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An integrated method for seismic velocity modeling based on collocated cokriging

机译:基于并置录音的地震速度建模综合方法

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The modeling results of seismic velocity (VP and VS) largely influence the accuracy of seismic inversion and depth migration. In the process of velocity modeling, seismic attributes and sedimentary facies are very important as covariates, especially sedimentary facies, which affect geological conditions in the whole area. Because of the sparse distribution of well loggings in the early stage of petroleum exploration, integrating multiple variables to control the modeling process becomes essentially critical. The conventional cokriging method and the two-step modeling approach, which do not use sedimentary facies as quantitative data, are not able to introduce enough information to enhance the quality of a velocity model. The proposed collocated cokriging with sedimentary facies (CCK with sedimentary) method directly uses the digital model of sedimentary facies as a covariate to calculate the velocity results. CCK with sedimentary integrates three kinds of data, logging, seismic attributes, and sedimentary facies, where the logging data is the primary variable, and seismic attributes and sedimentary facies are the two covariates. Field examples indicated that the velocity models of the P-wave for CCK with sedimentary is better than that for collocated cokriging (CCK), and the interval velocity has been proven to be a better seismic attribute of the kriging method. The same is true for the VS results. The velocity models obtained by CCK with sedimentary contain less abnormal values with high continuity and stability. Therefore, CCK with sedimentary has been proven to be an effective method to calculate velocity distributions from seismic data, and its applicability for other elastic properties needs further research.
机译:地震速度(VP和VS)的建模结果在很大程度上影响了地震反转和深度迁移的准确性。在速度建模过程中,地震属性和沉积相对于协变量非常重要,特别是沉积相,影响整个地区的地质条件。由于石油勘探早期阶段的井测井中的稀疏分布,集成了多个变量来控制建模过程变得基本上是至关重要的。传统的Cokriging方法和不使用沉积相作为定量数据的两步建模方法,不能引入足够的信息以增强速度模型的质量。拟议的与沉积相的并置COKRIGIGE(CCK具有沉积)方法直接使用沉积相的数字模型作为协变量计算速度结果。 CCK与沉积物整合了三种数据,伐木,地震属性和沉积相,其中日志记录数据是主要变量,地震属性和沉积相是两个协变量。字段示例表明,具有沉积物的CCK的P波的速度模型优于链接焦化(CCK),并且已经证明了间隔速度是Kriging方法的更好地震属性。对于VS结果也是如此。 CCK具有沉积物获得的速度模型包含具有高连续性和稳定性的较少的异常值。因此,已被证明具有沉积物的CCK是计算地震数据的速度分布的有效方法,其对其他弹性特性的适用性需要进一步研究。

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