Attenuation Compensation Method Research Articles

A comparison of the compensation effects of two typical post-stack attenuation compensation methods

A comparison of the compensation effects of two typical post-stack attenuation compensation methods

Multichannel seismic attenuation compensation and interpolation with curvelet sparse constraint of frequency-wavenumber spectrum

Abstract High-resolution exploration is hampered by seismic attenuation, caused by the viscosity and heterogeneity of underground media. Conventional single-channel attenuation compensation methods can increase the corresponding vertical resolution partially. While the lateral continuity of compensated seismic data is always ignored and the noise resistance can be improved. Therefore, multichannel attenuation compensation methods were proposed, including the algorithm with sparse curvelet coefficient constraint of the time-space (t-x) data. However, nonstationary seismic data may be affected by irregular missing traces in field cases, which severely degrades its lateral continuity and negatively affects the performance of multichannel attenuation compensation. Therefore, we concentrate on simultaneous multichannel attenuation compensation and missing trace interpolation in a unified framework. Based on the inversion framework of sparsity promotion, we propose an approach for simultaneous multichannel compensation and interpolation, utilizing sparse curvelet coefficient constraint of the recovered principal frequency-wavenumber (f-k) spectrum. The size of the principal f-k spectrum is reduced by at least half compared with that of the corresponding t-x band-limited data. It significantly reduces the computational expense of curvelet transform-based processing. Synthetic and field data experiments validate the effectiveness of the proposed method in efficiency improvement with consistent performance when compared to the multichannel method with sparse curvelet coefficient constraint of the t-x data in improving the vertical resolution and lateral continuity. Furthermore, we have discussed a potential acceleration strategy based on random sampling in the normal compensation issue.

A Stable Forward Modeling Approach in Heterogeneous Attenuating Media Using Reapplied Hilbert Transform

In the field of geological exploration and wave propagation theory, particularly in heterogeneous attenuating media, the stability of numerical simulations is a significant challenge for implementing effective attenuation compensation strategies. Consequently, the development and optimization of algorithms and techniques that can mitigate these numerical instabilities are critical for ensuring the accuracy and practicality of attenuation compensation methods. This is essential to reveal subsurface structure information accurately and enhance the reliability of geological interpretation. We present a method for stable forward modeling in strongly attenuating media by reapplying the Hilbert transform to eliminate increasing negative frequency components. We derived and validated new constant-Q wave equation (CWE) formulations and a stable solving method. Our study reveals that the original CWE equations, when utilizing the analytic signal, regenerate and amplify negative frequencies, leading to instability. Implementing our method maintains high accuracy between analytical and numerical solutions. The application of our approach to the Chimney Model, compared with results from the acoustic wave equation, confirms the reliability and effectiveness of the proposed equations and method.

Low-frequency ultrasonic array imaging for detecting concrete structural defects in blind zones

Ultrasonic array (UA) imaging is a promising non-destructive testing (NDT) method that is extensively used for defect detection. Due to the high attenuation characteristics of ultrasonic wave propagation in concrete structures and the directivity of sensors, the total focus method (TFM) easily misses specific defects in blind zones that are far from the sensors or located at a large deflection angle. To overcome this limitation, the diffusion attenuation compensation factor and solid directivity correction factor are adopted to improve the scattered signal energy of defects that are in blind zones. On this basis, the diffusion attenuation compensation method (DACM), the solid directivity correction method (SDCM), and the diffusion attenuation compensation-based solid directivity correction method (DAC-SDCM) are proposed. These methods are applied to characterize multiple circular holes in concrete structures using the dry point contact (DPC) low-frequency UA, and the detection results are evaluated from the intensity curve and detection area of ultrasonic images. The numerical and experimental results indicate that DACM is suitable for detecting defects located at longer distances, SDCM is capable of detecting defects located at larger deflection angles, and DAC-SDCM can significantly improve the detection performance of defects that are distant and have large deflection angles. The findings demonstrate that the proposed methods can significantly improve the detection ability of defects in blind zones and broaden the application of DPC low-frequency UA in the health monitoring of concrete structures.

Robust seismic attenuation compensation based on generalized minimax concave penalty sparse representation

Abstract Deep hydrocarbon resources have become more and more important nowadays. However, owing to the affection of long-distance propagation and stratigraphic absorption, seismic data coming from deep beds generally suffer from weak energy, low resolution, and low signal-to-noise ratio (SNR), which seriously influence the reliability of seismic interpretation. Generally, inverse Q (quality factor) filtering (IQF) is used for absorption compensation, but it may amplify noise at the same time. Although compensation methods based on inversion overcomes the instability, it is still difficult to obtain high-SNR results. To address this issue, under the framework of sparse representation theory, we proposed a single-channel attenuation compensation method constrained by generalized minimax concave (GMC) penalty function. It takes the modified Kolsky model to describe seismic absorption and combines sparse representation theory to create objective function. Furthermore, a GMC penalty function is utilized to promote sparsity. It allows more accurate estimates of sparse coefficients from noise-contaminated seismic data. Although the GMC penalty itself is concave, the objective function remains strictly convex. Therefore, globally optimal sparse solutions can be obtained through an operator-splitting algorithm. Even in the presence of noise, this method can obtain stable and accurate compensation results through reconstruction. Synthetic data tests and field seismic data application showed that this method has high robustness to noise. It can stably and effectively compensate for the energy loss of seismic data, as well as maintain high SNR.

Damage localization using contact and non-contact narrow frequency band elastic wave generation

In this paper analyses of non-contact elastic wave generation based on an air-coupled transducer (ACT) are presented. Authors compared contact piezoelectric based (PZT) wave generation, with non-contact one using ACT for a narrow frequency band excitation. Elastic wave sensing was based in both cases on a scanning laser Doppler vibrometer. The problem of ACT slope angle for the effectiveness of elastic wave modes generation is analysed. It was shown that for an excitation frequency of 40 kHz it is possible to generate A0 wave mode both in the case of PZT and ACT. Both methods of wave generation are compared based on an analysis of damage localisation results. For this purpose wave irregularity mapping (WIM) algorithm was utilised together with two attenuation compensation methods (based on energy normalisation and weighting function). Specimens in the form of simple square GFRP panel and bonded GFRP aerospace structure with omega stiffeners were investigated. The authors investigated simulated damage (Teflon inserts) and real delamination. In this research very cheap and popular, low-frequency ACT was utilised giving the possibility of realisation of low-cost excitation method. ACTs connected with a laser vibrometry sensing allows of realisation of full non-contact damage localisation method. Authors presented also non typical but very useful application of SLDV allowing to visualise the effect of acoustic wave generation in the air and determination of the pattern of generated acoustic waves. This was based on the photo-acoustic effect.

Development and task-based evaluation of a scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT.

Attenuation compensation (AC) is beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). However, traditional AC methods require the availability of a transmission scan, most often a CT scan. This approach has the disadvantage of increased radiation dose, increased scanner costs, and the possibility of inaccurate diagnosis in cases of misregistration between the SPECT and CT images. Further, many SPECT systems do not include a CT component. To address these issues, we developed a Scatter-window projection and deep Learning-based AC (SLAC) method to perform AC without a separate transmission scan. To investigate the clinical efficacy of this method, we then objectively evaluated the performance of this method on the clinical task of detecting perfusion defects on MPI in a retrospective study with anonymized clinical SPECT/CT stress MPI images. The proposed method was compared with CT-based AC (CTAC) and no-AC (NAC) methods. Our results showed that the SLAC method yielded an almost overlapping receiver operating characteristic (ROC) plot and a similar area under the ROC (AUC) to the CTAC method on this task. These results demonstrate the capability of the SLAC method for transmission-less AC in SPECT and motivate further clinical evaluation.

Single underwater image enhancement based on differential attenuation compensation

High quality underwater images and videos are important for exploitation tasks in the underwater environment, but the complexity of the underwater imaging environment makes the quality of the acquired underwater images generally low. To correct the chromatic aberration and enhance the sharpness of underwater images in order to improve the quality of underwater images, we based on the differential compensation proposed a Differential Attenuation Compensation (DAC) method. The underwater image is contrast stretched to improve the contrast of the image, as well as the underwater image is denoised, for the red channel with serious loss of detail information we choose the blue and green channels with more detail information to compensate for this, and finally the image is restored through the grayscale world to obtain more realistic colors. Our method is qualitatively and quantitatively compared with multiple state-of-the-art methods in the public underwater image dataset, underwater image enhancement benchmark (UIEB) and enhancing underwater visual perception (EUVP), demonstrating that the underwater images processed by our method better resolve the problems of chromatic aberration and blur, with more realistic color, detail and better underwater image quality evaluation indicators

Inversion-based attenuation compensation with dip constraint

Instability is an inherent problem with the attenuation compensation methods and has been partially relieved by using the inverse scheme. However, the conventional inversion-based attenuation compensation approaches ignore the important prior information of the seismic dip. Thus, the compensated result appears to be distorted spatial continuity and has a low signal-to-noise ratio (S/N). To alleviate this issue, we have incorporated the seismic dip information into the inversion framework and have developed a dip-constrained attenuation compensation (DCAC) algorithm. The seismic dip information, calculated from the poststack seismic data, is the key to construct a dip constraint term. Benefiting from the introduction of the seismic dip constraint, the DCAC approach maintains the numerical stability and preserves the spatial continuity of the compensated result. Synthetic and field data examples demonstrate that the proposed method can not only improve seismic resolution, but also protect the continuity of seismic data.

Depth-resolved backscattering signal reconstruction based OCT attenuation compensation.

Optical coherence tomography (OCT) with a robust depth-resolved attenuation compensation method for a wide range of imaging applications is proposed and demonstrated. We derive a model for deducing the attenuation coefficients and the signal compensation value using the depth-dependent backscattering profiles, to mitigate under and over-estimation in tissue imaging. We validated the method using numerical simulation and phantoms, where we achieved stable and robust compensation results over the entire depth of samples. The comparison between other attenuation characterization models and our proposed model is also performed.

Absorption Attenuation Compensation Using an End-to-End Deep Neural Network

Absorption attenuation compensation is an important part of seismic data processing. It enhances the resolution of non-stationary seismic data by compensating the amplitude energy and correcting phase distortion. The stabilized inverse <i>Q</i> -filter method, a widely used attenuation compensation method, constructs compensation operators based on stratigraphy-related assumptions and compensates seismic data using time-window analysis, which is computationally complex and sensitive to noise. The essence of attenuation compensation lies in the establishment of a nonlinear mapping relationship between attenuated and non-attenuated seismic traces, which strongly benefits from deep learning. This paper proposes a new method for attenuation compensation based on an end-to-end deep neural network to reduce the hand-crafted step of time-window analysis. Instead, the convolutional blocks of the network automatically learn and process seismic data features to achieve simultaneous amplitude and phase compensation. We have constructed two end-to-end network architectures for attenuation compensation: a fully convolutional network (FCN) and a U-Net. As an effective spectrum-broadening method, the compensation method based on the U-Net is shown to enhance vertical resolution with good lateral continuity, to provide reliable compensation results without complex calculations, and to exhibit high noise robustness. Synthetic data tests indicate that the compensation results from the U-Net are better than those from either the FCN or the stabilized inverse <i>Q</i> -filter method at different noise levels. Moreover, the correlation coefficient between the U-Net compensation results of the synthetic profile and the reference non-attenuated profile is higher than that of the FCN and the stabilized inverse <i>Q</i> -filter method. A field data application further verifies the effectiveness of this method.

Comparison of attenuation compensation methods in the estimation of the backscatter coefficient of breast cancer

Goal: This study compares two strategies to compensate for attenuation in the estimation of the backscatter coefficient σ of breast cancer Methods: Attenuation compensation was performed using local attenuation estimates from a constrained Spectral-Log-Difference (CSLD) method, and average estimates from a dynamic programming (DP)-based regularized method. First, bias and linearity of σ estimates from both strategies were evaluated in a Gammex 410SCG phantom with inclusions with known σ imaged at 8 MHz on a Verasonics Vantage 128 scanner. Then, the strategies were compared in terms of the contrast-to-noise ratio (CNR) between adipose tissue and invasive ductal carcinoma. σ estimates were obtained from 10 patients with biopsy-confirmed IDCs imaged invivo with a 12L4 transducer on a Siemens Acuson S2000 as part of an IRB-approved protocol at the National Institute of Cancerology in Mexico City. DP σ estimates provided smaller bias and better linearity compared to estimates of CSLD. In the in vivo study, DP σ estimates produced negative IDC-vs-adipose CNR that was significantly different from zero (p = 0.002) and agreed with the hypoechoic appearance of IDC. [Work supported by CONACYT Ciencia de Frontera 1311307, ASA international student support, and UNAM PAPIIT IA102320. We thank Siemens Mexico for scanner loan.]

Optimized OCT-based depth-resolved model for attenuation compensation using point-spread-function calibration.

Optical coherence tomography (OCT) with a robust depth-resolved attenuation compensation method for a wide range of imaging applications is proposed and demonstrated. The proposed novel OCT attenuation compensation algorithm introduces an optimized axial point spread function (PSF) to modify existing depth-resolved methods and mitigates under and overestimation in biological tissues, providing a uniform resolution over the entire imaging range. The preliminary study is implemented using A-mode numerical simulation, where this method achieved stable and robust compensation results over the entire depth of samples. The experiment results using phantoms and corneal imaging exhibit agreement with the simulation result evaluated using signal-to-noise (SNR) and contrast-to-noise (CNR) metrics.

A physics and learning-based transmission-less attenuation compensation method for SPECT.

Attenuation compensation (AC) is a pre-requisite for reliable quantification and beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT). Typical AC methods require the availability of an attenuation map, which is obtained using a transmission scan, such as a CT scan. This has several disadvantages such as increased radiation dose, higher costs, and possible misalignment between SPECT and CT scans. Also, often a CT scan is unavailable. In this context, we and others are showing that scattered photons in SPECT contain information to estimate the attenuation distribution. To exploit this observation, we propose a physics and learning-based method that uses the SPECT emission data in the photopeak and scatter windows to perform transmission-less AC in SPECT. The proposed method uses data acquired in the scatter window to reconstruct an initial estimate of the attenuation map using a physics-based approach. A convolutional neural network is then trained to segment this initial estimate into different regions. Pre-defined attenuation coefficients are assigned to these regions, yielding the reconstructed attenuation map, which is then used to reconstruct the activity distribution using an ordered subsets expectation maximization (OSEM)-based reconstruction approach. We objectively evaluated the performance of this method using highly realistic simulation studies conducted on the clinically relevant task of detecting perfusion defects in myocardial perfusion SPECT. Our results showed no statistically significant differences between the performance achieved using the proposed method and that with the true attenuation maps. Visually, the images reconstructed using the proposed method looked similar to those with the true attenuation map. Overall, these results provide evidence of the capability of the proposed method to perform transmission-less AC and motivate further evaluation.

Quantification of the backscatter coefficient in heterogeneous media: Comparison of attenuation compensation methods

The estimation of backscatter coefficient, from in vivo tissue requires accurate compensation for intervening tissue attenuation. Current attenuation compensation methods (ACM) have been tested in fully or piecewise homogeneous phantoms. Thus, evidence of their performance in complex media remains scant. In this study we compare the performance of two ACM in a tissue-mimicking material with strong reflectors (SR). A gel-based phantom with SR was scanned with a L11-5v transducer on a Vantage 128 system (Verasonics). Estimates of from the phantom's background were obtained from the IQ echo signals using the known phantom attenuation (KA) or two ACM (a Constrained-Log-Difference (CLD) and a dynamic programming (DP) regularized method).The former method was used as gold standard. To analyze bias versus depth, a Pearson correlation coefficient was computed and the mean difference (MD) vs. depth was estimated. CLD-based showed a strong correlation (r = 0.96) with depth, while the correlation of DP-based estimates was weaker. DP-based values were closer to those obtained with KA (MD [0.9–1.15]) compared to the CLD-based estimates (MD [1.0–1.79]). The DP, regularized ACM show less sensitivity to the presence of SR compared to conventional ACM. We are currently using DP-based ACM to characterize breast lesions.

A LIST-MODE OSEM-BASED ATTENUATION AND SCATTER COMPENSATION METHOD FOR SPECT.

Reliable attenuation and scatter compensation (ASC) is a pre-requisite for quantification and beneficial for visual interpretation tasks in SPECT. In this paper, we develop a reconstruction method that uses the entire SPECT emission data, i.e. data in both the photopeak and scatter windows, acquired in list-mode format and including the energy attribute of the detected photon, to perform ASC. We implemented a GPU-based version of this method using an ordered subsets expectation maximization (OSEM) algorithm. The method was objectively evaluated using realistic simulation studies on the task of estimating uptake in the striatal regions of the brain in a 2-D dopamine transporter (DaT)-scan SPECT study. We observed that inclusion of data from the scatter window and using list-mode data yielded improved quantification compared to using data only from the photopeak window or using binned data. These results motivate further development of list-mode-based ASC methods that include scatter-window data for SPECT.

A Stable and Efficient Attenuation Compensation Method based on Inversion

AbstractInverse Q filtering, which can compensate amplitude and correct phase, is an effective method to improve the resolution of seismic data. The conventional inverse Q method is usually based on wavefield continuation, which is unstable or under‐compensation. Based on the forward Q filtering equation in wavefield continuation, this work proposes a new attenuation compensation method, which is stable and accurate, taking advantages of the inverse theory and regularization strategy to obtain compensated seismic data eventually. It is also computationally efficient because only effective frequency components are calculated. Tests on synthetic and real data prove that the proposed method is effective.

Signal Attenuation and Compensation Model in Long-Distance Communication

The communication signal attenuation compensation method for long distance communication is studied in this paper in order to improve the accuracy of the signal transmission. In long-distance communication, due to the shock pulse signal attenuation, the accuracy of signal is reduced. The use of auto-regressive integrated moving control method of error compensation can solve this problem. In the process of communication, the cumulative attenuation rate of communications network is used to establish auto-regressive integrated moving control model to achieve cumulative error compensation. The experiment results show that compensating the total amount of cumulative attenuation of signal in long-distance communication can reduce the attenuating property of communication network and achieve the requirements of communication.

Attenuation compensation method based on inversion

Attenuation compensation, which corrects the attenuation and dispersion of seismic waves, is one of the effective methods for improving seismic data resolution. In general, the attenuation compensation is achieved by an inverse Q-filter based on wave field continuation. In this paper, using the Futterman attenuation model, a method to compute synthetic seismogram is derived for an attenuation medium. Based on the synthetic method, the attenuation compensation problem is reduced to an inversion problem of the Fredholm integral equation and can be achieved by inversion. The Tikhonov regularization is used to improve inversion stability. The processing results of numerical simulation and real data show the effectiveness of the method.

Backscatter-Contour-Attenuation Joint Estimation Model for Attenuation Compensation in Ultrasound Imagery

Ultrasound B-scan exhibits shadowing and enhancement artifacts due to acoustic wave propagation and spatially varying scatter attenuation across layers of tissues. These artifacts hide underlying echo signals that are truly clinically indicative of diseases. Attenuation compensation estimates and corrects for shadowing and enhancement artifacts, which improves the quality of ultrasound imaging. Block-based attenuation compensation methods, widely employed in commercial scanners, produce results with resolutions limited by the block size. To obtain higher spatial resolution (as desired for quantitative analysis), we present a backscatter-contour-attenuation (BCA) joint estimation model for attenuation compensation in pulse-echo imaging using a set of self-consistent partial differential equations and a contour evolution model. The problem is posed as reconstructing sources of information from observations. We derive the joint estimation model from minimizing a cost functional of separated attributes with region-based isotropic regularizations. A three-step alternating minimization method is adopted towards a tractable numerical solution. Detailed numerical methods are described. The efficacy of the proposed approach is demonstrated using simulated and real images.