Nowadays, to obtain a better understanding of dynamic time-lapse changes, frequent seismic monitoring is necessary, although it will generate a considerable cost increase. Therefore, low-cost frequent monitoring, e.g., sparse and/or nonrepeated surveys, is desired. The simultaneous inversion-based method allows the baseline and monitor parameters to communicate and compensate with each other during inversion via constraints and helps to reduce the artifacts caused by sparse acquisition. These features make it largely independent of the used low-cost acquisition geometry and suitable for inexpensive frequent monitoring surveys. Therefore, we have used this simultaneous inversion-based method as an effective time-lapse processing tool for data sets acquired from inexpensive, semi-continuous time-lapse monitoring surveys, which are based on the so-called instantaneous 4D (i4D) technology. We choose a specific simultaneous inversion method called simultaneous joint migration inversion (S-JMI), which combines a simultaneous processing strategy with the JMI method. In i4D technology, inexpensive localized/sparse surveys, called i4D surveys, are deployed frequently between the conventional full-field surveys. This technology can be treated as a special case of changing geometries during monitoring. In this case, the simultaneous strategy allows the information of the full-field survey to compensate for the insufficient illumination of the localized/sparse i4D surveys during processing. Furthermore, we apply constraints on the reflectivity and velocity differences between the baseline and monitor vintages along the calendar-time axis called calendar-time constraints. These constraints take advantage of the feature that time-lapse effects develop (semi-)continuously along the calendar-time axis, when the monitoring surveys are deployed (semi-)continuously over calendar time. Based on a complex synthetic example, we determined that S-JMI is a promising tool to process the data sets from the semi-continuous monitoring surveys based on i4D technology. Finally, we found that the calendar-time constraints significantly improve the quality of time-lapse effects.

中文翻译：

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日历时间约束的同时联合偏移反演作为半连续调查的处理工具

如今，为了更好地了解动态时移变化，尽管需要进行频繁的地震监测，但这会带来相当大的成本增加，但它仍然是必需的。因此，需要低成本的频繁监视，例如稀疏和/或未重复的调查。基于同步的基于反演的方法允许基线和监视参数在反演期间通过约束相互通信并进行补偿，并有助于减少由稀疏采集引起的伪像。这些功能使其在很大程度上与所使用的低成本采集几何结构无关，并且适合于廉价的频繁监测调查。因此，我们已将这种基于同时反转的方法用作从廉价，半连续的时移监视调查中获取的数据集的有效时移处理工具，它们基于所谓的即时4D（i4D）技术。我们选择一种称为同时联合偏移反演（S-JMI）的特定同时反演方法，该方法将同时处理策略与JMI方法结合在一起。在i4D技术中，廉价的本地化/稀疏调查（称为i4D调查）经常在常规的全场调查之间部署。可以将此技术视为在监视过程中更改几何形状的特殊情况。在这种情况下，同步策略允许全场勘测的信息来补偿处理期间局部/稀疏i4D勘测的照明不足。此外，我们对基线和显示器年份之间沿日历时间轴的反射率和速度差异应用约束，称为日历时间约束。这些约束利用了以下特性：当监视调查在日历时间内连续（半）部署时，时延效应会沿日历时间轴连续（半）发展。基于一个复杂的综合示例，我们确定S-JMI是处理基于i4D技术的半连续监视调查中的数据集的有前途的工具。最后，我们发现日历时间约束显着提高了延时效果的质量。我们确定S-JMI是处理基于i4D技术的半连续监视调查中的数据集的有前途的工具。最后，我们发现日历时间约束显着提高了延时效果的质量。我们确定S-JMI是处理基于i4D技术的半连续监视调查中的数据集的有前途的工具。最后，我们发现日历时间约束显着提高了延时效果的质量。