Elastic least-squares reverse time migration of steeply dipping structures using prismatic reflections

Geophysics ◽  
2022 ◽  
pp. 1-130
Author(s):  
Zheng Wu ◽  
Yuzhu Liu ◽  
Jizhong Yang
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Oil And Gas ◽  
Normal Equation ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Time Migration ◽  
Multicomponent Seismic ◽  
Imaging Conditions

The migration of prismatic reflections can be used to delineate steeply dipping structures, which is crucial for oil and gas exploration and production. Elastic least-squares reverse time migration (ELSRTM), which considers the effects of elastic wave propagation, can be used to obtain reasonable subsurface reflectivity estimations and interpret multicomponent seismic data. In most cases, we can only obtain a smooth migration model. Thus, conventional ELSRTM, which is based on the first-order Born approximation, considers only primary reflections and cannot resolve steeply dipping structures. To address this issue, we develop an ELSRTM framework, called Pris-ELSRTM, which can jointly image primary and prismatic reflections in multicomponent seismic data. When Pris-ELSRTM is directly applied to multicomponent records, near-vertical structures can be resolved. However, the application of imaging conditions established for prismatic reflections to primary reflections destabilizes the process and leads to severe contamination of the results. Therefore, we further improve the Pris-ELSRTM framework by separating prismatic reflections from recorded multicomponent data. By removing artificial imaging conditions from the normal equation, primary and prismatic reflections can be imaged based on unique imaging conditions. The results of synthetic tests and field data applications demonstrate that the improved Pris-ELSRTM framework produces high-quality images of steeply dipping P- and S-wave velocity structures. However, it is difficult to delineate steep density structures because of the insensitivity of the density to prismatic reflections.

Elastic least-squares reverse time migration with hybrid l1/l2 misfit function

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. S271-S291 ◽  
Author(s):  
Bingluo Gu ◽  
Zhenchun Li ◽  
Peng Yang ◽  
Wencai Xu ◽  
Jianguang Han
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Adjoint Equations ◽  
P Wave ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Time Migration ◽  
Wave Image

We have developed the theory and synthetic tests of elastic least-squares reverse time migration (ELSRTM). In this method, a least-squares reverse time migration algorithm is used to image multicomponent seismic data based on the first-order elastic velocity-stress wave equation, in which the linearized elastic modeling equations are used for forward modeling and its adjoint equations are derived based on the adjoint-state method for back propagating the data residuals. Also, we have developed another ELSRTM scheme based on the wavefield separation technique, in which the P-wave image is obtained using P-wave forward and adjoint wavefields and the S-wave image is obtained using P-wave forward and S-wave adjoint wavefields. In this way, the crosstalk artifacts can be minimized to a significant extent. In general, seismic data inevitably contain noise. We apply the hybrid [Formula: see text] misfit function to the ELSRTM algorithm to improve the robustness of our ELSRTM to noise. Numerical tests on synthetic data reveal that our ELSRTM, when compared with elastic reverse time migration, can produce images with higher spatial resolution, more-balanced amplitudes, and fewer artifacts. Moreover, the hybrid [Formula: see text] misfit function makes the ELSRTM more robust than the [Formula: see text] misfit function in the presence of noise.

scholarly journals Elastic Reverse-Time Migration with Complex Topography

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7837
Author(s):  
Yu Zhong ◽  
Hanming Gu ◽  
Yangting Liu ◽  
Qinghui Mao
Keyword(s):  
Surface Topography ◽  
Seismic Data ◽  
Wave Equations ◽  
Oil And Gas ◽  
Complex Topography ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Waves ◽  
Time Migration ◽  
Multicomponent Seismic

Migration is an important step in seismic data processing for oil and gas exploration. The accuracy of migration directly affects the accuracy of subsequent oil and gas reservoir characterization. Reverse-time migration is one of the most accurate migration methods at present. Multi-wave and multicomponent seismic data contain more P- and S-wave information. Making full use of multi-wave and multicomponent seismic data can offer more information about underground structure and lithology, as well as improve the accuracy of seismic exploration. Elastic reverse-time migration (ERTM) has no dip restriction and can be applied to image multi-wave and multicomponent seismic data in complex structural areas and some special lithology structures. However, the surface topography of complex regions has an influence on wavefield and seriously degrades the quality of ERTM’s migration results. We developed a new ERTM method to migrate multi-wave and multicomponent seismic data in the region with complex surface topography. We first fill the layers between the highest and lowest undulating surface with near-surface elastic parameters in a complex topography model to obtain a new model with a horizontal surface. This allows the finite difference (FD) method based on the regular rectangular grid to be used to numerically solve elastic wave equations in the model with complex topography. The decoupled wave equations are used to generate source P- and S-waves and receiver P- and S-waves to reduce crosstalk artefacts in ERTM. A topography-related filter is further used to remove the influence of surface topography on migration results. The scalar imaging condition is also applied to generate PP and PS migration images. Some numerical examples with different complex topographies demonstrate that our proposed ERTM method can remove the influence of complex topography on ERTM’s images and effectively generate high-quality ERTM images.

2D least-squares elastic reverse time migration of multicomponent seismic data

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. S523-S538 ◽  
Author(s):  
Bingluo Gu ◽  
Jianguang Han ◽  
Zhiming Ren ◽  
Zhenchun Li
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Adjoint Operator ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
Multicomponent Seismic ◽  
Isotropic Media ◽  
Wavefield Decomposition

Elastic reverse time migration (ERTM) is a state-of-the-art imaging technique used for determining complicated subsurface structures. However, the migrated images often suffer from low spatial resolution, low signal-to-noise ratio (S/N), and unbalanced amplitudes because the theoretical hypothesis of ERTM cannot be satisfied in practice. Although elastic least-squares reverse time migration (ELSRTM) has been proposed to address the issues of ERTM, the resulting images are generally represented by parameter perturbations such as P- and S-velocity perturbations, which have the different physical meanings from the ERTM images. To produce improved ERTM images, we used a least-squares RTM method for elastic data in isotropic media by applying least-squares inversion to ERTM. In the least-squares ERTM method, the forward operator generates multicomponent seismic data from the migrated images by applying elastic wavefield decomposition, scalar wavefield extrapolation, and wavefield recomposition operators. Additionally, the adjoint operator generates PP and PS images using ERTM, at which point the wavefield decomposition operator and scalar imaging condition are applied in the imaging process. Compared to conventional ERTM, our least-squares ERTM method enables us to produce improved ERTM images with higher resolution, more balanced amplitudes, and fewer artifacts. Several synthetic and field data examples were used to validate the effectiveness of the proposed least-squares ERTM method.

Vector-wave-based elastic reverse time migration of ocean-bottom 4C seismic data

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. S333-S343 ◽  
Author(s):  
Pengfei Yu ◽  
Jianhua Geng ◽  
Jiqiang Ma
Keyword(s):  
Seismic Data ◽  
Ocean Bottom ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Vector Wave ◽  
S Waves ◽  
Time Migration ◽  
Multicomponent Seismic ◽  
Wavefield Extrapolation

The acoustic-elastic coupled equation (AECE) has several advantages when compared with conventional scalar-wave-based elastic reverse time migration (ERTM) methods used to image ocean-bottom multicomponent seismic data. In particular, vector-wave-based ERTM requires vectorial P- and S-waves on the source and receiver sides, but these cannot be directly obtained from wavefield extrapolation using AECE. Therefore, we have developed a P- and S-wave vector decomposition (VD) approach within AECE; this approach enables the deduction of a novel VD-based AECE, from which vectorial P- and S-waves can be obtained directly via wavefield extrapolation. We are also able to derive a new formulation suitable for vector-wave-based ERTM of ocean-bottom multicomponent seismic data that can generate a phase-preserved PS-image. Three synthetic examples illustrate the validity and effectiveness of our new method.

From acoustic to elastic inverse extended Born modeling: a first insight in the marine environment

Geophysics ◽  
2021 ◽  
pp. 1-73
Author(s):  
Milad Farshad ◽  
Hervé Chauris
Keyword(s):  
Least Squares ◽  
Marine Environment ◽  
Computational Cost ◽  
Physical Parameters ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Time Migration ◽  
Physical Density ◽  
Acoustic Approximation

Elastic least-squares reverse time migration is the state-of-the-art linear imaging technique to retrieve high-resolution quantitative subsurface images. A successful application requires many migration/modeling cycles. To accelerate the convergence rate, various pseudoinverse Born operators have been proposed, providing quantitative results within a single iteration, while having roughly the same computational cost as reverse time migration. However, these are based on the acoustic approximation, leading to possible inaccurate amplitude predictions as well as the ignorance of S-wave effects. To solve this problem, we extend the pseudoinverse Born operator from acoustic to elastic media to account for the elastic amplitudes of PP reflections and provide an estimate of physical density, P- and S-wave impedance models. We restrict the extension to marine environment, with the recording of pressure waves at the receiver positions. Firstly, we replace the acoustic Green's functions by their elastic version, without modifying the structure of the original pseudoinverse Born operator. We then apply a Radon transform to the results of the first step to calculate the angle-dependent response. Finally, we simultaneously invert for the physical parameters using a weighted least-squares method. Through numerical experiments, we first illustrate the consequences of acoustic approximation on elastic data, leading to inaccurate parameter inversion as well as to artificial reflector inclusion. Then we demonstrate that our method can simultaneously invert for elastic parameters in the presence of complex uncorrelated structures, inaccurate background models, and Gaussian noisy data.

Imaging conditions for elastic reverse time migration

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. S95-S111 ◽  
Author(s):  
Wei Zhang ◽  
Ying Shi
Keyword(s):  
Decomposition Method ◽  
Inner Product ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Imaging Condition ◽  
Subsurface Structures ◽  
Time Migration ◽  
Imaging Conditions ◽  
Wave Modes

Elastic reverse time migration (RTM) has the ability to retrieve accurately migrated images of complex subsurface structures by imaging the multicomponent seismic data. However, the imaging condition applied in elastic RTM significantly influences the quality of the migrated images. We evaluated three kinds of imaging conditions in elastic RTM. The first kind of imaging condition involves the crosscorrelation between the Cartesian components of the particle-velocity wavefields to yield migrated images of subsurface structures. An alternative crosscorrelation imaging condition between the separated pure wave modes obtained by a Helmholtz-like decomposition method could produce reflectivity images with explicit physical meaning and fewer crosstalk artifacts. A drawback of this approach, though, was that the polarity reversal of the separated S-wave could cause destructive interference in the converted-wave image after stacking over multiple shots. Unlike the conventional decomposition method, the elastic wavefields can also be decomposed in the vector domain using the decoupled elastic wave equation, which preserves the amplitude and phase information of the original elastic wavefields. We have developed an inner-product imaging condition to match the vector-separated P- and S-wave modes to obtain scalar reflectivity images of the subsurface. Moreover, an auxiliary P-wave stress image can supplement the elastic imaging. Using synthetic examples with a layered model, the Marmousi 2 model, and a fault model, we determined that the inner-product imaging condition has prominent advantages over the other two imaging conditions and generates images with preserved amplitude and phase attributes.

scholarly journals Imaging Complex Subsurface Structures for Geothermal Exploration at Pirouette Mountain and Eleven-Mile Canyon in Nevada

2021 ◽  
Vol 9 ◽  
Author(s):  
Yunsong Huang ◽  
Miao Zhang ◽  
Kai Gao ◽  
Andrew Sabin ◽  
Lianjie Huang
Keyword(s):  
High Resolution ◽  
Least Squares ◽  
Seismic Data ◽  
Seismic Wave Propagation ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Geothermal Exploration ◽  
Subsurface Structures ◽  
Time Migration ◽  
Ground Roll

Accurate imaging of subsurface complex structures with faults is crucial for geothermal exploration because faults are generally the primary conduit of hydrothermal flow. It is very challenging to image geothermal exploration areas because of complex geologic structures with various faults and noisy surface seismic data with strong and coherent ground-roll noise. In addition, fracture zones and most geologic formations behave as anisotropic media for seismic-wave propagation. Properly suppressing ground-roll noise and accounting for subsurface anisotropic properties are essential for high-resolution imaging of subsurface structures and faults for geothermal exploration. We develop a novel wavenumber-adaptive bandpass filter to suppress the ground-roll noise without affecting useful seismic signals. This filter adaptively exploits both characteristics of the lower frequency and the smaller velocity of the ground-roll noise than those of the signals. Consequently, this filter can effectively differentiate the ground-roll noise from the signal. We use our novel filter to attenuate the ground-roll noise in seismic data along five survey lines acquired by the U.S. Navy Geothermal Program Office at Pirouette Mountain and Eleven-Mile Canyon in Nevada, United States. We then apply our novel anisotropic least-squares reverse-time migration algorithm to the resulting data for imaging subsurface structures at the Pirouette Mountain and Eleven-Mile Canyon geothermal exploration areas. The migration method employs an efficient implicit wavefield-separation scheme to reduce image artifacts and improve the image quality. Our results demonstrate that our wavenumber-adaptive bandpass filtering method successfully suppresses the strong and coherent ground-roll noise in the land seismic data, and our anisotropic least-squares reverse-time migration produces high-resolution subsurface images of Pirouette Mountain and Eleven-Mile Canyon, facilitating accurate fault interpretation for geothermal exploration.

SP- and SS-imaging for 3D elastic reverse time migration

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. A1-A6 ◽  
Author(s):  
Xufei Gong ◽  
Qizhen Du ◽  
Qiang Zhao
Keyword(s):  
Three Dimensional ◽  
Scalar Wave ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Sh Waves ◽  
S Waves ◽  
Time Migration ◽  
Underlying Principle ◽  
Imaging Conditions

Three-dimensional elastic reverse time migration has been confronted with the problem of generating scalar images with vector S-waves. The underlying principle for solving this problem is to convert the vector S-waves into scalars. Previous methods were mainly focused on PS-imaging, but they usually cannot work properly on SP- and SS-cases. The complexity of SP- and SS-imaging arises from the fact that the incident S-wave has unpredictable relationship with the raypath plane. We have suggested that S-wave should be treated separately as SV- and SH-waves, which keep predictable relationships with the raypath plane. First, the elastic wavefield is separated into P- and S-waves using the Helmholtz decomposition. Then, we evaluate the normal direction of the raypath plane at each imaging grid. Next, we separate the vector S-wave obtained with curl operator into SH- and SV-waves, both of which are scalars. Finally, correlation imaging conditions are implemented to those scalar wave modes to produce scalar SV-P, SV-SV, and SH-SH images.

Elastic wavefield separation based on the Helmholtz decomposition

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. S173-S183 ◽  
Author(s):  
Hejun Zhu
Keyword(s):  
Vector Fields ◽  
Helmholtz Decomposition ◽  
Elastic Media ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
S Waves ◽  
Poisson Solver ◽  
Time Migration ◽  
Imaging Conditions

Divergence and curl operators used for the decomposition of P- and S-wave modes in elastic reverse time migration (RTM) change the amplitudes, units, and phases of extrapolated wavefields. I separate the P- and S-waves in elastic media based on the Helmholtz decomposition. The decomposed wavefields based on this approach have the same amplitudes, units, and phases as the extrapolated wavefields. To avoid expensive multidimensional integrals in the Helmholtz decomposition, I introduce a fast Poisson solver to efficiently solve the vector Poisson’s equation. This fast algorithm allows us to reduce computational complexity from [Formula: see text] to [Formula: see text], where [Formula: see text] is the total number of grid points. Because the decomposed P- and S-waves are vector fields, I use vector imaging conditions to construct PP-, PS-, SS-, and SP-images. Several 2D numerical examples demonstrate that this approach allows us to accurately and efficiently decompose P- and S-waves in elastic media. In addition, elastic RTM images based on the vector imaging conditions have better quality and avoid polarity reversal in comparison with images based on the divergence and curl separation or direct component-by-component crosscorrelation.

Sign in / Sign up

Export Citation Format

Share Document