In this work, we draw connections between the imaging conditions using the impedance kernel, the inverse scattering imaging condition, and the energy norm imaging condition in acoustic and elastic reverse-time migration (RTM). Traditional RTM often introduces large low-wavenumber artifacts that degrade image quality in intricate geological structures with large velocity variations. In practice, the Laplacian filter is commonly used to remove these low-wavenumber artifacts, but it changes the image wavenumber spectrum. The advanced imaging conditions of the inverse scattering, the energy norm, and the impedance kernel can effectively remove the low-wavenumber artifacts while not changing the wavenumber spectrum. This study aims to build a connection between these three types of imaging conditions by conducting detailed analysis in the wavenumber domain for acoustic and elastic RTMs. We find that they are exactly the same except for the varying weights of the source-receiver wavefield cross-correlation. All three imaging conditions can generate clear RTM images that are not affected by low-wavenumber artifacts. Numerical examples for a simple model, Sigsbee 2a, and BP models verify the consistency of these three imaging conditions and show their advantage over conventional simple zero-lag cross-correlation imaging conditions. This is important for improving the quality and reliability of seismic imaging technology.
{"title":"Consistency of the inverse scattering imaging condition, the energy norm imaging condition and the impedance kernel in acoustic and elastic reverse-time migration","authors":"Pengfei Wang, Jidong Yang, Jianping Huang, Jiaxing Sun, Chong Zhao","doi":"10.1093/jge/gxae022","DOIUrl":"https://doi.org/10.1093/jge/gxae022","url":null,"abstract":"\u0000 In this work, we draw connections between the imaging conditions using the impedance kernel, the inverse scattering imaging condition, and the energy norm imaging condition in acoustic and elastic reverse-time migration (RTM). Traditional RTM often introduces large low-wavenumber artifacts that degrade image quality in intricate geological structures with large velocity variations. In practice, the Laplacian filter is commonly used to remove these low-wavenumber artifacts, but it changes the image wavenumber spectrum. The advanced imaging conditions of the inverse scattering, the energy norm, and the impedance kernel can effectively remove the low-wavenumber artifacts while not changing the wavenumber spectrum. This study aims to build a connection between these three types of imaging conditions by conducting detailed analysis in the wavenumber domain for acoustic and elastic RTMs. We find that they are exactly the same except for the varying weights of the source-receiver wavefield cross-correlation. All three imaging conditions can generate clear RTM images that are not affected by low-wavenumber artifacts. Numerical examples for a simple model, Sigsbee 2a, and BP models verify the consistency of these three imaging conditions and show their advantage over conventional simple zero-lag cross-correlation imaging conditions. This is important for improving the quality and reliability of seismic imaging technology.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140440585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction to: Evaluation of membrane quality and entrance pressure of oil-based mud at elevated temperatures","authors":"","doi":"10.1093/jge/gxae027","DOIUrl":"https://doi.org/10.1093/jge/gxae027","url":null,"abstract":"","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140443196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Junjie Wu, Qingquan Zhi, Xingchun Wang, Xiaohong Deng, Xiaodong Chen, Yi Zhao, Yue Huang, Yuge Liu, Du Xiao
The karst strata in the south-western mountainous areas of China are extensively developed, creating a fragile geological environment. Landslide geological disasters occur frequently in these areas due to high annual rainfall, concentrated time periods, and frequent human engineering activities. Conventional ground geophysical methods face challenges in complex terrains, making it difficult to quickly and reliably obtain underground structures in landslide-prone areas. The semi-airborne transient electromagnetic method (SATEM) combines ground-based transmission and airborne reception of electromagnetic responses. This method, characterized by large emission magnetic moment and rapid data collection in the air, offers advantages in detecting deep geological structures in complex terrain areas. This article presents the application of a newly developed loop source SATEM system, integrated with multi-rotor unmanned aerial vehicles (UAVs), to conduct deep geological structure detection experiments on a large-scale landslide. The inversion results clearly depict the spatial distribution of the Feixianguan Formation and Longtan Formation, as well as vertical fractures developed in the strata due to underground coal mining. The detection test demonstrates the applicability of the SATEM method in detecting underground structures in Karst Plateau special landform areas, providing a new detection approach for similar regions.
{"title":"Exploring the Geological Structure of a Large-scale Landslide Using the Semi-airborne TEM in the Karst Area of Southwest China","authors":"Junjie Wu, Qingquan Zhi, Xingchun Wang, Xiaohong Deng, Xiaodong Chen, Yi Zhao, Yue Huang, Yuge Liu, Du Xiao","doi":"10.1093/jge/gxae019","DOIUrl":"https://doi.org/10.1093/jge/gxae019","url":null,"abstract":"\u0000 The karst strata in the south-western mountainous areas of China are extensively developed, creating a fragile geological environment. Landslide geological disasters occur frequently in these areas due to high annual rainfall, concentrated time periods, and frequent human engineering activities. Conventional ground geophysical methods face challenges in complex terrains, making it difficult to quickly and reliably obtain underground structures in landslide-prone areas. The semi-airborne transient electromagnetic method (SATEM) combines ground-based transmission and airborne reception of electromagnetic responses. This method, characterized by large emission magnetic moment and rapid data collection in the air, offers advantages in detecting deep geological structures in complex terrain areas. This article presents the application of a newly developed loop source SATEM system, integrated with multi-rotor unmanned aerial vehicles (UAVs), to conduct deep geological structure detection experiments on a large-scale landslide. The inversion results clearly depict the spatial distribution of the Feixianguan Formation and Longtan Formation, as well as vertical fractures developed in the strata due to underground coal mining. The detection test demonstrates the applicability of the SATEM method in detecting underground structures in Karst Plateau special landform areas, providing a new detection approach for similar regions.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139964030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Controlled-Source Audio Frequency Magnetotellurics (CSAMT) is an artificial-source electromagnetic technique that partially mitigates the limitations of weak natural field signals. However, practical field surveys inevitably encounter strong interference, severely affecting signal quality. Traditional methods like Fourier transformation, which directly computes apparent resistivity from frequency-domain information, are inadequate for this context, so we need alternative denoising approaches. However, research on CSAMT denoising is currently limited. Given the excellent performance of Long Short-Term Memory (LSTM) neural networks in the processing of Magnetotelluric (MT) data, as demonstrated by previous studies, this paper proposes the use of LSTM to denoise CSAMT signals in the time domain. Unlike traditional denoising methods, we aim to directly extract the target frequency signal from the time series data for denoising. For MT data, target frequency signals and noise are all mixed together, so noise suppression can only be achieved by identifying noise characteristics in the time series. However, unlike MT data, CSAMT data has an artificial transmitting source, and the frequency of the valid signal is fixed within a time interval. This allows for the direct extraction of target frequency signals without considering the complex characteristics of noise. In this study, we developed a neural network based on bidirectional LSTM to accomplish the task of noise suppression. After conducting both simulated and measured data tests, this method was able to, on average, improve the signal-to-noise ratio (SNR) of CSAMT data by approximately 20dB and partially address the challenge of denoising when the data's SNR falls below 0dB.
{"title":"Denoising CSAMT signals in the time domain base on long short-term memory","authors":"Bingcheng Xu, Zhiguo An, Ying Han, Gaofeng Ye","doi":"10.1093/jge/gxae017","DOIUrl":"https://doi.org/10.1093/jge/gxae017","url":null,"abstract":"\u0000 Controlled-Source Audio Frequency Magnetotellurics (CSAMT) is an artificial-source electromagnetic technique that partially mitigates the limitations of weak natural field signals. However, practical field surveys inevitably encounter strong interference, severely affecting signal quality. Traditional methods like Fourier transformation, which directly computes apparent resistivity from frequency-domain information, are inadequate for this context, so we need alternative denoising approaches. However, research on CSAMT denoising is currently limited. Given the excellent performance of Long Short-Term Memory (LSTM) neural networks in the processing of Magnetotelluric (MT) data, as demonstrated by previous studies, this paper proposes the use of LSTM to denoise CSAMT signals in the time domain. Unlike traditional denoising methods, we aim to directly extract the target frequency signal from the time series data for denoising. For MT data, target frequency signals and noise are all mixed together, so noise suppression can only be achieved by identifying noise characteristics in the time series. However, unlike MT data, CSAMT data has an artificial transmitting source, and the frequency of the valid signal is fixed within a time interval. This allows for the direct extraction of target frequency signals without considering the complex characteristics of noise. In this study, we developed a neural network based on bidirectional LSTM to accomplish the task of noise suppression. After conducting both simulated and measured data tests, this method was able to, on average, improve the signal-to-noise ratio (SNR) of CSAMT data by approximately 20dB and partially address the challenge of denoising when the data's SNR falls below 0dB.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139848117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Controlled-Source Audio Frequency Magnetotellurics (CSAMT) is an artificial-source electromagnetic technique that partially mitigates the limitations of weak natural field signals. However, practical field surveys inevitably encounter strong interference, severely affecting signal quality. Traditional methods like Fourier transformation, which directly computes apparent resistivity from frequency-domain information, are inadequate for this context, so we need alternative denoising approaches. However, research on CSAMT denoising is currently limited. Given the excellent performance of Long Short-Term Memory (LSTM) neural networks in the processing of Magnetotelluric (MT) data, as demonstrated by previous studies, this paper proposes the use of LSTM to denoise CSAMT signals in the time domain. Unlike traditional denoising methods, we aim to directly extract the target frequency signal from the time series data for denoising. For MT data, target frequency signals and noise are all mixed together, so noise suppression can only be achieved by identifying noise characteristics in the time series. However, unlike MT data, CSAMT data has an artificial transmitting source, and the frequency of the valid signal is fixed within a time interval. This allows for the direct extraction of target frequency signals without considering the complex characteristics of noise. In this study, we developed a neural network based on bidirectional LSTM to accomplish the task of noise suppression. After conducting both simulated and measured data tests, this method was able to, on average, improve the signal-to-noise ratio (SNR) of CSAMT data by approximately 20dB and partially address the challenge of denoising when the data's SNR falls below 0dB.
{"title":"Denoising CSAMT signals in the time domain base on long short-term memory","authors":"Bingcheng Xu, Zhiguo An, Ying Han, Gaofeng Ye","doi":"10.1093/jge/gxae017","DOIUrl":"https://doi.org/10.1093/jge/gxae017","url":null,"abstract":"\u0000 Controlled-Source Audio Frequency Magnetotellurics (CSAMT) is an artificial-source electromagnetic technique that partially mitigates the limitations of weak natural field signals. However, practical field surveys inevitably encounter strong interference, severely affecting signal quality. Traditional methods like Fourier transformation, which directly computes apparent resistivity from frequency-domain information, are inadequate for this context, so we need alternative denoising approaches. However, research on CSAMT denoising is currently limited. Given the excellent performance of Long Short-Term Memory (LSTM) neural networks in the processing of Magnetotelluric (MT) data, as demonstrated by previous studies, this paper proposes the use of LSTM to denoise CSAMT signals in the time domain. Unlike traditional denoising methods, we aim to directly extract the target frequency signal from the time series data for denoising. For MT data, target frequency signals and noise are all mixed together, so noise suppression can only be achieved by identifying noise characteristics in the time series. However, unlike MT data, CSAMT data has an artificial transmitting source, and the frequency of the valid signal is fixed within a time interval. This allows for the direct extraction of target frequency signals without considering the complex characteristics of noise. In this study, we developed a neural network based on bidirectional LSTM to accomplish the task of noise suppression. After conducting both simulated and measured data tests, this method was able to, on average, improve the signal-to-noise ratio (SNR) of CSAMT data by approximately 20dB and partially address the challenge of denoising when the data's SNR falls below 0dB.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139788327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The discrete cosine transform is a commonly used technique in the field of signal processing that employs cosine basis functions for signal analysis. Traditionally, the regression coefficients of the cosine basis functions are solely based on frequency information. This paper extends the regression coefficients associated with the cosine basis functions to take into account both frequency and time information, not just frequency information alone. This modification results in an ill-posed linear system, which requires regularization to prevent overfitting. To address this, the paper uses shaping regularization, a technique used to stabilize ill-posed problems. By doing so, the absolute values of these extended coefficients, now exhibiting variations in both frequency and time domains, are defined as the time-frequency distribution of that input signal. The numerical experiments conducted to validate this approach demonstrate that the proposed method yields a commendable time-frequency resolution. Consequently, it proves valuable for interpreting seismic data, showcasing its potential for applications in this field.
{"title":"Time varying discrete cosine transform based on shaping regularization and its application in seismic data analysis","authors":"Zhaolin Zhu, Guoning Wu, Yaxin Gu, Jinliang Huang, Zhihao Chen, Haotian Lu","doi":"10.1093/jge/gxae016","DOIUrl":"https://doi.org/10.1093/jge/gxae016","url":null,"abstract":"\u0000 The discrete cosine transform is a commonly used technique in the field of signal processing that employs cosine basis functions for signal analysis. Traditionally, the regression coefficients of the cosine basis functions are solely based on frequency information. This paper extends the regression coefficients associated with the cosine basis functions to take into account both frequency and time information, not just frequency information alone. This modification results in an ill-posed linear system, which requires regularization to prevent overfitting. To address this, the paper uses shaping regularization, a technique used to stabilize ill-posed problems. By doing so, the absolute values of these extended coefficients, now exhibiting variations in both frequency and time domains, are defined as the time-frequency distribution of that input signal. The numerical experiments conducted to validate this approach demonstrate that the proposed method yields a commendable time-frequency resolution. Consequently, it proves valuable for interpreting seismic data, showcasing its potential for applications in this field.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139855395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The discrete cosine transform is a commonly used technique in the field of signal processing that employs cosine basis functions for signal analysis. Traditionally, the regression coefficients of the cosine basis functions are solely based on frequency information. This paper extends the regression coefficients associated with the cosine basis functions to take into account both frequency and time information, not just frequency information alone. This modification results in an ill-posed linear system, which requires regularization to prevent overfitting. To address this, the paper uses shaping regularization, a technique used to stabilize ill-posed problems. By doing so, the absolute values of these extended coefficients, now exhibiting variations in both frequency and time domains, are defined as the time-frequency distribution of that input signal. The numerical experiments conducted to validate this approach demonstrate that the proposed method yields a commendable time-frequency resolution. Consequently, it proves valuable for interpreting seismic data, showcasing its potential for applications in this field.
{"title":"Time varying discrete cosine transform based on shaping regularization and its application in seismic data analysis","authors":"Zhaolin Zhu, Guoning Wu, Yaxin Gu, Jinliang Huang, Zhihao Chen, Haotian Lu","doi":"10.1093/jge/gxae016","DOIUrl":"https://doi.org/10.1093/jge/gxae016","url":null,"abstract":"\u0000 The discrete cosine transform is a commonly used technique in the field of signal processing that employs cosine basis functions for signal analysis. Traditionally, the regression coefficients of the cosine basis functions are solely based on frequency information. This paper extends the regression coefficients associated with the cosine basis functions to take into account both frequency and time information, not just frequency information alone. This modification results in an ill-posed linear system, which requires regularization to prevent overfitting. To address this, the paper uses shaping regularization, a technique used to stabilize ill-posed problems. By doing so, the absolute values of these extended coefficients, now exhibiting variations in both frequency and time domains, are defined as the time-frequency distribution of that input signal. The numerical experiments conducted to validate this approach demonstrate that the proposed method yields a commendable time-frequency resolution. Consequently, it proves valuable for interpreting seismic data, showcasing its potential for applications in this field.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139795726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Northeast India encompasses numerous thrusts, faults, and lineaments with undulated surface topography and is one of the utmost tectonically active regions in the world. Owing to the results of the collision of the Indian Plate under the Tibetan Plate and Burmese Plate, respectively, this area has affected the highest seismic potential zone-V, triggering many earthquakes. The current study area is located in and around the Shillong plateau, Mikir Hills, Naga Hills, Arakan-Yoma fold belt, Bengal basin, and Mishmi hills of the Himalayan foothills and that fall under the northeast of India. The thrusts and faults information available in this area are very scanty due to limited availability of geoscientific data and revealing seismic survey. Henceforth, it is necessary to get enhanced geoscientific learning for a better understanding of thrusts, faults, and lineaments information, the most positive and most negative curvature attribute analyses have been carried out using ground gravity data in this area. The significant derived results from this study encourage supplementary findings of thrust, fault, and lineament information, which also correlate well with the previously found results of 3D Euler deconvolution and source edge detection. Although, gravity data interpretation has its own limitations, however, the current derived results using the latest curvature analysis approach utilizing gravity data show realistic invigorated solutions for a better understanding of the thrust, fault, and lineament locations in this area.
印度东北部包括众多推力、断层和线状构造，地表地形起伏不定，是世界上构造最活跃的地区之一。由于印度板块分别与西藏板块和缅甸板块碰撞，该地区成为地震潜势最高的 V 区，引发了许多地震。目前的研究区域位于喜马拉雅山麓的志隆高原、米基尔丘陵、那加丘陵、阿拉干-山脉褶皱带、孟加拉盆地和米什米丘陵及其周边地区，属于印度东北部。由于地球科学数据和揭示性地震勘测有限，该地区的推力和断层信息非常少。因此，有必要加强地球科学学习，以便更好地了解推力、断层和线状信息，我们利用该地区的地面重力数据进行了最正和最负曲率属性分析。这项研究得出的重要结果鼓励了对推力、断层和线状信息的补充发现，这也与之前发现的三维欧拉解卷积和源边缘检测结果密切相关。虽然重力数据解释有其自身的局限性，但目前利用重力数据的最新曲率分析方法得出的推导结果显示了现实可行的解决方案，有助于更好地了解该地区的推力、断层和线状构造位置。
{"title":"Automatic thrust/fault and edge location with gravity data across the Shillong plateau and Mikir hill complex in northeastern India using the most positive and most negative curvature interpretation","authors":"Gopal K Ghosh","doi":"10.1093/jge/gxad101","DOIUrl":"https://doi.org/10.1093/jge/gxad101","url":null,"abstract":"Northeast India encompasses numerous thrusts, faults, and lineaments with undulated surface topography and is one of the utmost tectonically active regions in the world. Owing to the results of the collision of the Indian Plate under the Tibetan Plate and Burmese Plate, respectively, this area has affected the highest seismic potential zone-V, triggering many earthquakes. The current study area is located in and around the Shillong plateau, Mikir Hills, Naga Hills, Arakan-Yoma fold belt, Bengal basin, and Mishmi hills of the Himalayan foothills and that fall under the northeast of India. The thrusts and faults information available in this area are very scanty due to limited availability of geoscientific data and revealing seismic survey. Henceforth, it is necessary to get enhanced geoscientific learning for a better understanding of thrusts, faults, and lineaments information, the most positive and most negative curvature attribute analyses have been carried out using ground gravity data in this area. The significant derived results from this study encourage supplementary findings of thrust, fault, and lineament information, which also correlate well with the previously found results of 3D Euler deconvolution and source edge detection. Although, gravity data interpretation has its own limitations, however, the current derived results using the latest curvature analysis approach utilizing gravity data show realistic invigorated solutions for a better understanding of the thrust, fault, and lineament locations in this area.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139750838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pingmin Zhang, Gang Yao, Qingqing Zheng, Xin-Yu Fang, Di Wu
An accurate pure qP-wave equation in TI media and its efficient and stable implementation are valuable for seismic imaging and inversion. Owing to the complexity of the qP-wave phase velocity expression in anisotropic media, it is difficult to construct such a pure qP-wave equation. In this paper, we combine the Taylor expansion and scalar operator methods to formulate an efficient and stable pure qP-wave equation in TI media. First, the Taylor expansion method is used to convert the square-root term into a fractional term in the qP-wave phase velocity expression. We further improve the approximation accuracy of the resulting equation by a correction technique. Then, the scalar operator is applied to scalarize the equivalent form of the fractional term in the approximated dispersion equation, deriving a simple and easy-to-implement pure qP-wave equation. We utilize the optical flow method to compute the direction of wave propagation, which improves the calculation accuracy of the scalar operators. Numerical experiments with representative models demonstrate that the new method has higher accuracy and better adaptability to models with strong anisotropy, complex structure, and rapid variation of the tilt angle than previous methods.
TI 介质中精确的纯 qP 波方程及其高效稳定的实现对地震成像和反演非常重要。由于各向异性介质中 qP 波相位速度表达的复杂性，构建这样一个纯 qP 波方程非常困难。本文结合泰勒展开法和标量算子法，提出了一种高效稳定的 TI 介质中的纯 qP 波方程。首先，我们使用泰勒展开法将 qP 波相位速度表达式中的平方根项转换为分数项。我们通过修正技术进一步提高了所得方程的近似精度。然后，应用标量算子将近似色散方程中分数项的等效形式标量化，从而得出一个简单且易于实现的纯 qP 波方程。我们利用光流方法计算波的传播方向，从而提高了标量算子的计算精度。用代表性模型进行的数值实验证明，与以前的方法相比，新方法具有更高的精度，对各向异性强、结构复杂、倾斜角变化快的模型具有更好的适应性。
{"title":"An improved pure quasi-P-wave equation for complex anisotropic media","authors":"Pingmin Zhang, Gang Yao, Qingqing Zheng, Xin-Yu Fang, Di Wu","doi":"10.1093/jge/gxae020","DOIUrl":"https://doi.org/10.1093/jge/gxae020","url":null,"abstract":"\u0000 An accurate pure qP-wave equation in TI media and its efficient and stable implementation are valuable for seismic imaging and inversion. Owing to the complexity of the qP-wave phase velocity expression in anisotropic media, it is difficult to construct such a pure qP-wave equation. In this paper, we combine the Taylor expansion and scalar operator methods to formulate an efficient and stable pure qP-wave equation in TI media. First, the Taylor expansion method is used to convert the square-root term into a fractional term in the qP-wave phase velocity expression. We further improve the approximation accuracy of the resulting equation by a correction technique. Then, the scalar operator is applied to scalarize the equivalent form of the fractional term in the approximated dispersion equation, deriving a simple and easy-to-implement pure qP-wave equation. We utilize the optical flow method to compute the direction of wave propagation, which improves the calculation accuracy of the scalar operators. Numerical experiments with representative models demonstrate that the new method has higher accuracy and better adaptability to models with strong anisotropy, complex structure, and rapid variation of the tilt angle than previous methods.","PeriodicalId":54820,"journal":{"name":"Journal of Geophysics and Engineering","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139804811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pingmin Zhang, Gang Yao, Qingqing Zheng, Xin-Yu Fang, Di Wu
An accurate pure qP-wave equation in TI media and its efficient and stable implementation are valuable for seismic imaging and inversion. Owing to the complexity of the qP-wave phase velocity expression in anisotropic media, it is difficult to construct such a pure qP-wave equation. In this paper, we combine the Taylor expansion and scalar operator methods to formulate an efficient and stable pure qP-wave equation in TI media. First, the Taylor expansion method is used to convert the square-root term into a fractional term in the qP-wave phase velocity expression. We further improve the approximation accuracy of the resulting equation by a correction technique. Then, the scalar operator is applied to scalarize the equivalent form of the fractional term in the approximated dispersion equation, deriving a simple and easy-to-implement pure qP-wave equation. We utilize the optical flow method to compute the direction of wave propagation, which improves the calculation accuracy of the scalar operators. Numerical experiments with representative models demonstrate that the new method has higher accuracy and better adaptability to models with strong anisotropy, complex structure, and rapid variation of the tilt angle than previous methods.
TI 介质中精确的纯 qP 波方程及其高效稳定的实现对地震成像和反演非常重要。由于各向异性介质中 qP 波相位速度表达的复杂性，构建这样一个纯 qP 波方程非常困难。本文结合泰勒展开法和标量算子法，提出了一种高效稳定的 TI 介质中的纯 qP 波方程。首先，我们使用泰勒展开法将 qP 波相位速度表达式中的平方根项转换为分数项。我们通过修正技术进一步提高了所得方程的近似精度。然后，应用标量算子将近似色散方程中分数项的等效形式标量化，从而得出一个简单且易于实现的纯 qP 波方程。我们利用光流方法计算波的传播方向，从而提高了标量算子的计算精度。用代表性模型进行的数值实验证明，与以前的方法相比，新方法具有更高的精度，对各向异性强、结构复杂、倾斜角变化快的模型具有更好的适应性。
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