利用全波形声波数据进行近井眼成像

Hala Alqatari, T. Tonellot, M. Mubarak
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引用次数: 0

摘要

这项工作提出了一种全波形声波(FWS)数据集处理方法,以生成近井眼区域的高分辨率图像。该数据集是在5400英尺的近水平井中获得的。在最终图像上可以识别多个地层边界,并沿着井眼轨迹跟踪至200英尺深。我们首先提出了一个新的预处理序列来准备成像的声波数据。该序列利用常规地面地震数据处理中使用的去噪算法,去除记录数据中可能影响成像结果的无用成分。然后,我们对不同处理阶段的数据应用反向时间迁移算法,以评估主要处理步骤对最终图像的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-Borehole Imaging Using Full-Waveform Sonic Data
This work presents a full waveform sonic (FWS) dataset processing to generate high-resolution images of the near-borehole area. The dataset was acquired in a nearly horizontal well over a distance of 5400 feet. Multiple formation boundaries can be identified on the final image and tracked at up to 200 feet deep, along the wellbore's trajectory. We first present a new preprocessing sequence to prepare the sonic data for imaging. This sequence leverages denoising algorithms used in conventional surface seismic data processing to remove unwanted components of the recorded data that could harm the imaging results. We then apply a reverse time migration algorithm to the data at different processing stages to assess the impact of the main processing steps on the final image.
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