Model-based radiation pattern correction for interferometric redatuming in 4D seismic

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. Q25-Q35 ◽  
Author(s):  
Yang Zhao ◽  
Weichang Li
Keyword(s):  
Image Quality ◽  
Radiation Pattern ◽  
Matched Filter ◽  
Time Lapse ◽  
Wave Mode ◽  
P Wave ◽  
Radiation Patterns ◽  
Near Surface ◽  
Model Based ◽  
Isotropic Radiation

Interferometric virtual source (VS) redatuming converts surface-triggered source records into the equivalent records as if they originated from buried receiver locations by crosscorrelating downgoing waves with the corresponding upgoing waves. The theory suggests that when the receivers are surrounded by an enclosing boundary of sources, then the VS has an isotropic radiation pattern and yields an accurate response. The resultant records should determine improvement in the seismic repeatability and image quality compared with non-VS. However, in the presence of a complex near surface, an intricate shallow structure and highly variable weathering layers can severely distort the raypath, such that it produces uneven angle coverage to the buried VS. In addition, near-surface reverberations, surface multiples, and other mode-converted waves may leak into the time-gated early arrivals and further corrupt the direct wavefields. The above-mentioned issues can result in distorted radiation patterns and contaminated responses of the VS. We address these issues explicitly by spatially filtering the potentially contaminated direct wavefields using a zero-phase matched filter, such that the filtered wavefield is consistent with a model-based ideal direct P-wavefield observed at common receiver locations. This ideal reference response is computed from a homogeneous approximation to the local near-surface overburden on top of each VS. The phases of the original direct arrivals are preserved. Components associated with the reverberations and other noises can be effectively suppressed as their spatial radiation patterns deviate from that of the ideal single P-wave mode. Toward an isotropic radiation pattern by the iterative matched filter, we reduce the unbalanced illumination arising from imperfect source coverage and near-surface complexity. Compared with previous methods, the new VS approach provides significantly improved image quality and repeatability based on a pilot field of 13 time-lapse surveys, which solved a significant repeatability problem across a 17 month survey gap.

Visualizing effects of anisotropy on seismic moments and their potency-tensor isotropic equivalent

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. C85-C97 ◽  
Author(s):  
Nepomuk Boitz ◽  
Anton Reshetnikov ◽  
Serge A. Shapiro
Keyword(s):  
Radiation Pattern ◽  
Elastic Anisotropy ◽  
Moment Tensor ◽  
Matrix Multiplication ◽  
Tensor Decomposition ◽  
P Wave ◽  
Propagation Path ◽  
Tectonic Deformation ◽  
Radiation Patterns ◽  
Rock Anisotropy

Radiation patterns of earthquakes contain important information on tectonic strain responsible for seismic events. However, elastic anisotropy may significantly impact these patterns. We systematically investigate and visualize the effect of anisotropy on the radiation patterns of microseismic events. For visualization, we use a vertical-transverse-isotropic (VTI) medium. We distinguish between two different effects: the anisotropy in the source and the anisotropy on the propagation path. Source anisotropy mathematically comes from the matrix multiplication of the anisotropic stiffness tensor with the source strain expressed by the potency tensor. We analyze this effect using the corresponding radiation pattern and the moment tensor decomposition. Propagation anisotropy mathematically comes from the deviation between the polarization and the propagation direction of a quasi P-wave in an anisotropic medium. We investigate both effects separately by either assuming the source to be anisotropic and the propagation to be isotropic or vice versa. We find that both effects have a significant impact on the radiation pattern of a pure-slip source. Finally, we develop an alternative visualization of source mechanisms by plotting beach balls proportional to their potency tensors. For this, we multiply the potency tensor with an isotropic elasticity tensor having the equivalent shear modulus [Formula: see text] and [Formula: see text]. In this way, we visualize the tectonic deformation in the source, independently of the rock anisotropy.

scholarly journals Virtual-source imaging and repeatability for complex near surface

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yang Zhao ◽  
Tao Liu ◽  
Genyang Tang ◽  
Houzhu Zhang ◽  
Madhumita Sengupta
Keyword(s):  
Radiation Pattern ◽  
Local Time ◽  
Matched Filter ◽  
Negative Impact ◽  
Data Driven ◽  
Virtual Source ◽  
Surface Source ◽  
Source Imaging ◽  
Near Surface ◽  
Time Frequency

Abstract Based on seismic interferometry, the virtual source (VS) method is able to produce virtual gathers at buried receiver locations by crosscorrelating the direct-downgoing waves with corresponding reflected-upgoing waves from surface-source gathers. Theoretically, the VS records can improve seismic quality with less negative impact from overburdened complexities. However, shallow complex structures and weathering layers at near surface not only severely distort the wavepaths, but also introduce multiples, surface waves, scattering noise, and interference among different wave modes. These additional seismic responsescontaminate both direct-downgoing and reflected-upgoing wavefields. As a result, the VS gathers experience spurious events and unbalanced illuminations associated with distorted radiation patterns. Conventional stacking operator can produce significant artifacts for sources associated with ineffective-wavepath cancellation. We review three publications and summarize a comprehensive workflow to address these issues using data-driven offset stacking, wavelet-crosscorrelation filtering, and radiation-pattern correction. A data-driven offset stacking theme, with each individual source contribution is weighted by certain quality measures, is applied for available offsets. The wavelet crosscorrelation transforms time-offset data into local time-frequency and local time-frequency-wavenumber domains. Filters are designed for the power-spectrum in each domain. The radiation-pattern correction spatially alters the contaminated direct-wavefields using a zero-phase matched filter, such that the filtered wavefield is consistent with the model-based direct P-wavefields observed at buried receiver locations. Our proposed workflow produces significant improvement as demonstrated in the 13 time-lapse field surveys that included substantial repeatability problems across a 17-month survey gap.

The effect of an initial hypocentral stress upon the radiation patterns of P and S waves

1972 ◽  
Vol 62 (5) ◽  
pp. 1173-1182 ◽  
Author(s):  
F. A. Dahlen
Keyword(s):  
Radiation Pattern ◽  
Fault Plane ◽  
Deviatoric Stress ◽  
P Wave ◽  
Stress Deviator ◽  
Radiation Patterns ◽  
Fault Plane Solutions ◽  
S Waves ◽  
Quadrupole Component ◽  
Sufficient Magnitude

Abstract The effect of an initial hypocentral deviatoric stress upon the radiation patterns of radiated P and S waves is explicitly described for the case of an infinitesimal, nonpropagating seismic dislocation. A nonzero hypocentral stress deviator produces two small changes in the familiar quadrupole radiation pattern; it gives rise to a small additional explosion-like component, and it acts to skew slightly the quadrupole component relative to the fault plane and auxiliary plane. The latter phenomenon is not of sufficient magnitude to give rise to any serious uncertainties in the interpretation of fault-plane solutions; in fact, both phenomena are so small that they will be exceedingly difficult ever to detect. The recent measurements of P-wave amplitudes on the focal sphere by Randall and Knopoff (1970) cannot be explained by these results.

scholarly journals Body‐wave radiation patterns and AVO in transversely isotropic media

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1409-1425 ◽  
Author(s):  
Ilya Tsvankin
Keyword(s):  
Reflection Coefficient ◽  
Radiation Pattern ◽  
Transversely Isotropic ◽  
P Wave ◽  
Wave Radiation ◽  
Reflection Coefficients ◽  
Radiation Patterns ◽  
Avo Analysis ◽  
Transversely Isotropic Media ◽  
Isotropic Media

The angular dependence of reflection coefficients may be significantly distorted in the presence of elastic anisotropy. However, the influence of anisotropy on amplitude variation with offset (AVO) analysis is not limited to reflection coefficients. AVO signatures (e.g., AVO gradient) in anisotropic media are also distorted by the redistribution of energy along the wavefront of the wave traveling down to the reflector and back up to the surface. Significant anisotropy above the target horizon may be rather typical of sand‐shale sequences commonly encountered in AVO analysis. Here, I examine the influence of P‐ and S‐wave radiation patterns on AVO in the most common anisotropic model—transversely isotropic media. A concise analytic solution, obtained in the weak‐anisotropy approximation, provides a convenient way to estimate the impact of the distortions of the radiation patterns on AVO results. It is shown that the shape of the P‐wave radiation pattern in the range of angles most important to AVO analysis (0–40°) is primarily dependent on the difference between Thomsen parameters ε and δ. For media with ε − δ > 0 (the most common case), the P‐wave amplitude may drop substantially over the first 25–40° from vertical. There is no simple correlation between the strength of velocity anisotropy and angular amplitude variations. For instance, for models with a fixed positive ε − δ the amplitude distortions are less pronounced for larger values of ε and δ. The distortions of the SV‐wave radiation pattern are usually much more significant than those for the P‐wave. The anisotropic directivity factor for the incident wave may be of equal or greater importance for AVO than the influence of anisotropy on the reflection coefficient. Therefore, interpretation of AVO anomalies in the presence of anisotropy requires an integrated approach that takes into account not only the reflection coefficient but also the wave propagation above the reflector.

scholarly journals Deep learning–based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms

2021 ◽  
Author(s):  
Luuk J. Oostveen ◽  
Frederick J. A. Meijer ◽  
Frank de Lange ◽  
Ewoud J. Smit ◽  
Sjoert A. Pegge ◽  
...  
Keyword(s):  
Deep Learning ◽  
White Matter ◽  
Image Quality ◽  
Iterative Reconstruction ◽  
Quality Characteristics ◽  
Model Based ◽  
Hybrid Iterative Reconstruction ◽  
Contrast Ct ◽  
Lower Noise ◽  
Reconstruction Time

Abstract Objectives To evaluate image quality and reconstruction times of a commercial deep learning reconstruction algorithm (DLR) compared to hybrid-iterative reconstruction (Hybrid-IR) and model-based iterative reconstruction (MBIR) algorithms for cerebral non-contrast CT (NCCT). Methods Cerebral NCCT acquisitions of 50 consecutive patients were reconstructed using DLR, Hybrid-IR and MBIR with a clinical CT system. Image quality, in terms of six subjective characteristics (noise, sharpness, grey-white matter differentiation, artefacts, natural appearance and overall image quality), was scored by five observers. As objective metrics of image quality, the noise magnitude and signal-difference-to-noise ratio (SDNR) of the grey and white matter were calculated. Mean values for the image quality characteristics scored by the observers were estimated using a general linear model to account for multiple readers. The estimated means for the reconstruction methods were pairwise compared. Calculated measures were compared using paired t tests. Results For all image quality characteristics, DLR images were scored significantly higher than MBIR images. Compared to Hybrid-IR, perceived noise and grey-white matter differentiation were better with DLR, while no difference was detected for other image quality characteristics. Noise magnitude was lower for DLR compared to Hybrid-IR and MBIR (5.6, 6.4 and 6.2, respectively) and SDNR higher (2.4, 1.9 and 2.0, respectively). Reconstruction times were 27 s, 44 s and 176 s for Hybrid-IR, DLR and MBIR respectively. Conclusions With a slight increase in reconstruction time, DLR results in lower noise and improved tissue differentiation compared to Hybrid-IR. Image quality of MBIR is significantly lower compared to DLR with much longer reconstruction times. Key Points • Deep learning reconstruction of cerebral non-contrast CT results in lower noise and improved tissue differentiation compared to hybrid-iterative reconstruction. • Deep learning reconstruction of cerebral non-contrast CT results in better image quality in all aspects evaluated compared to model-based iterative reconstruction. • Deep learning reconstruction only needs a slight increase in reconstruction time compared to hybrid-iterative reconstruction, while model-based iterative reconstruction requires considerably longer processing time.

scholarly journals Near-surface real-time seismic imaging using parsimonious interferometry

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sherif M. Hanafy ◽  
Hussein Hoteit ◽  
Jing Li ◽  
Gerard T. Schuster
Keyword(s):  
Fluid Flow ◽  
Real Time ◽  
Temporal Resolution ◽  
Seismic Imaging ◽  
Time Lapse ◽  
Rock Properties ◽  
Recording Time ◽  
Near Surface ◽  
Arrival Times ◽  
Order Of Magnitude

AbstractResults are presented for real-time seismic imaging of subsurface fluid flow by parsimonious refraction and surface-wave interferometry. Each subsurface velocity image inverted from time-lapse seismic data only requires several minutes of recording time, which is less than the time-scale of the fluid-induced changes in the rock properties. In this sense this is real-time imaging. The images are P-velocity tomograms inverted from the first-arrival times and the S-velocity tomograms inverted from dispersion curves. Compared to conventional seismic imaging, parsimonious interferometry reduces the recording time and increases the temporal resolution of time-lapse seismic images by more than an order-of-magnitude. In our seismic experiment, we recorded 90 sparse data sets over 4.5 h while injecting 12-tons of water into a sand dune. Results show that the percolation of water is mostly along layered boundaries down to a depth of a few meters, which is consistent with our 3D computational fluid flow simulations and laboratory experiments. The significance of parsimonious interferometry is that it provides more than an order-of-magnitude increase of temporal resolution in time-lapse seismic imaging. We believe that real-time seismic imaging will have important applications for non-destructive characterization in environmental, biomedical, and subsurface imaging.

scholarly journals Time-lapse imaging of CO2 migration within near-surface sediments during a controlled sub-seabed release experiment

2021 ◽  
Vol 109 ◽  
pp. 103363
Author(s):  
Ben Roche ◽  
Jonathan M. Bull ◽  
Hector Marin-Moreno ◽  
Timothy G. Leighton ◽  
Ismael H. Falcon-Suarez ◽  
...  
Keyword(s):  
Surface Sediments ◽  
Time Lapse ◽  
Near Surface ◽  
Release Experiment ◽  
Time Lapse Imaging

Model-based reconstruction algorithm in the detection of acute trauma-related lesions in brain CT examinations

2021 ◽  
pp. 197140092110087
Author(s):  
Andrea De Vito ◽  
Cesare Maino ◽  
Sophie Lombardi ◽  
Maria Ragusi ◽  
Cammillo Talei Franzesi ◽  
...  
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Signal To Noise Ratio ◽  
Reconstruction Algorithm ◽  
Signal To Noise ◽  
Subjective Image Quality ◽  
Model Based ◽  
Hybrid Iterative Reconstruction ◽  
Noise Ratio ◽  
Enhanced Computed Tomography

Background and purpose To evaluate the added value of a model-based reconstruction algorithm in the assessment of acute traumatic brain lesions in emergency non-enhanced computed tomography, in comparison with a standard hybrid iterative reconstruction approach. Materials and methods We retrospectively evaluated a total of 350 patients who underwent a 256-row non-enhanced computed tomography scan at the emergency department for brain trauma. Images were reconstructed both with hybrid and model-based iterative algorithm. Two radiologists, blinded to clinical data, recorded the presence, nature, number, and location of acute findings. Subjective image quality was performed using a 4-point scale. Objective image quality was determined by computing the signal-to-noise ratio and contrast-to-noise ratio. The agreement between the two readers was evaluated using k-statistics. Results A subjective image quality analysis using model-based iterative reconstruction gave a higher detection rate of acute trauma-related lesions in comparison to hybrid iterative reconstruction (extradural haematomas 116 vs. 68, subdural haemorrhages 162 vs. 98, subarachnoid haemorrhages 118 vs. 78, parenchymal haemorrhages 94 vs. 64, contusive lesions 36 vs. 28, diffuse axonal injuries 75 vs. 31; all P<0.001). Inter-observer agreement was moderate to excellent in evaluating all injuries (extradural haematomas k=0.79, subdural haemorrhages k=0.82, subarachnoid haemorrhages k=0.91, parenchymal haemorrhages k=0.98, contusive lesions k=0.88, diffuse axonal injuries k=0.70). Quantitatively, the mean standard deviation of the thalamus on model-based iterative reconstruction images was lower in comparison to hybrid iterative one (2.12 ± 0.92 vsa 3.52 ± 1.10; P=0.030) while the contrast-to-noise ratio and signal-to-noise ratio were significantly higher (contrast-to-noise ratio 3.06 ± 0.55 vs. 1.55 ± 0.68, signal-to-noise ratio 14.51 ± 1.78 vs. 8.62 ± 1.88; P<0.0001). Median subjective image quality values for model-based iterative reconstruction were significantly higher ( P=0.003). Conclusion Model-based iterative reconstruction, offering a higher image quality at a thinner slice, allowed the identification of a higher number of acute traumatic lesions than hybrid iterative reconstruction, with a significant reduction of noise.

scholarly journals Structured Computational Modeling of Human Visual System for No-reference Image Quality Assessment

2021 ◽  
Author(s):  
Wen-Han Zhu ◽  
Wei Sun ◽  
Xiong-Kuo Min ◽  
Guang-Tao Zhai ◽  
Xiao-Kang Yang
Keyword(s):  
Information Processing ◽  
Image Quality ◽  
Visual System ◽  
Computational Modeling ◽  
Quality Assessment ◽  
Human Visual System ◽  
Visual Communication ◽  
Visual Experience ◽  
Image Quality Assessment ◽  
Model Based

AbstractObjective image quality assessment (IQA) plays an important role in various visual communication systems, which can automatically and efficiently predict the perceived quality of images. The human eye is the ultimate evaluator for visual experience, thus the modeling of human visual system (HVS) is a core issue for objective IQA and visual experience optimization. The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively, while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity. For bridging the gap between signal distortion and visual experience, in this paper, we propose a novel perceptual no-reference (NR) IQA algorithm based on structural computational modeling of HVS. According to the mechanism of the human brain, we divide the visual signal processing into a low-level visual layer, a middle-level visual layer and a high-level visual layer, which conduct pixel information processing, primitive information processing and global image information processing, respectively. The natural scene statistics (NSS) based features, deep features and free-energy based features are extracted from these three layers. The support vector regression (SVR) is employed to aggregate features to the final quality prediction. Extensive experimental comparisons on three widely used benchmark IQA databases (LIVE, CSIQ and TID2013) demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.

Sign in / Sign up

Export Citation Format

Share Document