Three-dimensional modeling of clinoforms in shallow-marine reservoirs: Part 1. Concepts and application
Three-dimensional modeling of clinoforms in shallow-marine reservoirs: Part 1. Concepts and application
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浅海油藏斜形三维建模：第 1 部分：概念与应用
DOI：
10.1306/01191513190
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发表时间：
2015
期刊：
影响因子：
3.5
通讯作者：
G. Hampson
中科院分区：
文献类型：
--
作者：
G. Graham;M. Jackson;G. Hampson
斜仿面控制着浅海准层序中相结构的各个方面，也可以在被低渗透岩性（如胶结物或泥岩）衬砌的地方作为流动的屏障或挡板。目前的储层建模技术并不适合捕捉斜形，特别是当它们数量众多、地震分辨率低于地震分辨率和/或井间难以关联时。目前，还没有建模工具可用于使用少量输入参数自动生成多个三维斜形曲面。因此，即使认识到斜形岩对流体流动的潜在影响，也很少将其纳入浅海储层模型中。本文提出了一种在由两个边界面（如三角洲瓣沉积或滨面准层序）定义的体积内生成多个斜形的数值算法。采用几何方法来构造斜仿形，将其相对于边界面的高度与描述斜仿形几何的数学函数相结合。该方法是灵活的，允许用户定义的推进方向和参数，控制的几何形状和分布的单个斜形。通过建立基于地面的三维储层模型，验证了该算法的有效性：(1)露头处的河流主导型三角洲瓣沉积（犹他州白垩纪Ferron砂岩段），以及(2)来自三角洲储层的稀疏地下数据集（挪威北海Troll油田侏罗纪Sognefjord组）。由此产生的流动模拟结果证明了将算法生成的斜地形纳入储层模型的价值，因为当它们与大面积的流动障碍相关联时，可能会显著影响油气采收率。
Clinoform surfaces control aspects of facies architecture within shallow-marine parasequences and can also act as barriers or baffles to flow where they are lined by low-permeability lithologies, such as cements or mudstones. Current reservoir modeling techniques are not well suited to capturing clinoforms, particularly if they are numerous, below seismic resolution, and/or difficult to correlate between wells. At present, there are no modeling tools available to automate the generation of multiple three-dimensional clinoform surfaces using a small number of input parameters. Consequently, clinoforms are rarely incorporated in models of shallow-marine reservoirs, even when their potential impact on fluid flow is recognized. A numerical algorithm that generates multiple clinoforms within a volume defined by two bounding surfaces, such as a delta-lobe deposit or shoreface parasequence, is developed. A geometric approach is taken to construct the shape of a clinoform, combining its height relative to the bounding surfaces with a mathematical function that describes clinoform geometry. The method is flexible, allowing the user to define the progradation direction and the parameters that control the geometry and distribution of individual clinoforms. The algorithm is validated via construction of surface-based three-dimensional reservoir models of (1) fluvial-dominated delta-lobe deposits exposed at the outcrop (Cretaceous Ferron Sandstone Member, Utah), and (2) a sparse subsurface data set from a deltaic reservoir (Jurassic Sognefjord Formation, Troll Field, Norwegian North Sea). Resulting flow simulation results demonstrate the value of including algorithm-generated clinoforms in reservoir models, because they may significantly impact hydrocarbon recovery when associated with areally extensive barriers to flow.