Depth-consistent reflection tomography using PP and PS seismic data

Geophysics ◽  
2005 ◽  
Vol 70 (5) ◽  
pp. U51-U65 ◽  
Author(s):  
Stig-Kyrre Foss ◽  
Bjørn Ursin ◽  
Maarten V. de Hoop
Keyword(s):  
Seismic Data ◽  
Optimization Procedure ◽  
Transversely Isotropic ◽  
Data Depth ◽  
Image Point ◽  
Ocean Bottom ◽  
Data Set ◽  
Scattering Angle ◽  
Velocity Models ◽  
Reflection Tomography

We present a method of reflection tomography for anisotropic elastic parameters from PP and PS reflection seismic data. The method is based upon the differential semblance misfit functional in scattering angle and azimuth (DSA) acting on common-image-point gathers (CIGs) to find fitting velocity models. The CIGs are amplitude corrected using a generalized Radon transform applied to the data. Depth consistency between the PP and PS images is enforced by penalizing any mis-tie between imaged key reflectors. The mis-tie is evaluated by means of map migration-demigration applied to the geometric information (times and slopes) contained in the data. In our implementation, we simplify the codepthing approach to zero-scattering-angle data only. The resulting measure is incorporated as a regularization in the DSA misfit functional. We then resort to an optimization procedure, restricting ourselves to transversely isotropic (TI) velocity models. In principle, depending on the available surface-offset range and orientation of reflectors in the subsurface, by combining the DSA with codepthing, the anisotropic parameters for TI models can be determined, provided the orientation of the symmetry axis is known. A proposed strategy is applied to an ocean-bottom-seismic field data set from the North Sea.

Scattering‐angle migration of ocean‐bottom seismic data in weakly anisotropic media

Geophysics ◽  
2003 ◽  
Vol 68 (2) ◽  
pp. 641-655 ◽  
Author(s):  
Anders Sollid ◽  
Bjørn Ursin
Keyword(s):  
Seismic Data ◽  
Large Angle ◽  
Computational Cost ◽  
Synthetic Data ◽  
Transversely Isotropic ◽  
Real Data ◽  
Image Point ◽  
Ocean Bottom ◽  
Weak Anisotropy ◽  
Scattering Angle

Scattering‐angle migration maps seismic prestack data directly into angle‐dependent reflectivity at the image point. The method automatically accounts for triplicated rayfields and is easily extended to handle anisotropy. We specify scattering‐angle migration integrals for PP and PS ocean‐bottom seismic (OBS) data in 3D and 2.5D elastic media exhibiting weak contrasts and weak anisotropy. The derivation is based on the anisotropic elastic Born‐Kirchhoff‐Helmholtz surface scattering integral. The true‐amplitude weights are chosen such that the amplitude versus angle (AVA) response of the angle gather is equal to the Born scattering coefficient or, alternatively, the linearized reflection coefficient. We implement scattering‐angle migration by shooting a fan of rays from the subsurface point to the acquisition surface, followed by integrating the phase‐ and amplitude‐corrected seismic data over the migration dip at the image point while keeping the scattering‐angle fixed. A dense summation over migration dip only adds a minor additional cost and enhances the coherent signal in the angle gathers. The 2.5D scattering‐angle migration is demonstrated on synthetic data and on real PP and PS data from the North Sea. In the real data example we use a transversely isotropic (TI) background model to obtain depth‐consistent PP and PS images. The aim of the succeeding AVA analysis is to predict the fluid type in the reservoir sand. Specifically, the PS stack maps the contrasts in lithology while being insensitive to the fluid fill. The PP large‐angle stack maps the oil‐filled sand but shows no response in the brine‐filled zones. A comparison to common‐offset Kirchhoff migration demonstrates that, for the same computational cost, scattering‐angle migration provides common image gathers with less noise and fewer artifacts.

Common-focus point-based target-oriented imaging approach for continuous seismic reservoir monitoring

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. M41-M48 ◽  
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Time Lapse ◽  
Velocity Estimation ◽  
Estimation Methods ◽  
Data Sets ◽  
Data Set ◽  
Velocity Models ◽  
Reservoir Monitoring ◽  
Focus Point

The ideal approach for continuous reservoir monitoring allows generation of fast and accurate images to cope with the massive data sets acquired for such a task. Conventionally, rigorous depth-oriented velocity-estimation methods are performed to produce sufficiently accurate velocity models. Unlike the traditional way, the target-oriented imaging technology based on the common-focus point (CFP) theory can be an alternative for continuous reservoir monitoring. The solution is based on a robust data-driven iterative operator updating strategy without deriving a detailed velocity model. The same focusing operator is applied on successive 3D seismic data sets for the first time to generate efficient and accurate 4D target-oriented seismic stacked images from time-lapse field seismic data sets acquired in a [Formula: see text] injection project in Saudi Arabia. Using the focusing operator, target-oriented prestack angle domain common-image gathers (ADCIGs) could be derived to perform amplitude-versus-angle analysis. To preserve the amplitude information in the ADCIGs, an amplitude-balancing factor is applied by embedding a synthetic data set using the real acquisition geometry to remove the geometry imprint artifact. Applying the CFP-based target-oriented imaging to time-lapse data sets revealed changes at the reservoir level in the poststack and prestack time-lapse signals, which is consistent with the [Formula: see text] injection history and rock physics.

Deep learning-driven velocity model building workflow

2019 ◽  
Vol 38 (11) ◽  
pp. 872a1-872a9 ◽  
Author(s):  
Mauricio Araya-Polo ◽  
Stuart Farris ◽  
Manuel Florez
Keyword(s):  
Deep Learning ◽  
Seismic Data ◽  
Model Building ◽  
Ground Truth ◽  
Velocity Model ◽  
Training Data ◽  
Quality Data ◽  
Generative Adversarial Network ◽  
Data Set ◽  
Velocity Models

Exploration seismic data are heavily manipulated before human interpreters are able to extract meaningful information regarding subsurface structures. This manipulation adds modeling and human biases and is limited by methodological shortcomings. Alternatively, using seismic data directly is becoming possible thanks to deep learning (DL) techniques. A DL-based workflow is introduced that uses analog velocity models and realistic raw seismic waveforms as input and produces subsurface velocity models as output. When insufficient data are used for training, DL algorithms tend to overfit or fail. Gathering large amounts of labeled and standardized seismic data sets is not straightforward. This shortage of quality data is addressed by building a generative adversarial network (GAN) to augment the original training data set, which is then used by DL-driven seismic tomography as input. The DL tomographic operator predicts velocity models with high statistical and structural accuracy after being trained with GAN-generated velocity models. Beyond the field of exploration geophysics, the use of machine learning in earth science is challenged by the lack of labeled data or properly interpreted ground truth, since we seldom know what truly exists beneath the earth's surface. The unsupervised approach (using GANs to generate labeled data)illustrates a way to mitigate this problem and opens geology, geophysics, and planetary sciences to more DL applications.

scholarly journals Converted-wave azimuth moveout

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. S99-S110
Author(s):  
Daniel A. Rosales ◽  
Biondo Biondi
Keyword(s):  
Seismic Data ◽  
Extreme Case ◽  
Ocean Bottom ◽  
Sampled Data ◽  
Computationally Efficient ◽  
Converted Wave ◽  
Data Set ◽  
Prestack Migration ◽  
Conversion Point ◽  
The Common

A new partial-prestack migration operator to manipulate multicomponent data, called converted-wave azimuth moveout (PS-AMO), transforms converted-wave prestack data with an arbitrary offset and azimuth to equivalent data with a new offset and azimuth position. This operator is a sequential application of converted-wave dip moveout and its inverse. As expected, PS-AMO reduces to the known expression of AMO for the extreme case when the P velocity is the same as the S velocity. Moreover, PS-AMO preserves the resolution of dipping events and internally applies a correction for the lateral shift between the common-midpoint and the common-reflection/conversion point. An implementation of PS-AMO in the log-stretch frequency-wavenumber domain is computationally efficient. The main applications for the PS-AMO operator are geometry regularization, data-reduction through partial stacking, and interpolation of unevenly sampled data. We test our PS-AMO operator by solving 3D acquisition geometry-regularization problems for multicomponent, ocean-bottom seismic data. The geometry-regularization problem is defined as a regularized least-squares-objective function. To preserve the resolution of dipping events, the regularization term uses the PS-AMO operator. Application of this methodology on a portion of the Alba 3D, multicomponent, ocean-bottom seismic data set shows that we can satisfactorily obtain an interpolated data set that honors the physics of converted waves.

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.

Diffractivity — Another attribute for the interpretation of seismic data in hard rock environment, a case study

2016 ◽  
Vol 4 (4) ◽  
pp. B23-B32 ◽  
Author(s):  
Mohammad Javad Khoshnavaz ◽  
Andrej Bóna ◽  
Muhammad Shahadat Hossain ◽  
Milovan Urosevic ◽  
Kit Chambers
Keyword(s):  
Seismic Data ◽  
Hard Rock ◽  
Shear Zones ◽  
Primary Objective ◽  
Seismic Exploration ◽  
Image Point ◽  
Small Scale ◽  
Imaging Method ◽  
Data Set ◽  
Diffraction Imaging

The primary objective of seismic exploration in a hard rock environment is the detection of heterogeneities such as fracture zones, small-scale geobodies, intrusions, and steeply dipping structures that are often associated with mineral deposits. Prospecting in such environments using seismic-reflection methods is more challenging than in sedimentary settings due to lack of continuous reflector beds and predominance of steeply dipping hard rock formations. The heterogeneities and “fractal” aspect of hard rock geologic environment produce considerable scattering of the seismic energy in the form of diffracted waves. These scatterers can be traced back to irregular and often “sharp-shaped” mineral bodies, magmatic intrusions, faults, and complex and heterogeneous shear zones. Due to the natural lack of reflectors and abundant number of diffractors, there are only a few case studies of diffraction imaging in hard rock environments. There are almost no theoretical models or field examples of diffraction imaging in prestack domain. We have filled this gap by applying a 3D prestack diffraction imaging method to image point diffractors. We calculated the diffractivity by computing the semblance of seismic data along diffraction traveltime curves in the prestack domain. The performance of the method is evaluated on a synthetic case and a field seismic data set collected over the Kevitsa mineral deposit in northern Finland. The high-resolution results obtained by the application of prestack diffraction imaging suggest that diffractivity is a robust attribute that can be used in addition to other seismic attributes for the interpretation of seismic data in hard rock environment.

Integrated 2D 4-C OBC velocity analysis of near-seafloor sediments, Green Canyon, Gulf of Mexico

Geophysics ◽  
2008 ◽  
Vol 73 (6) ◽  
pp. B109-B115 ◽  
Author(s):  
Michael V. DeAngelo ◽  
Paul E. Murray ◽  
Bob A. Hardage ◽  
Randy L. Remington
Keyword(s):  
Seismic Data ◽  
Velocity Analysis ◽  
Ocean Bottom ◽  
Reflection Mode ◽  
Velocity Models ◽  
Velocity Information ◽  
Interval Velocities ◽  
Seafloor Sediments ◽  
Vital Element

Using 2D four-component ocean-bottom-cable (2D 4-C OBC) seismic data processed in common-receiver gathers, we developed robust [Formula: see text] and [Formula: see text] interval velocities for the near-seafloor strata. A vital element of the study was to implement iterative interpretation techniques to correlate near-seafloor P-P and P-SV images. Initially, depth-equivalent P-P and P-SV layers were interpreted by visually matching similar events in both seismic modes. Complementary 1D ray-tracing analyses then determined interval values of subsea-floor [Formula: see text] and [Formula: see text] velocities across a series of earth layers extending from the seafloor to below the base of the hydrate stability zone (BHSZ) to further constrain these interpretations. Iterating interpretation of depth-equivalent horizons with velocity analyses allowed us to converge on physically reasonable velocity models. Simultaneous [Formula: see text] and [Formula: see text] velocity analysis provided additional model constraints in areas where data quality of one reflection mode (usually [Formula: see text] in the near-seafloor environments) would not provide adequate information to derive reliable velocity information.

Building tilted transversely isotropic depth models using localized anisotropic tomography with well information

Geophysics ◽  
2010 ◽  
Vol 75 (4) ◽  
pp. D27-D36 ◽  
Author(s):  
Andrey Bakulin ◽  
Marta Woodward ◽  
Dave Nichols ◽  
Konstantin Osypov ◽  
Olga Zdraveva
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
Symmetry Axis ◽  
Transverse Isotropy ◽  
Synthetic Data ◽  
Rock Physics ◽  
Transversely Isotropic ◽  
Data Set ◽  
Anisotropic Models ◽  
Well Data

Tilted transverse isotropy (TTI) is increasingly recognized as a more geologically plausible description of anisotropy in sedimentary formations than vertical transverse isotropy (VTI). Although model-building approaches for VTI media are well understood, similar approaches for TTI media are in their infancy, even when the symmetry-axis direction is assumed known. We describe a tomographic approach that builds localized anisotropic models by jointly inverting surface-seismic and well data. We present a synthetic data example of anisotropic tomography applied to a layered TTI model with a symmetry-axis tilt of 45 degrees. We demonstrate three scenarios for constraining the solution. In the first scenario, velocity along the symmetry axis is known and tomography inverts for Thomsen’s [Formula: see text] and [Formula: see text] parame-ters. In the second scenario, tomography inverts for [Formula: see text], [Formula: see text], and velocity, using surface-seismic data and vertical check-shot traveltimes. In contrast to the VTI case, both these inversions are nonunique. To combat nonuniqueness, in the third scenario, we supplement check-shot and seismic data with the [Formula: see text] profile from an offset well. This allows recovery of the correct profiles for velocity along the symmetry axis and [Formula: see text]. We conclude that TTI is more ambiguous than VTI for model building. Additional well data or rock-physics assumptions may be required to constrain the tomography and arrive at geologically plausible TTI models. Furthermore, we demonstrate that VTI models with atypical Thomsen parameters can also fit the same joint seismic and check-shot data set. In this case, although imaging with VTI models can focus the TTI data and match vertical event depths, it leads to substantial lateral mispositioning of the reflections.

Generation and processing of pseudo‐shear‐wave data: Theory and case study

Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 1807-1816 ◽  
Author(s):  
Vladimir Grechka ◽  
Pawan Dewangan
Keyword(s):  
Shear Wave ◽  
Pure Shear ◽  
Transversely Isotropic ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Ocean Bottom ◽  
S Wave ◽  
Velocity Models ◽  
Conversion Point

Processing of converted (PS) waves currently adopted by the exploration industry is essentially based on resorting the PS data into common‐conversion‐point gathers and using them for velocity analysis. Here, we explore an alternative procedure. Our key idea is to generate the so‐called pseudo‐shear (ΨS) seismograms from the recorded PP and PS traces and run conventional velocity analysis on the reconstructed ΨS data. This results in an effective S‐wave velocity model because our method creates data that possess kinematics of pure shear‐wave primaries. We never deal with such complexities of converted waves as moveout asymmetry, reflection point dispersal, and polarity reversal; therefore, these generally troublesome features become irrelevant. We describe the details of our methodology and examine its behavior both analytically and numerically. We apply the developed processing flow to a four‐component ocean‐bottom cable line acquired in the Gulf of Mexico. Since the obtained stacking velocities of P‐ and ΨS‐waves indicate the presence of effective anisotropy, we proceed with estimating a family of kinematically equivalent vertical transversely isotropic (VTI) velocity models of the subsurface.

scholarly journals Joint migration velocity analysis of PP- and PS-waves for VTI media

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. WC123-WC135 ◽  
Author(s):  
Pengfei Cai ◽  
Ilya Tsvankin
Keyword(s):  
Grid Point ◽  
Transversely Isotropic ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Analysis ◽  
Ocean Bottom ◽  
Velocity Models ◽  
The North ◽  
Migration Velocity Analysis ◽  
Vti Media

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 [Formula: see text] 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 [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] 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.

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