A 3D subsalt tomography based on wave-equation migration-perturbation scans

Geophysics ◽  
2006 ◽  
Vol 71 (2) ◽  
pp. E1-E6 ◽  
Author(s):  
Bin Wang ◽  
Volker Dirks ◽  
Patrice Guillaume ◽  
François Audebert ◽  
Duryodhan Epili
Keyword(s):  
Wave Equation ◽  
Ray Tracing ◽  
Velocity Model ◽  
Image Point ◽  
Seismic Events ◽  
Observation Data ◽  
Velocity Analysis ◽  
Data Set ◽  
Tomographic Inversion ◽  
Model Independent

We have developed a simple but practical methodology for updating subsalt velocities using wave-equation, migration-perturbation scans. For the sake of economy and scalability (with respect to full source-receiver migration) and accuracy (with respect to common-azimuth migration), we use shot-profile, wave-equation migration. As input for subsalt-velocity analysis, we provide wave-equation migration scans with velocity scanning limited to the subsalt sediments. Throughout the migration-scan sections, we look for the best focusing or structural positioning of characteristic seismic events. The picking on the migration stacks selects the value of the best perturbation attribute (alpha-scaling factor) along with the corresponding position and local dip for the chosen seismic events. The associated, locally coherent events are then demigrated to the base of the salt horizon. Our key observation is that this process is theoretically equivalent to performing a datuming to a base of salt followed by subsalt migration of the redatumed data perturbed-velocity profiles. Thanks to this implicit redatuming of shot profiles, no ray tracing through the salt body is required. Thus, the events picked on the subsalt-velocity scans only need to be demigrated to the base of salt. For the event demigration we use 3D specular-ray tracing up to the base of the salt horizon within a predefined range of reflection angles. Event demigration produces model-independent data — time and time slope — that are then kinematically migrated using the current tomographic-inversion working model. To find a final-velocity model that will flatten best the remigrated events on common image point (CIP) angle gathers, we use the same set of demigrated observation data as the input data set for several nonlinear iterations of 3D tomographic inversion.

Case Study: Improving the quality of the seismic reflection image for a Fujian mineral exploration data set with offset-domain common-image gathers

Geophysics ◽  
2021 ◽  
pp. 1-45
Author(s):  
Guofeng Liu ◽  
Xiaohong Meng ◽  
Johanes Gedo Sea
Keyword(s):  
Wave Equation ◽  
Image Quality ◽  
Seismic Data ◽  
Seismic Reflection ◽  
Mineral Exploration ◽  
Velocity Model ◽  
Image Point ◽  
Single Shot ◽  
Data Set ◽  
Depth Migration

Seismic reflection is a proven and effective method commonly used during the exploration of deep mineral deposits in Fujian, China. In seismic data processing, rugged depth migration based on wave-equation migration can play a key role in handling surface fluctuations and complex underground structures. Because wave-equation migration in the shot domain cannot output offset-domain common-image gathers in a straightforward way, the use of traditional tools for updating the velocity model and improving image quality can be quite challenging. To overcome this problem, we employed the attribute migration method. This worked by sorting the migrated stack results for every single-shot gather into the offset gathers. The value of the offset that corresponded to each image point was obtained from the ratio of the original migration results to the offset-modulated shot-data migration results. A Gaussian function was proposed to map every image point to a certain range of offsets. This helped improve the signal-to-noise ratio, which was especially important in handing low quality seismic data obtained during mineral exploration. Residual velocity analysis was applied to these gathers to update the velocity model and improve image quality. The offset-domain common-image gathers were also used directly for real mineral exploration seismic data with rugged depth migration. After several iterations of migration and updating the velocity, the proposed procedure achieved an image quality better than the one obtained with the initial velocity model. The results can help with the interpretation of thrust faults and deep deposit exploration.

Tomographic modeling of a cross‐borehole data set

Geophysics ◽  
1989 ◽  
Vol 54 (10) ◽  
pp. 1249-1257 ◽  
Author(s):  
Larry R. Lines ◽  
Edward D. LaFehr
Keyword(s):  
Wave Equation ◽  
Ray Tracing ◽  
Velocity Model ◽  
Velocity Estimation ◽  
P Wave ◽  
Seismic Survey ◽  
Equation Modeling ◽  
Data Set ◽  
True Solution ◽  
Velocity Models

In this paper we describe a methodology for estimating P‐wave velocities from a cross‐borehole seismic survey that uses straight‐ray tomography, ray tracing, and finite‐difference wave‐equation modeling to produce velocity models that fit the first‐break traveltimes. After a starting model is established by straight‐ray tomography, the velocity model is checked by ray tracing and wave‐equation modeling. Since the models for each procedure show consistent results and the modeled traveltimes closely match those traveltimes from the actual data, we felt our interpretation was confirmed. However, the fitting of cross‐well first break traveltimes is only a necessary validity check and is not sufficient to guarantee that the true solution has been found. Two wells were drilled through the areas that were anomalous on the derived tomogram and check‐shot velocity surveys were run. Due primarily to a lateral ambiguity in velocity estimation caused by too few near‐vertical raypaths, the check‐shot surveys did not agree with the tomogram velocities. However, subsequently the check‐shot traveltimes were used to place bounds on velocity in a constrained least‐squares procedure; the combined modeling of uphole and cross‐well rays produced an optimum velocity model which satisfies all available data.

Subsalt velocity estimation by target-oriented wave-equation migration velocity analysis: A 3D field-data example

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. U19-U29 ◽  
Author(s):  
Yaxun Tang ◽  
Biondo Biondi
Keyword(s):  
Wave Equation ◽  
Field Data ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Estimation ◽  
Velocity Analysis ◽  
Data Set ◽  
Generalized Born ◽  
Migration Velocity Analysis ◽  
Recorded Data

We apply target-oriented wave-equation migration velocity analysis to a 3D field data set acquired from the Gulf of Mexico. Instead of using the original surface-recorded data set, we use a new data set synthesized specifically for velocity analysis to update subsalt velocities. The new data set is generated based on an initial unfocused target image and by a novel application of 3D generalized Born wavefield modeling, which correctly preserves velocity kinematics by modeling zero and nonzero subsurface-offset-domain images. The target-oriented inversion strategy drastically reduces the data size and the computation domain for 3D wave-equation migration velocity analysis, greatly improving its efficiency and flexibility. We apply differential semblance optimization (DSO) using the synthesized new data set to optimize subsalt velocities. The updated velocity model significantly improves the continuity of subsalt reflectors and yields flattened angle-domain common-image gathers.

Joint inversion of the reflectivity and the velocity model

Geophysics ◽  
2021 ◽  
pp. 1-68
Author(s):  
Alejandro Cabrales-Vargas ◽  
Rahul Sarkar ◽  
Biondo L. Biondi ◽  
Robert G. Clapp
Keyword(s):  
Wave Equation ◽  
Field Data ◽  
Joint Inversion ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Migration Velocity ◽  
Background Model ◽  
Seismic Events ◽  
Velocity Analysis ◽  
Migration Velocity Analysis

During linearized waveform inversion, the presence of small inaccuracies in the background subsurface model can lead to unfocused seismic events in the final image. The effect on the amplitude can mislead the interpretation. We present a joint inversion scheme in the model domain of the reflectivity and the background velocity model. The idea is to unify the inversion of the background and the reflectivity model into a single framework instead of treating them as decoupled problems. We show that with this method, we can obtain a better estimate of the reflectivity than that obtained with conventional linearized waveform inversion. Conversely, the background model is improved by the joint inversion with the reflectivity in comparison with wave-equation migration velocity analysis. We perform tests on 2D synthetics and 3D field data that demonstrate both benefits.

Migration moveout analysis and depth focusing

Geophysics ◽  
1993 ◽  
Vol 58 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Claude F. Lafond ◽  
Alan R. Levander
Keyword(s):  
Heterogeneous Media ◽  
A Priori ◽  
Complex Structure ◽  
Tomographic Reconstruction ◽  
Synthetic Data ◽  
Real Data ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Data Set ◽  
Velocity Models

Prestack depth migration still suffers from the problems associated with building appropriate velocity models. The two main after‐migration, before‐stack velocity analysis techniques currently used, depth focusing and residual moveout correction, have found good use in many applications but have also shown their limitations in the case of very complex structures. To address this issue, we have extended the residual moveout analysis technique to the general case of heterogeneous velocity fields and steep dips, while keeping the algorithm robust enough to be of practical use on real data. Our method is not based on analytic expressions for the moveouts and requires no a priori knowledge of the model, but instead uses geometrical ray tracing in heterogeneous media, layer‐stripping migration, and local wavefront analysis to compute residual velocity corrections. These corrections are back projected into the velocity model along raypaths in a way that is similar to tomographic reconstruction. While this approach is more general than existing migration velocity analysis implementations, it is also much more computer intensive and is best used locally around a particularly complex structure. We demonstrate the technique using synthetic data from a model with strong velocity gradients and then apply it to a marine data set to improve the positioning of a major fault.

Inversion of seismic refraction and reflection data for building long-wavelength velocity models

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. R81-R93 ◽  
Author(s):  
Haiyang Wang ◽  
Satish C. Singh ◽  
Francois Audebert ◽  
Henri Calandra
Keyword(s):  
Wave Equation ◽  
Short Wavelength ◽  
Velocity Model ◽  
Density Model ◽  
Data Set ◽  
Reflected Waves ◽  
Long Wavelength ◽  
Velocity Models ◽  
Computation Efficiency ◽  
Refracted Waves

Long-wavelength velocity model building is a nonlinear process. It has traditionally been achieved without appealing to wave-equation-based approaches for combined refracted and reflected waves. We developed a cascaded wave-equation tomography method in the data domain, taking advantage of the information contained in the reflected and refracted waves. The objective function was the traveltime residual that maximized the crosscorrelation function between real and synthetic data. To alleviate the nonlinearity of the inversion problem, refracted waves were initially used to provide vertical constraints on the velocity model, and reflected waves were then included to provide lateral constraints. The use of reflected waves required scale separation. We separated the long- and short-wavelength subsurface structures into velocity and density models, respectively. The velocity model update was restricted to long wavelengths during the wave-equation tomography, whereas the density model was used to absorb all the short-wavelength impedance contrasts. To improve the computation efficiency, the density model was converted into the zero-offset traveltime domain, where it was invariant to changes of the long-wavelength velocity model. After the wave-equation tomography has derived an optimized long-wavelength velocity model, full-waveform inversion was used to invert all the data to retrieve the short-wavelength velocity structures. We developed our method in two synthetic tests and then applied it to a marine field data set. We evaluated the results of the use of refracted and reflected waves, which was critical for accurately building the long-wavelength velocity model. We showed that our wave-equation tomography strategy was robust for the real data application.

scholarly journals Ray-tracing traveltime tomography versus wave-equation traveltime inversion for near-surface seismic land data

2017 ◽  
Vol 5 (3) ◽  
pp. SO11-SO19
Author(s):  
Lei Fu ◽  
Sherif M. Hanafy
Keyword(s):  
Wave Equation ◽  
Ray Tracing ◽  
Water Table ◽  
Seismic Data ◽  
Velocity Model ◽  
Water Table Depth ◽  
Seismic Survey ◽  
Near Surface ◽  
Traveltime Tomography ◽  
Initial Starting

Full-waveform inversion of land seismic data tends to get stuck in a local minimum associated with the waveform misfit function. This problem can be partly mitigated by using an initial velocity model that is close to the true velocity model. This initial starting model can be obtained by inverting traveltimes with ray-tracing traveltime tomography (RT) or wave-equation traveltime (WT) inversion. We have found that WT can provide a more accurate tomogram than RT by inverting the first-arrival traveltimes, and empirical tests suggest that RT is more sensitive to the additive noise in the input data than WT. We present two examples of applying WT and RT to land seismic data acquired in western Saudi Arabia. One of the seismic experiments investigated the water-table depth, and the other one attempted to detect the location of a buried fault. The seismic land data were inverted by WT and RT to generate the P-velocity tomograms, from which we can clearly identify the water table depth along the seismic survey line in the first example and the fault location in the second example.

Velocity analysis without picking

Geophysics ◽  
1989 ◽  
Vol 54 (2) ◽  
pp. 191-199 ◽  
Author(s):  
John L. Toldi
Keyword(s):  
Field Data ◽  
Velocity Model ◽  
Point Of View ◽  
Velocity Analysis ◽  
Lateral Variation ◽  
Data Set ◽  
Initial Interval ◽  
Analysis Algorithm ◽  
Interval Velocity ◽  
Interval Velocities

Conventionally, interval velocities are derived from picked stacking velocities. The velocity‐analysis algorithm proposed in this paper is also based on stacking velocities; however, it eliminates the conventional picking stage by always considering stacking velocities from the point of view of an interval‐velocity model. This view leads to a model‐based, automatic velocity‐analysis algorithm. The algorithm seeks to find an interval‐velocity model such that the stacking velocities calculated from that model give the most powerful stack. An additional penalty is incurred for models that differ in smoothness from an initial interval‐velocity model. The search for the best model is conducted by means of a conjugate‐gradient method. The connection between the interval‐velocity model and the stacking velocities plays an important role in the algorithm proposed in this paper. In the simplest case, stacking velocity is assumed to be equal to rms velocity. For the more general case, a linear theory is developed, connecting interval velocity and stacking velocity through the intermediary of traveltime. When applied to a field data set, the method produces an interval‐velocity model that explains the lateral variation in both stacking velocity and traveltime.

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