As dense seismic arrays at different scales are deployed,the techniques to make full use of array data with low computing cost become increasingly needed.The wave gradiometry method(WGM)is a new branch in seismic tomo...As dense seismic arrays at different scales are deployed,the techniques to make full use of array data with low computing cost become increasingly needed.The wave gradiometry method(WGM)is a new branch in seismic tomography,which utilizes the spatial gradients of the wavefield to determine the phase velocity,wave propagation direction,geometrical spreading,and radiation pattern.Seismic wave propagation parameters obtained using the WGM can be further applied to invert 3D velocity models,Q values,and anisotropy at lithospheric(crust and/or mantle)and smaller scales(e.g.,industrial oilfield or fault zone).Herein,we review the theoretical foundation,technical development,and major applications of the WGM,and compared the WGM with other commonly used major array imaging methods.Future development of the WGM is also discussed.展开更多
An analysis of a passive seismic method for subsurface imaging is presented in which ambient seismic noise is employed as the source of illumination of subsurface scatterers. The imaging algorithm can incorporate new ...An analysis of a passive seismic method for subsurface imaging is presented in which ambient seismic noise is employed as the source of illumination of subsurface scatterers. The imaging algorithm can incorporate new data into the image in a recursive fashion which causes image background noise to diminish over time. Under the assumption of spatially-incoherent ambient noise, an analytical expression for the point-spread function of the imaging algorithm is derived. The point-spread function （PSF） characterizes the resolution of the image, which is a function of the receiving array length and the ambient bandwidth.展开更多
盐体是具有良好气密性的地质构造,有利于油气储存,实现精细化盐体的解释极为必要。然而,不同于断层,盐体的特征较为复杂且形态差异大,常规方法易导致混淆和误判。此外,基于数据驱动的盐体识别模型在实际数据集上的泛化能力较差,因此目...盐体是具有良好气密性的地质构造,有利于油气储存,实现精细化盐体的解释极为必要。然而,不同于断层,盐体的特征较为复杂且形态差异大,常规方法易导致混淆和误判。此外,基于数据驱动的盐体识别模型在实际数据集上的泛化能力较差,因此目前在地震勘探中进行盐体的解释及可视化仍存在挑战。文章将盐体解释视为地震图像的语义分割问题,提出了基于迁移学习的上下文融合与混合注意力的智能盐体分割(Multi-path structure Mixed Attention and Transfer Optimized Net,MMTONet)方法。同时设计了一种基于盐体上下文特征融合模块,进而建立了改进注意力卷积混合的跳跃连接机制,以更好地弥补由下采样造成的信息损失,从而提高模型对盐体边界与高振幅噪声的像素级辨别能力。在此基础上,还设计了迁移学习的适配器微调策略,提升了模型在实际数据上的泛化能力。在地震数据集上的实验结果表明,MMTONet在提高分割精度和减少计算量、参数量方面均优于主流的语义分割方法。展开更多
文摘As dense seismic arrays at different scales are deployed,the techniques to make full use of array data with low computing cost become increasingly needed.The wave gradiometry method(WGM)is a new branch in seismic tomography,which utilizes the spatial gradients of the wavefield to determine the phase velocity,wave propagation direction,geometrical spreading,and radiation pattern.Seismic wave propagation parameters obtained using the WGM can be further applied to invert 3D velocity models,Q values,and anisotropy at lithospheric(crust and/or mantle)and smaller scales(e.g.,industrial oilfield or fault zone).Herein,we review the theoretical foundation,technical development,and major applications of the WGM,and compared the WGM with other commonly used major array imaging methods.Future development of the WGM is also discussed.
文摘An analysis of a passive seismic method for subsurface imaging is presented in which ambient seismic noise is employed as the source of illumination of subsurface scatterers. The imaging algorithm can incorporate new data into the image in a recursive fashion which causes image background noise to diminish over time. Under the assumption of spatially-incoherent ambient noise, an analytical expression for the point-spread function of the imaging algorithm is derived. The point-spread function （PSF） characterizes the resolution of the image, which is a function of the receiving array length and the ambient bandwidth.
文摘盐体是具有良好气密性的地质构造,有利于油气储存,实现精细化盐体的解释极为必要。然而,不同于断层,盐体的特征较为复杂且形态差异大,常规方法易导致混淆和误判。此外,基于数据驱动的盐体识别模型在实际数据集上的泛化能力较差,因此目前在地震勘探中进行盐体的解释及可视化仍存在挑战。文章将盐体解释视为地震图像的语义分割问题,提出了基于迁移学习的上下文融合与混合注意力的智能盐体分割(Multi-path structure Mixed Attention and Transfer Optimized Net,MMTONet)方法。同时设计了一种基于盐体上下文特征融合模块,进而建立了改进注意力卷积混合的跳跃连接机制,以更好地弥补由下采样造成的信息损失,从而提高模型对盐体边界与高振幅噪声的像素级辨别能力。在此基础上,还设计了迁移学习的适配器微调策略,提升了模型在实际数据上的泛化能力。在地震数据集上的实验结果表明,MMTONet在提高分割精度和减少计算量、参数量方面均优于主流的语义分割方法。
