Net erosion, the difference between the present‐day and maximum burial depths of a reference unit, may have a major impact on hydrocarbon prospectivity in a sedimentary basin. Erosion may affect all the components of a petroleum system, from source rock to reservoir to seal. In most cases, vitrinite reflectance (VR), temperature and sonic velocity data, which are often readily available, can be used to determine net erosion in a region based on the thermal and mechanical evolution of sedimentary layers with burial. This paper revisits these methods and discusses the determination of net erosion from these datasets. Furthermore, it is shown that a closer look at the data is warranted if the estimates derived from complementary VR/temperature and velocity datasets significantly diverge. Such differences can be reconciled by critically examining the datasets and the regional geology, resulting in erosion estimates from both datasets which are within 100 m of each other. Lastly, a fully automated, process‐driven method combined with multi‐objective optimization algorithms and that takes all three datasets into account is showcased while determining net erosion for three wells located in the Norwegian Barents Sea. One of the benefits of this method is that it explores a wide range of likely scenarios that would best match the different datasets. Furthermore, the method can also automatically flag datasets that are inconsistent with each other by returning an overall low fit score. These datasets can then be critically examined to determine their reliability and to arrive at a more consistent erosion estimate, reducing the error margin to about 100 m.

中文翻译：

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估算沉积盆地侵蚀的方法

净侵蚀是参考单元当前埋藏深度与最大埋藏深度之间的差，可能会对沉积盆地中的油气勘探前景产生重大影响。侵蚀可能会影响石油系统的所有组成部分，从烃源岩到储层再到密封。在大多数情况下，通常可以容易获得的镜质体反射率（VR），温度和声速数据可用于根据带有埋藏的沉积层的热演化和机械演化来确定某个地区的净侵蚀。本文将重新探讨这些方法，并讨论从这些数据集中确定净侵蚀的方法。此外，还表明，如果从互补的VR /温度和速度数据集得出的估计值明显不同，则有必要仔细查看数据。可以通过严格检查数据集和区域地质来调和这种差异，从而得出两个数据集之间的侵蚀估算值都在100 m之内。最后，展示了一种全自动，过程驱动的方法，并结合了多目标优化算法，该方法将所有三个数据集都考虑在内，同时确定了位于挪威巴伦支海的三口井的净侵蚀量。这种方法的优点之一是它探索了各种最能匹配不同数据集的可能场景。此外，该方法还可以通过返回总体低拟合得分来自动标记彼此不一致的数据集。然后可以对这些数据集进行严格检查，以确定其可靠性并得出更一致的侵蚀估算，