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Multicomponent seismic reservoir characterization of a steam-assisted gravity drainage (SAGD) heavy oil project, Athabasca oil sands, Alberta.

机译:阿尔伯塔省阿萨巴斯卡油砂蒸汽辅助重力排水(SAGD)重油项目的多组分地震储层表征。

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摘要

Steam-assisted gravity drainage (SAGD) is an in situ heavy oil recovery method involving the injection of steam in horizontal wells. Time-lapse seismic analysis over a SAGD project in the Athabasca oil sands deposit of Alberta reveals that the SAGD steam chamber has not developed uniformly. Core data confirm the presence of low permeability shale bodies within the reservoir. These shales can act as barriers and baffles to steam and limit production by prohibiting steam from accessing the full extent of the reservoir. Seismic data can be used to identify these shale breaks prior to siting new SAGD well pairs in order to optimize field development.;To identify shale breaks in the study area, three types of seismic inversion and a probabilistic neural network prediction were performed. The predictive value of each result was evaluated by comparing the position of interpreted shales with the boundaries of the steam chamber determined through time-lapse analysis. The P-impedance result from post-stack inversion did not contain enough detail to be able to predict the vertical boundaries of the steam chamber but did show some predictive value in a spatial sense. P-impedance from pre-stack inversion exhibited some meaningful correlations with the steam chamber but was misleading in many crucial areas, particularly the lower reservoir.;Density estimated through the application of a probabilistic neural network (PNN) trained using both PP and PS attributes identified shales most accurately. The interpreted shales from this result exhibit a strong relationship with the boundaries of the steam chamber, leading to the conclusion that the PNN method can be used to make predictions about steam chamber growth. In this study, reservoir characterization incorporating multicomponent seismic data demonstrated a high predictive value and could be useful in evaluating future well placement.
机译:蒸汽辅助重力排水(SAGD)是一种现场重油回收方法,涉及在水平井中注入蒸汽。对艾伯塔省阿萨巴斯卡油砂矿床中SAGD项目的时移地震分析表明,SAGD蒸汽室的发展并不均匀。岩心数据证实了储层中低渗透性页岩体的存在。这些页岩可充当蒸汽的屏障和挡板,并通过禁止蒸汽进入储层的全部范围来限制产量。为了优化油田开发,可以在放置新的SAGD井对之前,使用地震数据来识别这些页岩折断。为了识别研究区域中的页岩折断,进行了三种类型的地震反演和概率神经网络预测。通过将解释页岩的位置与通过延时分析确定的蒸汽室边界进行比较,可以评估每个结果的预测值。叠后反演的P阻抗结果没有包含足够的细节来预测蒸汽室的垂直边界,但是在空间意义上确实显示了一些预测价值。叠前反演的P阻抗与蒸汽室有一些有意义的相关性,但在许多关键区域,尤其是下层储层中具有误导性;通过使用同时使用PP和PS属性训练的概率神经网络(PNN)估算了密度最准确地确定页岩。该结果解释的页岩表现出与蒸汽室边界的密切关系,从而得出结论,即PNN方法可用于预测蒸汽室的增长。在这项研究中,结合多组分地震数据的储层表征具有很高的预测价值,可用于评估未来的油井布置。

著录项

  • 作者

    Schiltz, Kelsey Kristine.;

  • 作者单位

    Colorado School of Mines.;

  • 授予单位 Colorado School of Mines.;
  • 学科 Geophysics.;Petroleum Geology.
  • 学位 M.S.
  • 年度 2013
  • 页码 129 p.
  • 总页数 129
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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