Migration Velocity Model Research Articles

Basin-scale integrated earth-model building using rock-physics constraints

Earth modeling plays a decisive role in seismic imaging. Presently, methods such as tomography and full-waveform inversion (FWI) are widely used to generate 3D high-resolution velocity models across sedimentary basins. However, given the nonunique nature of the solution, the relative fidelity of these velocity models remains low. Moreover, earth-model building must incorporate a dual strategy. In particular, it must derive a velocity model for migration and yield a series of rock properties such as density, temperature, effective stress, and pore pressure. These large-scale, basin-sized rock properties are used for drilling purposes and as an initial model for small-scale reservoir property inversion. Hence, one must inquire: How can we improve an earth model built at basin-scale using seismic data? Traditional workflows will simply convert seismic-derived velocity into rock properties, thereby propagating the uncertainty without addressing the issue. To alleviate this problem and fully exploit the potential of seismic data, an alternate workflow will be discussed. The new workflow involves using rock physics to link rock properties with velocity, and the physical range of the rock properties is used to constrain velocity when derived from surface seismic data; this way we reinforce the reliability of the final earth model. The application of this new workflow is demonstrated using Gulf of Mexico examples.

Velocity analysis of simultaneous-source data using high-resolution semblance—coping with the strong noise

Direct imaging of simultaneous-source (or blended) data, without the need of deblending, requires a precise subsurface velocity model. In this paper, we focus on the velocity analysis of simultaneous-source data using the normal moveout-based velocity picking approach.We demonstrate that it is possible to obtain a precise velocity model directly from the blended data in the common-midpoint domain. The similarity-weighted semblance can help us obtain much better velocity spectrum with higher resolution and higher reliability compared with the traditional semblance. The similarity-weighted semblance enforces an inherent noise attenuation solely in the semblance calculation stage, thus it is not sensitive to the intense interference. We use both simulated synthetic and field data examples to demonstrate the performance of the similarity-weighted semblance in obtaining reliable subsurface velocity model for direct migration of simultaneous-source data. The migrated image of blended field data using prestack Kirchhoff time migration approach based on the picked velocity from the similarity-weighted semblance is very close to the migrated image of unblended data.

Velocity analysis using zero-offset attributes in common source domain

SUMMARY Velocity analysis is one of the most critical stages in seismic data processing and the velocity errors influence the accuracy of the imaging. The conventional workflows, to obtain the migration velocity model, are generally labour intensive and time consuming. An experienced processor is needed to pick the velocities in the velocity spectrum. In this paper, we introduce another approach to obtain the velocity model using the first derivative of time with respect to offset (local slopes) in one domain, common source domain. In this time- effective approach, one order of differentiation has been reduced from the previous velocity analysis in common source domain, using zero-offset attributes. This velocity analysis and imaging are being done at the same time. There is no need to have any velocity model prior to imaging in this approach. The accuracy of the velocity analysis method is more robust than the previous technique because of the reduction in order of the derivatives needed. Computational experiments with synthetic seismic data examples confirm the theoretical expectations and demonstrate the feasibility of the proposed technique.

High-density point-receiver seismic survey of a deep carbonate cave reservoir system: a case study from the Tarim Basin, Western China

In the northern rim of the Tarim Basin, western China, oil is being produced from an extensive system of interconnected caves, faults and fractures in Ordovician carbonates buried about 6000 to 7000 m below the surface. Although onshore, drilling costs are high due to the depth of the field, so, to produce the field economically, wells must be accurately located within the cavernous features to access as large a drainage area as possible. However, imaging fine details of the reservoir structures presents challenges due to a complex overburden. While the surface terrain and near-surface geology are relatively benign for land seismic operations, the subsurface exhibits large lateral velocity changes related to widely distributed Permian volcanic formations around 1000 and 1200 m above the target zone. These formations are considered to have led to errors in the imaging of the target layers in legacy datasets due to incorrect velocity modelling of the overburden. Improved imaging of detailed features of the deep cavernous carbonate reservoir beneath the complex overburden would require an accurate velocity model in addition to seismic data with both high temporal and spatial resolution. To determine whether new land seismic acquisition and processing technologies could provide a significant uplift in imaging quality, in 2013 PetroChina Tarim Oil Company (TOC) acquired a high-density full-azimuth 3D seismic survey using a point-source and point-receiver geometry. The dataset was recorded using an advanced high-channel count acquisition system and processed with high-end processing techniques designed to address the various challenges presented in the area. Three approaches were used over different depth ranges to develop an accurate velocity model for prestack depth migration (PSDM). Model velocities were constrained using available well data, providing confidence in the accuracy of the resulting image. Relative amplitude preserving (RAP) methods were used for noise attenuation and signal processing to maximise the reliability of subsequent inversion and interpretation work.

Assessing seismic uncertainty via geostatistical velocity-model perturbation and image registration: An application to subsalt imaging

Seismic data play a critical role in reservoir forecasting and decision making. However, large uncertainties are associated with seismic data, many of which arise from depth migration and the absence of accurate velocity models. Moreover, because of the computational and labor costs associated with velocity-model building, generally only a single seismic image and interpretation are performed. In that sense, seismic uncertainty largely is neglected in the reservoir-modeling workflow. A novel framework for assessing this uncertainty combines geostatistics with image-registration techniques. A novel geostatistical perturbation algorithm is used to generate multiple velocity models which are verified to be consistent with observed geophysical data. To alleviate the computational bottlenecks associated with migration, a distance-based model-selection step is performed to select a representative subset of the velocity models for depth migration. Image registration in combination with manual interpretation is used to generate a set of interpretations. This allows for direct linking of seismic-velocity uncertainty to the positional uncertainty of imaged structures. The workflow is demonstrated for a subsalt imaging case using the SEG Advanced Modeling (SEAM) model.

Lithospheric structure of the Texas‐Gulf of Mexico passive margin from surface wave dispersion and migrated Ps receiver functions

AbstractThe seismic velocity structure beneath Texas Gulf Coastal Plain (GCP) is imaged by migrating Ps receiver functions with a seismic velocity model found by fitting surface wave dispersion. We use seismic data from a linear array of 22 broadband stations, spaced 16–20 km apart. A Common Conversion Point (CCP) stacking technique is applied to earthquake data to improve the S/N ratios of receiver functions. Using an incorrect velocity model for depth migration of a stacked CCP image may produce an inaccurate image of the subsurface. To find sufficiently accurate P and S‐velocity models, we first apply a nonlinear modeling technique to fit Rayleigh wave group velocity dispersion via Very Fast Simulated Annealing. Vs ranges from 1.5 km/s in shallow layers of the GCP to 4.5 km/s beneath the Llano uplift and just outboard of the Balcones Fault Zone (BFZ). The BFZ is characterized by slow velocities that persist to nearly 100 km depth. In the stacked image, the largest amplitude positive‐polarity event ranges from the surface, at the Llano uplift, to a maximum depth of ∼16 km beneath Matagorda Island. We attribute this event to the sediment‐basement contact, which is expected to produce a large impedance contrast. Another large‐amplitude and positive‐polarity event at ∼35 km depth, which likely marks the Moho, disappears outboard of the Luling Fault Zone. The disappearance of the Moho beneath the GCP may be due to serpentinization of the upper mantle, which would reduce the impedance contrast between the lower crust and upper mantle dramatically.

Anisotropic effects on the near surface seismic imaging

ABSTRACTAnisotropic effects have been widely considered in seismic subsurface imaging but rarely for the near‐surface area. The near‐surface area is often assumed isotropic. Seismic refraction methods are often applied to infer a shallow velocity model, either for making static corrections or for building the top portion of a pre‐stack depth migration velocity model. To study the anisotropic effects on the refractions and the near‐surface imaging results, we design numerical models with horizontal‐transverse‐isotropy anisotropic parameters assigned in the shallow layers and perform three‐dimensional seismic ray‐tracing with the consideration of horizontal‐transverse‐isotropy anisotropy to calculate the first‐arrival travel times. Then, we assume the near‐surface area “isotropic” and invert a near‐surface velocity model using isotropic travel‐time tomography. Through these tests, we have identified that the footprints of the recording geometry could be mapped into the velocity model, and high‐velocity anomalies are produced right above the refractor if the horizontal‐transverse‐isotropy anisotropy is ignored. By applying the azimuth‐dependent travel‐time tomography, we could account for anisotropic effects and infer the fast and slow velocity models to determine the direction of the symmetry axis. With the same approach, we process a three‐dimensional real data set, and the results are consistent with the local geology.

Prestack time-migration velocity analysis using remigration trajectories

We have developed a prestack time-migration tool for local improvement of the seismic migration-velocity model. The method is based on remigration trajectories that describe the position of an image point in the image domain for different source-receiver offsets as a function of the migration velocity. It determines kinematic migration parameters using local-slope information of migrated seismic reflection events. These parameters, in turn, are used to locally correct the velocity model. The main advantage of this technique is that it allows us to carry out a moveout correction not just at a fixed point in a zero-offset (poststack) time-migrated gather, but varying through all offsets of a common-image gather, taking into account the reflection-point displacement in the midpoint direction. In other words, it provides for time-migration velocity analysis from prestack data. We have tested the feasibility of the method on synthetic data from four simple models and the Sigsbee2B data. Our tests determined that the proposed tool increases the velocity-model resolution and provides a plausible time-migrated image. The quality of the initial model is not critical. The procedure is quite efficient. Significant effort was spent on manual event picking.

Application of Mixture of Gaussian Clustering on Joint Facies Interpretation of Seismic and Magnetotelluric Sections

Seismic and magnetotelluric (MT) methods are the most applicable geophysical methods in exploration of hydrocarbon resources. In this paper, mixture of Gaussian clustering is used to combine seismic and MT images under the scheme of Expectation/Maximization (EM) algorithm. Pre-Stack Depth Migration (PSDM) velocity, Root Mean Square (RMS) velocity and vertical gradient of RMS velocity of seismic and resistivity model of MT along 19.3 km MUN-21 profile in Munir Block that has been located in Southwest of Iran in Dezful embayment over the Seh-Qanat anticline are applied. The anticline is the most important oil trap of this area. The Expectation/Maximization (EM) method that has been applied includes: (1) creation of data vectors from the seismic and MT images using image processing techniques, (2) normalizing and mapping using Principal Component Analysis (PCA) procedure (3) unsupervised learning of dataset matrix, (4) setting the matrix in Expectation/Maximization (EM) iteration algorithm (5) remapping to physical space. The final model consists fof six classes which could be given to eight formations that belong to Eocene to Neocomian geological age. Pre-Stack Depth Migration (PSDM) velocity model obtained from seismic study on Seh-Qanat anticline only detected 2 horizons of formations, Asmari and Sarvak Formations; however, the current methodology introduces subdivision anticline into six classes by matching it to the log information of Seh-Qanat Deep-1 (SQD-1) borehole where it was excavated over the anticline with total depth of 2876 m.

Removing smearing-effect artifacts in angle-domain common-image gathers from reverse time migration

Local plane-wave decomposition (LPWD) and local shift imaging condition (LSIC) methods for extracting angle-domain common-image gathers (ADCIGs) from prestack reverse time migration are based on the local plane-wave assumption, and both suffer from a trade-off in choosing the local window size. Small windows produce clean ADCIGs, but with low angle resolution, whereas large windows produce noisy ADCIGs, which include smearing-effect artifacts, but with high angle resolution. The cause of the smearing-effect artifacts in LPWD is the crosscorrelation of plane waves obtained by decomposition of the source and receiver wavefronts, at points that do not lie on the source wavefront excitation time trajectory. The cause of the smearing-effect artifacts in LSIC is the decomposition of curved events of offset-domain common-image gathers (ODCIGs) at incorrect depth points at zero offset. These artifacts can occur even if the migration velocity model is correct. Two methods were proposed to remove the artifacts. In the LPWD method, the smearing-effect artifacts were removed by decomposing and crosscorrelating the resulting source and receiver plane waves only at image points and excitation (image) times. In the LSIC method, the artifacts were removed by decomposing curved events in ODCIGs into planar events only at zero-offset target image points. Numerical tests with synthetic data revealed the success of the proposed methods.

Sensitivity-kernel-based tomographic migration velocity analysis using reverse time migration angle-image gathers

Sensitivity-kernel-based tomographic migration velocity analysis (TMVA) provides a means to better update the migration velocity model in complex media. For actual seismic data with finite-frequency bandwidth, migration velocity updated from wave-equation-based tomography is more suitable and robust than ray-based tomography for images obtained from reverse time migration (RTM). Depth residuals in the RTM-extracted angle-image gathers offer a reliable source of velocity information. We have developed cost-effective means of calculating the angle-domain sensitivity kernel and incorporated it into the TMVA approach using RTM angle-image gathers. The angle-domain sensitivity kernels are used to convert the depth residuals from RTM angle-image gathers into velocity perturbations, which were then used to refine the velocity model. We derived an approximate analytical residual moveout function for measuring depth residuals of the RTM angle-image gather in isotropic media and also devised a workflow for sensitivity-kernel-based TMVA. The workflow maintains the simplicity of ray-based tomography by replacing the rays with the more accurate angle-domain sensitivity kernels. We determined the capability of this method in updating migration velocity with the 2D Sigsbee2 model and the 3D SEAM model. Our method significantly improved the quality of the migrated depth image and flattened the RTM angle-image gathers.

Improving input/output performance in 2D and 3D angle-domain common-image gathers from reverse time migration

We have developed a new method of extracting angle-domain common-image gathers (ADCIGs) from prestack reverse time migration (RTM) that has minimal intermediate storage requirements. To include multipathing, we applied an imaging condition for prestack RTM that uses multiple excitation image times. Instead of saving the full-source snapshots at all time steps, we picked and saved only a few of the highest amplitude arrivals, and their corresponding excitation times, of the source wavefield at each grid point, and we crosscorrelated with the receiver wavefield. When extracting the ADCIGs from RTM, we calculated the source propagation direction from the gradient of the excitation times. The result was that the source time snapshots do not have to be saved or reconstructed during RTM or while extracting ADCIGs. We calculated the receiver propagation direction from Poynting vectors during the receiver extrapolation at each time step and the reflector normal direction by the phase-gradient method. With a new strategy that uses three direction vectors (the source and receiver propagation directions as well as the reflector normal direction), we provided more reliable ADCIGs that are free of low-wavenumber artifacts than any two of them do separately, when the migration velocity model was near to the correct velocity model. The 2D and 3D synthetic tests demonstrated the successful application of the new algorithms with acceptable accuracy, improved storage efficiency, and without an input/output bottleneck.

Improved imaging of the Strzelecki Formation by the reprocessing of 3D seismic reflection data: onshore Gippsland Basin, Australia

The Wombat 3D seismic survey was recorded by Lakes Oil in 2008 following the drilling of the Wombat–3 well. The survey was aimed at identifying the structures better inside the Strzelecki Formation and the underlying Rintoul Creek Sandstone, and to give a better understanding of the provenance of the gas encountered in the first three Wombat wells and the oil encountered at depth in the Wombat–3 well. Seismic acquisition design and processing in this area are challenged by the presence of coal measures in the Latrobe Group, which overlies the zone of interest, absorbs most of the incident seismic energy and complicates seismic imaging through the generation of multiple reflection events. A novel approach, described as multi-line decomposition, modelling and synthesis, was developed to model critical imaging parameters and in particular the velocity model for midpoint stacking and migration. This approach is demonstrated through the reprocessing of the Wombat 3D seismic survey and is compared with a conventional 3D processing approach and original survey processing examples. The reprocessed seismic section provides a significantly improved image of the deeper structures, delineating a number of continuous reflectors in the Early Cretaceous formations. It also provides the opportunity to build a more accurate model of the basement.

Seismic imaging of subsurface structure using tomographic migration velocity analysis: a case study of South China Sea data

Seismic migration algorithms are often used to reveal subsurface structures and can be roughly divided into stacking methods, pre-stack time migration methods and pre-stack depth migration methods. In theory, pre-stack depth migration methods can provide the most accurate subsurface images. However, these methods are sensitive to the accuracy of the migration velocity model, and thus the creation of a precise migration velocity model is one of the most important steps in seismic processing. We applied the tomographic travel-time inversion and the method of pre-stack Kirchhoff depth migration-based migration velocity analysis (MVA) to certain South China Sea data, in which we iteratively inverted the precise, high-resolution migration velocity model. We selected travel-time differences from the offset-domain common image gathers of the pre-stack Kirchhoff depth migration and inverted the travel-time differences for velocity updating. After several iterations, both the precise migration velocity model and the corresponding pre-stack depth migration image were obtained. The comparisons with Normal Move-out stacking and pre-stack Kirchhoff time migration confirm that the tomographic MVA and corresponding pre-stack Kirchhoff depth migration provide the best image quality and highest-resolution subsurface images from the South China Sea data.

Reverse time migration of multiples: Eliminating migration artifacts in angle domain common image gathers

Free-surface-related multiples are usually regarded as noise in conventional seismic processing. However, they can provide extra illumination of the subsurface and thus have been used in migration procedures, e.g., in one- and two-way wave-equation migrations. The disadvantage of the migration of multiples is the migration artifacts generated by the crosscorrelation of different seismic events, e.g., primaries and second-order free-surface-related multiples, so the effective elimination of migration artifacts is crucial for migration of multiples. The angle domain common image gather (ADCIG) is a suitable domain for testing the correctness of a migration velocity model. When the migration velocity model is correct, all the events in ADCIGs should be flat, and this provides a criterion for removing the migration artifacts. Our approach first obtains ADCIGs during reverse time migration and then applies a high-resolution parabolic Radon transform to all ADCIGs. By doing so, most migration artifacts will reside in the nonzero curvature regions in the Radon domain, and then a muting procedure can be implemented to remove the data components outside the vicinity of zero curvature. After the application of an adjoint Radon transform, the filtered ADCIGs are obtained and the final denoised migration result is generated by stacking all filtered ADCIGs. A three-flat-layer velocity model and the Marmousi synthetic data set are used for numerical experiments. The numerical results revealed that the proposed approach can eliminate most artifacts generated by migration of multiples when the migration velocity model is correct.

Attenuation compensation for least-squares reverse time migration using the viscoacoustic-wave equation

Strong subsurface attenuation leads to distortion of amplitudes and phases of seismic waves propagating inside the earth. Conventional acoustic reverse time migration (RTM) and least-squares reverse time migration (LSRTM) do not account for this distortion, which can lead to defocusing of migration images in highly attenuative geologic environments. To correct for this distortion, we used a linearized inversion method, denoted as [Formula: see text]-LSRTM. During the least-squares iterations, we used a linearized viscoacoustic modeling operator for forward modeling. The adjoint equations were derived using the adjoint-state method for back propagating the residual wavefields. The merit of this approach compared with conventional RTM and LSRTM was that [Formula: see text]-LSRTM compensated for the amplitude loss due to attenuation and could produce images with better balanced amplitudes and more resolution below highly attenuative layers. Numerical tests on synthetic and field data illustrated the advantages of [Formula: see text]-LSRTM over RTM and LSRTM when the recorded data had strong attenuation effects. Similar to standard LSRTM, the sensitivity tests for background velocity and [Formula: see text] errors revealed that the liability of this method is the requirement for smooth and accurate migration velocity and attenuation models.

Prestack time imaging algorithm with simultaneous velocity estimation in hard rock environments

Reflection seismic imaging faces several difficulties in hard rock environments. One of them is the estimation of the propagation velocity of seismic waves. Therefore, imaging algorithms that do not require prior construction of a velocity model seem promising for such environments. In this paper we illustrate an application of prestack time migration, which does not require an input velocity model, to hard rock conditions, and we demonstrate its effectiveness on synthetic data. This approach is based on an estimation of local event slopes (horizontal slownesses) in common-shot and common-receiver gathers and a subsequent calculation of the migration attributes (migration velocity, vertical traveltime and horizontal coordinates of the migrated reflection point). These attributes allow us to derive all the information needed to construct a time-migrated image. We also use the obtained migration velocities as an input velocity model for Kirchhoff prestack time migration (PSTM) and compare the results of the proposed approach with a conventional Kirchhoff migration using as an input the picked NMO velocity model. This application to a hard rock synthetic model illustrates the potential of the presented migration algorithm for imaging in hard rock seismic exploration. We believe that this approach can be used in hard rock seismic processing workflows as an automatic tool to obtain an input velocity model for the Kirchhoff PSTM.

Making the most out of least-squares migration

Standard migration images can suffer from (1) migration artifacts caused by an undersampled acquisition geometry, (2) poor resolution resulting from a limited recording aperture, (3) ringing artifacts caused by ripples in the source wavelet, and (4) weak amplitudes resulting from geometric spreading, attenuation, and defocusing. These problems can be remedied in part by least-squares migration (LSM), also known as linearized seismic inversion or migration deconvolution (MD), which aims to linearly invert seismic data for the reflectivity distribution. Given a sufficiently accurate migration velocity model, LSM can mitigate many of the above problems and can produce more resolved migration images, sometimes with more than twice the spatial resolution of standard migration. However, LSM faces two challenges: The computational cost can be an order of magnitude higher than that of standard migration, and the resulting image quality can fail to improve for migration velocity errors of about 5% or more. It is possible to obtain the most from least-squares migration by reducing the cost and velocity sensitivity of LSM.

Least-squares reverse-time migration with a wavefield-separation imaging condition and updated source wavefields

Directly imaging steeply dipping fault zones is difficult for conventional migration, including reverse-time migration (RTM). We developed a new least-squares RTM (LSRTM) method to directly image steeply dipping fault zones. The method uses a wavefield-separation imaging condition and updated source wavefields during each iteration. Our new imaging method produces horizontal-looking images that show mostly steeply dipping fault zones. Conventional least-squares RTM does not update source wavefields and cannot directly image vertical fault zones. We numerically determined that it is crucial to update source wavefields to image steeply dipping fault zones. Using synthetic seismic data, we proved that our new LSRTM method can directly image steeply dipping fault zones with dipping angles up to 90°. Compared with conventional LSRTM, our LSRTM method was less sensitive to the smoothness and the velocity error of the initial migration velocity model.

Noise removal by migration of time-shift images

When using seismic data to image complex structures, the reverse time migration (RTM) algorithm generally provides the best results when the velocity model is accurate. With an inexact model, moveouts appear in common image gathers (CIGs), which are either in the surface offset domain or in subsurface angle domain; thus, the stacked image is not well focused. In extended image gathers, the strongest energy of a seismic event may occur at non-zero-lag in time-shift or offset-shift gathers. Based on the operation of RTM images produced by the time-shift imaging condition, the non-zero-lag time-shift images exhibit a spatial shift; we propose an approach to correct them by a second pass of migration similar to zero-offset depth migration; the proposed approach is based on the local poststack depth migration assumption. After the proposed second-pass migration, the time-shift CIGs appear to be flat and can be stacked. The stack enhances the energy of seismic events that are defocused at zero time lag due to the inaccuracy of the model, even though the new focused events stay at the previous positions, which might deviate from the true positions of seismic reflection. With the stack, our proposed approach is also able to attenuate the long-wavelength RTM artifacts. In the case of tilted transverse isotropic migration, we propose a scheme to defocus the coherent noise, such as migration artifacts from residual multiples, by applying the original migration velocity model along the symmetry axis but with different anisotropic parameters in the second pass of migration. We demonstrate that our approach is effective to attenuate the coherent noise at subsalt area with two synthetic data sets and one real data set from the Gulf of Mexico.