首页> 外文学位 >Evaluating hydrocarbon source rock for unconventional shale oil play from seismic and well log data; Kingak Shale, North Slope, Alaska.
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Evaluating hydrocarbon source rock for unconventional shale oil play from seismic and well log data; Kingak Shale, North Slope, Alaska.

机译:根据地震和测井数据评估非常规页岩油的烃源岩运移;阿拉斯加北坡Kingak页岩。

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摘要

It has been proposed that Acoustic impedance (AI) responses can be used to estimate total organic carbon (TOC) within thick, clay rich shale. The purpose of this work is to evaluate the effectiveness of the AI inversion technique, and establish a methodology that can be applied to other basins. The Kingak Formation (lower Jurassic to early Cretaceous), located on the North Slope of Alaska, has been extensively evaluated for its unconventional potential. The Kingak is shale and is known to have greater than 30 percent clay. Because clay has ductile properties it makes it difficult to stimulate a well through hydraulic fracturing. This AI inversion technique was tested by utilizing synthetic seismograms to create an AI curve generated using The KINGDOM Software©. The synthetic seismograms were used to ensure a well log to seismic match. The synthetic seismograms also created an AI curve along the well. From these synthetic seismograms the AI value was compared to TOC values. It was from this comparison that a trend was observed that did not match the predicted trend. I believe the discrepancy observed was due to the sampling method. Based on this observation, I conclude that the method of tracking TOC with AI responses requires extremely controlled sampling methods; therefore it is not a beneficial method of revisiting old data sets in hopes of identifying new prospects.
机译:已经提出,声阻抗(AI)响应可用于估计厚的富含粘土的页岩中的总有机碳(TOC)。这项工作的目的是评估AI反演技术的有效性,并建立可应用于其他盆地的方法。位于阿拉斯加北坡的金雅克组(侏罗纪下至白垩纪早期)因其非常规潜力而受到广泛评价。 Kingak是页岩,已知粘土含量超过30%。由于粘土具有韧性,因此很难通过水力压裂来增产。通过使用合成地震图创建了使用KINGDOM Software©生成的AI曲线,对该AI反演技术进行了测试。合成地震图用于确保测井与地震匹配。合成地震图还沿着井产生了AI曲线。从这些合成地震图中将AI值与TOC值进行比较。通过该比较,观察到与预测趋势不匹配的趋势。我认为观察到的差异是由于采样方法所致。基于这一观察,我得出结论,利用AI响应跟踪TOC的方法需要严格控制的采样方法。因此,它不是重新访问旧数据集以希望发现新前景的有益方法。

著录项

  • 作者

    Leedberg, Sarah Elisabeth.;

  • 作者单位

    The University of Texas at El Paso.;

  • 授予单位 The University of Texas at El Paso.;
  • 学科 Geology.;Petroleum Geology.;Geophysics.
  • 学位 M.S.
  • 年度 2012
  • 页码 75 p.
  • 总页数 75
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 语言学;
  • 关键词

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