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Smart DAS Uphole Acquisition System for Near-Surface Model Building: Results from the First Successful Field Tests

机译:近表面模型建筑的智能DAS孔孔采集系统:第一个成功的现场测试结果

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Accurate near-surface velocity models are required to correct for shallow velocity heterogeneities that can otherwise lead to the misinterpretation of seismic data, particularly in the case of low-relief structures. Here we show how a novel uphole acquisition system utilizing distributed acoustic sensing (DAS) technology can be used in a number of different ways to generate near-surface models. The novel smart DAS uphole system connects multiple shallow wells with one continuous optical fiber. The horizontal and vertical segments of the fiber allow several techniques for near-surface model building to be tested using the same system. Uphole surveys use the vertical fiber segments to make accurate, localized velocity measurements, while the directivity of the DAS fiber enables horizontal sections to be used for refraction tomography and surface-wave inversion. The smart DAS uphole acquisition system, which enables the collection of data for deep reflection imaging and near-surface characterization simultaneously, has been successfully tested for the first time. Data acquired from ten smart DAS upholes produced excellent early arrival waveform quality for picking and subsequent velocity model building. This direct velocity measurement of the near-surface can reduce uncertainty in the seismic interpretation. In addition, replacing the shallow part of the depth velocity model with the DAS uphole model resulted in significant improvements in the final depth image from topography. The directivity of DAS enables the recording of refracted events on horizontal fiber sections which have been picked as input to refraction tomography. This produces an alternative near-surface model that captures a larger volume of the subsurface. Ultimately, while the uphole velocity model is only suitable for removing long-wavelength components of near-surface variation, the refraction velocity model may allow for the correction of small-to-medium wavelength statics.
机译:准确的近表面速度模型需要校正浅速度异质性,否则可以导致地震数据的误解,特别是在低浮雕结构的情况下。在这里,我们展示了如何利用分布式声学传感(DAS)技术的新型upHole采集系统如何以多种不同的方式使用来产生近表面模型。新型智能DAS孔系统连接多个浅井,具有一个连续光纤。光纤的水平和垂直段允许使用相同的系统进行测试的近表面模型建筑的几种技术。 umhole调查使用垂直光纤段进行准确,局部速度测量,而DAS光纤的方向性使水平部分能够用于折射断层扫描和表面波反转。智能DAS upHole采集系统,它能够同时收集深度反射成像和近表面表征的数据,首次成功进行了测试。从十个智能DAS UPHOLE获取的数据产生了优异的早期到达波形质量,用于采摘和随后的速度模型建筑。近表面的直接速度测量可以减少地震解释中的不确定性。此外,用DAS孔模型替换深度速度模型的浅部分导致地形中最终深度图像的显着改进。 DAS的方向性使得能够在水平光纤部分上记录已被挑选为折射断层扫描的输入。这产生了替代的近表面模型,其捕获更大的地下体积。最终,虽然ubhole速度模型仅适用于去除近表面变化的长波长分量,但折射速度模型可以允许校正小于介质波长的静力学。

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