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本帖最后由 Joseph 于 2014-9-19 19:08 编辑
此文引用的书籍请参考：
http://sunpetro.cn/forum.php?mod ... 63463&extra=&page=1
[摘者附言：此译文不严谨，需要对照原文来参考，“随机模拟”其实是“随机模型”，有些明显误译用红色标示请阅读原文。不过描述的情形是大约二十几年前的欧美，看看现在欧美开发地质家已经必须要求熟练掌握地质统计学、地质建模和不确定分析等技术，我们年轻的同业者应该能够看到希望了。这样的历史，他们也走了十几年，所以我们更应该有理由等待一段时间来证明我们是这个领域的践行者。不是吗？]
一、作为艺术的随机模拟 通常人们没有定量化地使用随机模拟，没有用随机模拟方法计算油气的体积或流体的流量。即使仅仅将随机模拟的结果视为“艺术品”，用作研究中心墙壁上的装饰品而不予以重视；但是它仍具有一定的作用、它可以用作更好的技术工作的摧化剂。在工业界，人们已非常熟悉简单的层状蛋糕的地层和延伸到下口井或通常在中途发生尖灭的岩性单元以及显示地形既优雅又乎缓起伏的等厚图。但常常很难认识到井间的复杂性远远地超出传统的储集层模拟所描绘的。当随机模拟方法用于解决简单储集层时，它们常常表现出最大的影响力。当熟悉储集层模拟传统方法的工程师们和科学家们首次看到某种随机方法的结果时，他们的第一反应经常是既惊讶又怀疑。惊讶的是由于用随机模拟作出的横剖面比所熟悉的横剖面要复杂得多，怀疑的是因为随机模拟给出了许多个实现，而他们却比较习惯于考虑一个“最好”的模型。当他们意识到储集层的许多个实现看上去具有相似的特征且都在一定程度上忠实于井的信息时，最初的惊讶和怀疑常常被好奇所代替。
一旦随机模拟的结果以横剖面的形式表达出来，并将其悬挂在会议室的墙壁上时，它们常常就成为争论的焦点，人们指着某个具体特征，并且认为这样的特征不可能存在。他们辩解的理由范围很广，从基于沉积环境的地质争论到基于地震地层学的地球物理争论，再到基于试井成果的油藏工程争论。在所有这些情况下，简单地说随机模拟的好处就是集中了许多专家的观点以及如何建立模型，并提出—个改进后的储集层模型。是将新的、更清晰的认识用于改进随机模型，还是将其用于对大多数的传统模型作智能型适应，最初的随机模型仍会在储集层模型评价方面发挥重要作用。
Stochastic Models as Art
Stochastic models often are not used quantitatively; no hydrocarbon volumes or fluid flows are calculated from them. Even though such stochastic “artwork” is often dismissed as mere decoration for the walls of research centers, it may still have a useful role to play as a catalyst for better technical work. In an industry that has become too familiar with simple layer-cake stratigraphy, lithologic units that either continue to the next well or conveniently pinch out halfway, and contour maps that show graceful and gentle undulations, it is often difficult to get people to realize that there is much more interwell complexity than traditional reservoir models can portray. Stochastic models often have their greatest influence when they are used to challenge a complacent belief in the simplicity of a reservoir.When engineers and scientists familiar with the traditional approaches to reservoir modeling first see the results of a stochastic approach, their initial reactions often are surprise and skepticism. Their surprise is due to the fact that cross sectionsthrough stochastic models are much more visually complex than the cross sections they are familiar with; their skepticism is due to the fact that stochastic models provide many different renditions and they are accustomed to thinking of one “best” model. The initial surprise and skepticism often give way to curiosity as they realize that these many alternate renditions of the reservoir share a similar visual character and all somehow manage to honor the information at the well locations.
Once the results of a stochastic model are rendered on cross sections and hung on the walls of a meeting room, they often become a lightning rod for criticism when people point to a specific feature and argue that such a feature cannot exist. Their reasons range from geologic arguments based on depositional environment to geophysical arguments based on seismic stratigraphy to engineering arguments based on well test information. In all of these situations, the benefit of the stochastic model simply may be to focus the views and opinions of a wide variety of experts and, in so doing, to point to an improved reservoir model. Whether this new and clearer understanding is used to improve the stochastic model or whether it is used to make intelligent adaptations to more traditional models, the initial stochastic model still has played an important role in the evolution of an appropriate reservoir model.
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