Successful Application of Honey-Bee Optimization Technique in Reservoir Engineering Assisted History Matching: Case Study

M. Shams
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Abstract

This paper provides the field application of the bee colony optimization algorithm in assisting the history match of a real reservoir simulation model. Bee colony optimization algorithm is an optimization technique inspired by the natural optimization behavior shown by honeybees during searching for food. The way that honeybees search for food sources in the vicinity of their nest inspired computer science researchers to utilize and apply same principles to create optimization models and techniques. In this work the bee colony optimization mechanism is used as the optimization algorithm in the assisted the history matching workflow applied to a reservoir simulation model of WD-X field producing since 2004. The resultant history matched model is compared with with those obtained using one the most widely applied commercial AHM software tool. The results of this work indicate that using the bee colony algorithm as the optimization technique in the assisted history matching workflow provides noticeable enhancement in terms of match quality and time required to achieve a reasonable match.
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蜜蜂优化技术在油藏工程辅助历史拟合中的成功应用:实例研究
本文给出了蜂群优化算法在实际油藏模拟模型历史拟合中的现场应用。蜂群优化算法是一种受蜜蜂在寻找食物过程中表现出的自然优化行为启发的优化技术。蜜蜂在巢穴附近寻找食物来源的方式启发了计算机科学研究人员利用和应用相同的原理来创建优化模型和技术。本文将蜂群优化机制作为辅助历史匹配工作流的优化算法,应用于2004年以来的WD-X油田生产油藏模拟模型。将所得的历史匹配模型与应用最广泛的商业AHM软件工具所获得的历史匹配模型进行了比较。研究结果表明,在辅助历史匹配工作流中使用蜂群算法作为优化技术,在匹配质量和实现合理匹配所需的时间方面有明显的提高。
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