A Signal Reconstruction Method for Memory-Type Transient Electromagnetic Detection Systems in Horizontal Wells

Dang Bo, Peng Mengmeng, Ren Bowen, Yang Ling
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Abstract

A signal reconstruction method for memory-type transient electromagnetic detection systems based on empirical mode decomposition (EMD) was proposed in this study to tackle with the large volume of data saved by the electromagnetic flaw detector in horizontal wells. First, based on the underground transient electromagnetic detection model, sparse representation was performed for the depth-dimensional transient electromagnetic detection signal, which was then projected through a Gaussian random measurement matrix. Next, a depth-directional observation matrix was built to reconstruct the underground transient electromagnetic signal. In addition, in order to improve the reconstruction precision, the baseline wander of underground transient electromagnetic detection signal was removed through EMD, the key information of casing pipe was described using intrinsic mode functions (IMFs), and the IMFs were constructed using the above compressive sensing algorithm. It is verified through the measured data that the compressed signal after the baseline removal can be recovered at a higher probability, and moreover, it can accurately describe the forms of casing pipes and effectively remit the storage problem of large data volume faced by the memory-type electromagnetic flaw detectors in horizontal wells.
水平井记忆型瞬变电磁探测系统的信号重构方法
针对水平井电磁探伤仪存储数据量大的问题,提出了一种基于经验模态分解(EMD)的记忆型瞬变电磁检测系统信号重构方法。首先,基于地下瞬变电磁探测模型,对深维瞬变电磁探测信号进行稀疏表示,然后通过高斯随机测量矩阵进行投影;其次,建立深度定向观测矩阵,重建地下瞬变电磁信号。此外,为了提高重建精度,通过EMD去除地下瞬变电磁探测信号的基线漂移,利用内禀模态函数(IMFs)描述套管的关键信息,并利用上述压缩感知算法构建了内禀模态函数。实测数据验证了去基线后的压缩信号能够以较高的概率恢复,并且能够准确地描述套管的形态,有效地解决了水平井记忆型电磁探伤仪面临的数据量大的存储问题。
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