Automatic Scenarios Extraction from Depth Uncertainty Evaluation

Pedro Correia, J. Chautru, Y. Meric, F. Geffroy, H. Binet, P. Ruffo, L. Bazzana
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引用次数: 0

Abstract

Summary The structurally lowest point in a hydrocarbon trap that can retain hydrocarbons is called a Spill Point and characterizing these locations over a depth horizon is a common approach in trap analysis. However, a horizon is an uncertain object typically produced through a time to depth conversion procedure which might involve several different variables like time, velocity, and fault position. Each of those variables brings its own uncertainty. By using geostatistical simulations, we produce different realizations of the depth horizons and further process them individually to determine the probability of presence of reservoirs and spill points associated to highly probable reservoirs. This paper presents a methodology to achieve such results including our analysis algorithm for trap and spill point characterization. By using a case-study we demonstrate that only proper characterization of all relevant realizations in the uncertainty space show us the possible scenarios, and their impact on traps volume.
基于深度不确定度评估的场景自动提取
油气圈闭中能够留住油气的结构最低点被称为溢油点,圈闭分析中常用的方法是在深度水平面上描述这些位置。然而,水平是一个不确定的对象,通常是通过时间到深度的转换过程产生的,这可能涉及到几个不同的变量,如时间、速度和断层位置。每一个变量都有自己的不确定性。通过使用地质统计学模拟,我们产生了不同的深度层,并进一步对它们进行单独处理,以确定储层存在的概率以及与极有可能的储层相关的泄漏点。本文提出了一种方法来实现这样的结果,包括我们的陷阱和溢出点表征的分析算法。通过一个案例研究,我们证明了只有在不确定性空间中对所有相关实现的适当描述才能向我们展示可能的情景,以及它们对圈闭体积的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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