公开(公告)号：US20100132450A1

公开(公告)日：2010-06-03

申请号：US12623952

申请日：2009-11-23

申请人： Andrew E. Pomerantz ,  Soraya S. Betancourt ,  Shawn D. Taylor ,  Katherine A. Rojas ,  Oliver C. Mullins

发明人： Andrew E. Pomerantz ,  Soraya S. Betancourt ,  Shawn D. Taylor ,  Katherine A. Rojas ,  Oliver C. Mullins

IPC分类号： E21B49/08 ,  G06F7/48 ,  G01J5/02

CPC分类号： E21B49/00 ,  G01N33/2823

摘要： Methods for optimizing petroleum reservoir analysis and sampling using a real-time component wherein heterogeneities in fluid properties exist. The methods help predict the recovery performance of oil such as, for example, heavy oil, which can be adversely impacted by fluid property gradients present in the reservoir. Additionally, the methods help optimize sampling schedules of the reservoir, which can reduce overall expense and increase sampling efficiency. The methods involve the use of analytical techniques for accurately predicting one or more fluid properties that are not in equilibrium in the reservoir. By evaluating the composition of downhole fluid samples taken from the reservoir using sensitive analytical techniques, an accurate base model of the fluid property of interest can be produced. With the base model in hand, real-time data can be obtained and compared to the base model in order to further define the fluid property of interest in the reservoir.

摘要翻译： 使用实时组分优化石油储层分析和采样的方法，其中存在流体性质的异质性。 这些方法有助于预测油的回收性能，例如重油，其可能受到存在于储层中的流体性质梯度的不利影响。 此外，这些方法有助于优化储层的采样计划，从而降低总体费用并提高采样效率。 这些方法涉及使用分析技术来精确地预测储层中不平衡的一种或多种流体性质。 通过使用敏感的分析技术评估从储层采集的井下液体样品的组成，可以产生目标流体性质的精确基础模型。 使用基本模型，可以获得实时数据并与基本模型进行比较，以进一步定义储层中感兴趣的流体属性。