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Estimation of prospective locations in mature hydrocarbon producing areas

机译:估算成熟烃产区的预期位置

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Abstract: Kalman filtering is a methodology that has demonstrated great potential for solving a large number of problems in many areas. It has so far had its greatest success in the areas of control theory and process control, but is a method and it is not limited to this area. There are a great number of areas within oil and gas exploration where it can prove to be of great success. Of particular interest is an aid to exploration in mature hydrocarbon provinces. The identification of remaining reserves of hydrocarbons in stratigraphic traps in the world's mature hydrocarbon provinces is a difficult task. Often these traps are small compounding identification. A subset of this general problem is the appropriate location of new wells in known producing areas. The task reported on herein has been to complete an uncompleted pattern of successful and unsuccessful wells. Two dimensional Kalman filter and interpolation theory is used to estimate successful and unsuccessful well locations. Based on a map of the known well locations, the image representing the estimated pattern is completed. The majority of image pixels in this particular case will be unknown, and not just distorted off of its original value by noise. Examples are detailed and discussed.!
机译:摘要:卡尔曼滤波是一种已显示出在许多领域解决大量问题的巨大潜力的方法。到目前为止,它已经在控制理论和过程控制领域取得了最大的成功,但是它是一种方法,并且不限于此领域。石油和天然气勘探领域有很多领域可以证明是非常成功的。特别令人感兴趣的是对成熟油气省的勘探的帮助。在世界上成熟的碳氢化合物省份,识别地层圈闭中的碳氢化合物剩余储量是一项艰巨的任务。这些陷阱通常都是很小的复合识别。这个普遍问题的一个子集是在已知产油区中适当安置新井。本文报道的任务是完成成功和失败的井的未完成模式。二维卡尔曼滤波和插值理论用于估计成功和不成功的井位。基于已知井位置的地图,完成了代表估计模式的图像。在这种特殊情况下,大多数图像像素都是未知的,而不仅仅是由于噪声而偏离其原始值。示例已详细讨论。

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