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Fluvial reservoir characterization and identification: A case study from Laohekou Oilfield

机译:河流储层的表征与识别-以老河口油田为例

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摘要

Finding channel sandbodies is an important task in oil and gas exploration due to the importance of fluvial reservoirs. It is difficult to describe fluvial reservoirs in detail owing to their frequent changes and serious intersections, as well as limitations of S/N ratio and seismic data resolution. Based on the Laohekou 3D data in Shengli Oilfield, we analyze the general characteristics of fluvial reservoirs in this area, from which we find that they are characterized by strong amplitudes on seismic profiles, high continuity on time slices, and low frequency in the frequency domain. In addition, a cluster of strong string-beadlike reflections was found after color processing and detailed interpretation. To understand this observation, we conduct forward modeling to explain the mechanism. This provides a new way to identify ancient channels in similar areas. By using the multi-attribute fusion and RGB display techniques, channel incision is more obvious and the characteristics of the channel structures are manifested much better. Finally, we introduce and apply multi-wavelet detection technology to identify weaker fluvial reservoir signals.
机译:由于河流储层的重要性,寻找通道砂体是油气勘探中的重要任务。由于河流储层的频繁变化和严重的交集以及信噪比和地震数据分辨率的局限性,很难详细描述河流储层。基于胜利油田老河口3D数据,分析了该地区河床储层的总体特征,发现其特征是地震剖面振幅大,时间段连续性高,频域频率低。 。此外,在进行颜色处理和详细解释后,发现一串强烈的串珠状反射。为了理解此观察,我们进行正向建模以解释该机制。这提供了一种识别相似区域中古老渠道的新方法。通过使用多属性融合和RGB显示技术,通道切口更加明显,并且通道结构的特征也得到了更好的体现。最后,我们介绍并应用多小波检测技术来识别较弱的河流储层信号。

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