Data reconstruction is a crucial step in seismic data preprocessing.To improve reconstruction speed and save memory,the commonly used three-dimensional(3D)seismic data reconstruction method divides the missing data in...Data reconstruction is a crucial step in seismic data preprocessing.To improve reconstruction speed and save memory,the commonly used three-dimensional(3D)seismic data reconstruction method divides the missing data into a series of time slices and independently reconstructs each time slice.However,when this strategy is employed,the potential correlations between two adjacent time slices are ignored,which degrades reconstruction performance.Therefore,this study proposes the use of a two-dimensional curvelet transform and the fast iterative shrinkage thresholding algorithm for data reconstruction.Based on the significant overlapping characteristics between the curvelet coefficient support sets of two adjacent time slices,a weighted operator is constructed in the curvelet domain using the prior support set provided by the previous reconstructed time slice to delineate the main energy distribution range,eff ectively providing prior information for reconstructing adjacent slices.Consequently,the resulting weighted fast iterative shrinkage thresholding algorithm can be used to reconstruct 3D seismic data.The processing of synthetic and field data shows that the proposed method has higher reconstruction accuracy and faster computational speed than the conventional fast iterative shrinkage thresholding algorithm for handling missing 3D seismic data.展开更多
【目的】随着深部资源勘探开发的重要性不断提高,对高精度地震勘探提出了新要求。针对具有强各向异性的含煤地层,传统基于各向同性的资料处理方法不再适用。【方法】提出一种基于水平横向各向同性介质(Transverse Isotropy Medium with ...【目的】随着深部资源勘探开发的重要性不断提高,对高精度地震勘探提出了新要求。针对具有强各向异性的含煤地层,传统基于各向同性的资料处理方法不再适用。【方法】提出一种基于水平横向各向同性介质(Transverse Isotropy Medium with Vertical Symmetry Axis,VTI)和方位各向异性介质(Transverse Isotropy with Horizontal Axis of Symmetry,HTI)联合处理的地震数据处理方法。首先,针对含煤地层沉积特征,分析VTI介质特点,采用高阶动校正处理,可以有效消除各向异性在大偏移距数据中引起的同相轴弯曲,保证共反射点远近道能达到同相,提高数据叠加成像质量。其次,针对构造裂隙发育特征,立足于HTI介质的方位各向异性分析,采用OVT域处理方法,通过建立方位各向异性参数场去除不同方位角差异对数据的影响。联合应用上述2种处理方法,通过制定合理的处理流程,优选关键参数,搭建一套实用的、适合目标地层的各向异性处理校正方法,解决含煤地层在复杂条件下的速度分析、叠加等问题,从而提高煤系地震数据的分辨率和解释精度。【结果和结论】实际应用结果表明,新方法获得的地震数据主频更高、频带更宽,在小构造特征识别和古地理环境刻画方面更具优势,为精细地质解释提供了有力支撑。同时也强调了对含煤地层进行各向异性处理的必要性,推动各向异性处理技术的在宽方位地震勘探中的应用。展开更多
基金National Natural Science Foundation of China under Grant 42304145Jiangxi Provincial Natural Science Foundation under Grant 20242BAB26051,20242BAB25191 and 20232BAB213077+1 种基金Foundation of National Key Laboratory of Uranium Resources Exploration-Mining and Nuclear Remote Sensing under Grant 2024QZ-TD-13Open Fund(FW0399-0002)of SINOPEC Key Laboratory of Geophysics。
文摘Data reconstruction is a crucial step in seismic data preprocessing.To improve reconstruction speed and save memory,the commonly used three-dimensional(3D)seismic data reconstruction method divides the missing data into a series of time slices and independently reconstructs each time slice.However,when this strategy is employed,the potential correlations between two adjacent time slices are ignored,which degrades reconstruction performance.Therefore,this study proposes the use of a two-dimensional curvelet transform and the fast iterative shrinkage thresholding algorithm for data reconstruction.Based on the significant overlapping characteristics between the curvelet coefficient support sets of two adjacent time slices,a weighted operator is constructed in the curvelet domain using the prior support set provided by the previous reconstructed time slice to delineate the main energy distribution range,eff ectively providing prior information for reconstructing adjacent slices.Consequently,the resulting weighted fast iterative shrinkage thresholding algorithm can be used to reconstruct 3D seismic data.The processing of synthetic and field data shows that the proposed method has higher reconstruction accuracy and faster computational speed than the conventional fast iterative shrinkage thresholding algorithm for handling missing 3D seismic data.
文摘【目的】随着深部资源勘探开发的重要性不断提高,对高精度地震勘探提出了新要求。针对具有强各向异性的含煤地层,传统基于各向同性的资料处理方法不再适用。【方法】提出一种基于水平横向各向同性介质(Transverse Isotropy Medium with Vertical Symmetry Axis,VTI)和方位各向异性介质(Transverse Isotropy with Horizontal Axis of Symmetry,HTI)联合处理的地震数据处理方法。首先,针对含煤地层沉积特征,分析VTI介质特点,采用高阶动校正处理,可以有效消除各向异性在大偏移距数据中引起的同相轴弯曲,保证共反射点远近道能达到同相,提高数据叠加成像质量。其次,针对构造裂隙发育特征,立足于HTI介质的方位各向异性分析,采用OVT域处理方法,通过建立方位各向异性参数场去除不同方位角差异对数据的影响。联合应用上述2种处理方法,通过制定合理的处理流程,优选关键参数,搭建一套实用的、适合目标地层的各向异性处理校正方法,解决含煤地层在复杂条件下的速度分析、叠加等问题,从而提高煤系地震数据的分辨率和解释精度。【结果和结论】实际应用结果表明,新方法获得的地震数据主频更高、频带更宽,在小构造特征识别和古地理环境刻画方面更具优势,为精细地质解释提供了有力支撑。同时也强调了对含煤地层进行各向异性处理的必要性,推动各向异性处理技术的在宽方位地震勘探中的应用。
