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RFID (Radio Frequency Identification), which transmits control data through electronic tags in a non-contact manner, provides a new approach for efficient and low-cost remote control of oil downhole tools. However, the interference of harsh downhole environments and the high-speed movement of tags seriously affect the performance of the current downhole reader. To effectively address this issue, in this study, a novel downhole RFID reader is presented. By introducing the half-duplex communication protocol to replace the current full-duplex communication protocol in the hardware circuits of the reader, its tag recognition ability can be improved. Then, the corresponding hardware circuits and software programs are designed. Furthermore, a sparse solenoid antenna is adopted to replace the traditional tightly wound solenoid antenna, which can provide a longer reading area range to cope with the high-moving tag, and its total length and spacing parameters between adjacent coils are designed in detail. The test results show that the proposed RFID reader based on a half-duplex communication protocol can communicate with tags normally, and its sparse solenoid antenna provides significantly more tag reading times than traditional tightly wound solenoid antennas under the same antenna inductance. [ABSTRACT FROM AUTHOR]

Spectrum induced polarisation (SIP) is a frequency-domain method commonly used in electrical geophysical exploration. However, SIP is very sensitive to the signal-to-noise ratio of the signal, so noise reduction is very important. Independent component analysis can be used to reduce the noise of geophysical exploration data, but it cannot be used when the observed signal has only one dimension. In this paper, an empirical wavelet transform-independent component analysis method is proposed, which can be used for noise reduction in spectrum induced polarisation data. Firstly, the original measurement data are adaptively decomposed into a finite number of intrinsic modal functions by empirical wavelet transform, and then the intrinsic modal functions are selected to construct a virtual noise channel according to their correlation with the induced polarisation signal. Finally, the induced polarisation signal in the multi-dimensional mixed data is extracted by independent component analysis. Our experiment shows results show that this method can effectively remove noise signals and improve the signal-to-noise ratio of induced polarisation data. [ABSTRACT FROM AUTHOR]