权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Knowledge to application: meta data approaches to improved geological model conditioning in petroleum industry workflows

知识应用：用于改进石油工业工作流程中地质模型调节的元数据方法

基本信息

批准号：
NE/M007324/1
负责人：
William McCaffrey
金额：
$ 8.81万
依托单位：
University of Leeds
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FM007324%2F1
关键词：
Knowledge application meta data approaches

项目摘要

Sedimentary rocks are commonly highly variable internally. For example when rivers leave behind sediments, channel deposits may sit within floodplain deposits, such that ribbons of sand become encased within a muddy background. To describe and study sedimentary systems such as these, sedimentologists use descriptive terms such as "channel" or "floodplain" to recognise building blocks that together stack up to build a rock volume. These building blocks are called architectural elements. Geologists also recognise that architectural elements may themselves stack up in organised patterns, and such organised patterns of elements can be placed in hierarchical arrangements. For example, channels may stack together to form channel complexes, and channel complexes may build channel complex sets. This hierarchical descriptive approach can work in the deposits from a wide range of sedimentary environments: e.g., rivers (fluvial rocks), shallow seas (shallow marine rocks) and deep seas (deep marine clastic rocks). Sedimentary systems built from pre-existing particles (such as sand grains, or mud grains, that might make sand- or mud-stones) are known as clastic systems. In the right circumstances, such systems may form hydrocarbon reservoirs. This happens when the sediment is buried, but with connected pores between the grains still open (i.e., without minerals growing in the pores during burial to seal the rock). If oil or gas migrates into connected pore spaces, but cannot migrate out, because the rock above is sealed in some way, the hydrocarbon filled rock volume may have the potential to be an oil or gas reservoir, if there is enough hydrocarbon in place, and the predicted flow rates are high enough.To predict whether a known hydrocarbon accumulation might make an economic reservoir - i.e., be worth developing - oil companies model its behaviour as a possible field. They may first build a sedimentary model, recognising different architectural elements and the way they are stacked together. They will then account for any deformation the rock experienced during or post deposition. Finally they will simplify this geological model to build a reservoir simulation model, in which the performance of the possible field can be predicted. Ideally the company would build the geological model using seismic reflection data that showed the basic geology (this is a remote sensing technique that builds 2- or 3D images of the subsurface geology based on processing the reflections of sound waves sent into the ground). However, the resolution of these techniques is usually not good enough to show exactly what the subsurface geology is like, and the companies have to use models to fill in the data they can't see directly. To build these models, companies commonly use computer techniques to generate synthetic geology at the finer scale, using algorithms that randomly generate patterns of architectural elements based upon modelling rules. However, problems often arise because these rules are not always based upon the way the geology actually tends to stack together in particular settings. The database approach is a new way of determining what these organisational rules should be. They provide data that are more reliable, because the data are all compiled from real world examples of geology. We have already applied this approach to rocks deposited by rivers, and in the deep sea, and many companies have used the results in their own modelling. However, the approach hasn't been tried yet for shallow marine rocks - and that's what we aim to do in this project. Shallow marine rocks host many oil and gas fields, so if we can improve the modelling of such fields, we'll have a significant impact upon the efficiency of the companies who use the technique, as we'll reduce the uncertainly they commonly experience when deciding whether or not to develop a field, and how to extend the lives of fields that are already producing.

沉积岩在内部通常是高度可变的。例如，当河流留下沉积物时，河道沉积可能位于泛滥平原沉积中，从而使沙带被包裹在泥泞的背景中。为了描述和研究这样的沉积体系，沉积学家使用“河道”或“泛滥平原”等描述性术语来识别堆积在一起形成岩石体积的积木。这些构建块称为建筑元素。地质学家还认识到，建筑元素本身可能会以有组织的模式堆积在一起，这种有组织的元素模式可以按等级安排放置。例如，通道可以堆叠在一起以形成通道复合体，并且通道复合体可以构建通道复合体集合。这种分层描述方法适用于各种沉积环境中的矿床：例如河流(河流相岩石)、浅海(浅海岩石)和深海(深海碎屑岩)。由预先存在的颗粒(如砂粒或泥粒，可能形成砂岩或泥岩)建造的沉积体系称为碎屑体系。在适当的情况下，这样的系统可能会形成油气藏。当沉淀物被埋藏，但颗粒之间的连通孔隙仍然开放时(即，在埋藏过程中没有矿物生长来密封岩石)，就会发生这种情况。如果石油或天然气运移到连通的孔隙空间，但由于上面的岩石以某种方式封闭而无法运移出去，那么充满碳氢化合物的岩石体积可能会成为石油或天然气储集层，如果有足够的碳氢化合物存在，并且预测的流速足够高。为了预测已知的碳氢化合物聚集层是否可能成为经济储集层--即是否值得开发--石油公司将其行为建模为可能的油田。他们可能会首先建立一个沉积模型，识别不同的建筑元素以及它们堆叠在一起的方式。然后，它们将解释岩石在沉积过程中或沉积后经历的任何变形。最后，他们将简化这个地质模型，建立一个油藏模拟模型，在这个模型中可以预测可能的油田的动态。理想情况下，该公司将使用显示基本地质的地震反射数据来建立地质模型(这是一种遥感技术，基于对进入地面的声波的反射进行处理，建立地下地质的2-或3D图像)。然而，这些技术的分辨率通常不足以准确显示地下地质是什么样子，公司不得不使用模型来填充他们无法直接看到的数据。为了建立这些模型，公司通常使用计算机技术来生成更精细的合成地质，使用基于建模规则随机生成建筑元素模式的算法。然而，问题经常出现，因为这些规则并不总是基于在特定环境中地质实际上倾向于堆积在一起的方式。数据库方法是确定这些组织规则应该是什么的一种新方法。它们提供了更可靠的数据，因为这些数据都是从真实的地质学例子中汇编而来的。我们已经将这种方法应用于河流沉积的岩石和深海中，许多公司在他们自己的模型中使用了这些结果。然而，这种方法还没有被尝试用于浅海岩石--这就是我们在这个项目中要做的。浅层海相岩石拥有许多油气田，因此，如果我们能够改进这类油田的建模，我们将对使用该技术的公司的效率产生重大影响，因为我们将减少他们在决定是否开发油田以及如何延长已在生产的油田的寿命时经常遇到的不确定性。