event be horizontally aligned in a migrated common image gather (CIG) (a CIG is a gather containing traces from the same surface location but from different migrated shot gathers). This is equivalent to saying that the image of the subsurface should be in the same location regardless of the source position. Conventional analysis is concerned with utilising primary events and these alone for the determination of interval velocity. However, it has been found that a greater accuracy can be obtained by utilising multiple events which are normally considered as noise and removed prior to MVA. The new technique is based on the fact that any initial error in velocity between the migration and interval velocities will be increased as the distance travelled through the Earth increases. Hence in migration, multiples will be more sensitive than primaries to changes in the velocity model. Two synthetic examples are presented to demonstrate this. Both show that on a coherency plot, multiples will stack in a more localised region. This should result in increased accuracy in determining interval velocity and subsequently interval thickness. It should also reduce the number of migration iterations needed to converge on an accurate solution. This has implications for reducing the time and cost of the MVA process.

Crustal velocity structure along the Nagaur–Rian sector of the Aravalli fold belt, India, using reflection data

Deep reflection data was collected along the Nagaur–Nandsi profile, Rajasthan (across the Aravalli fold belt), India, to study the tectonic pattern and evolutionary history of the Northwestern Indian Shield. However, as there was no coincident wide-angle/refraction input/well data input, no velocity picture could be derived to supplement the reflection results. In the present study, as velocity information is very important for a realistic analysis of the reflection time sections, we have used the interval velocity derived from stack velocities (Hubral, P. and Krey, T., 1980. In: Larner, K.I. (Ed.), Interval Velocities from Seismic Reflection Time Measurements. SEG, Tulsa, OK), to arrive at a possible velocity-depth section, along the 90-km Nagaur-Rian sector. This was followed by dynamic forward modeling, using the interval velocity model as the starting model. The resultant velocity depth section has a four-layer structure. One of the layers (third) is a low-velocity layer. The lateral extension of this layer vis-à-vis with other layers is presented, for a better understanding of the structure and tectonics of the Aravalli-Delhi fold belt.

Illuminating the shadows: tomography, attenuation and pore pressure processing in the South Caspian Sea

A new approach was successfully applied to produce better images through seismic shadow zones. These zones are caused by the existence of shallow low velocity zones and are a problem to interpretation efforts in the South Caspian Sea. A combination of careful wavelet processing with offset domain amplitude compensation and prestack tomographic inversion produced significantly improved images compared to conventional processing. Visco-acoustic modeling was successfully applied to investigate the effects of seismic attenuation in the seismic shadow zones. Forward modeling results with different Q values were compared to the seismic data and the best model fit to the seismic data determined. The final results indicate that the seismic shadow zones have a low Q in the order of 30 compared to 120 outside the anomaly. Q values of 175 were predicted for deeper zones in the seismic data. A detailed interval velocity model derived from the tomographic inversion analysis was also successfully used to make accurate pore pressure and fracture pressure predictions from the seismic data. After calibration to available well information, the pressure predictions were used to construct a mud weight and mud circulation warning display. The information provides drilling with pressure estimates that allow for better planning that can affect both cost and safety in drilling. Knowledge of the difference in pore pressure and rock fracture pressure is useful in designing casing points and deciding on mud weights to use during drilling. Pore pressures in the medium overpressure range which can possibly represent drilling hazard were predicted in this study.