As a particular kind of detection technology under weak magnetization, metal magnetic memory testing is very likely to be affected by external factors in the detecting process, which may lead to incorrect results. In order to minimize the negative influence of interrupting signals and improve the detection accuracy, this paper adopted the enhanced metal magnetic memory testing method to preliminarily increase the signal-to-noise ratio (SNR) of the detection signal and then compares the denoising effects of wavelet threshold denoising method, empirical mode decomposition (EMD) denoising method, EMD-wavelet threshold denoising method, ensemble EMD (EEMD), complementary EEMD (CEEMD), variational mode decomposition (VMD), local mean decomposition (LMD) and empirical wavelet transform (EWT) on the detection signal and the gradient signal respectively. The results show that the enhanced metal magnetic memory testing method can significantly increase the SNR of the obtained signal and cannot improve the SNR of a gradient signal which is generated from the obtained signal. The different denoising methods can further boost the SNR and improve the detection accuracy of the obtained signal and the gradient signal. Among the eight signal processing methods, wavelet threshold, EMD and its improved methods are more applicable in the denoising of enhanced metal magnetic memory testing signals. The Wavelet threshold denoising, EMD-wavelet threshold denoising and EEMD denoising all have good denoising effects, and the denoising results to the same signal are analogous.

Conventional downhole traction robots only provide axial traction, while coiled tubing drilling (CTD) robots must not only overcome the axial force but also overcome the reaction torque generated by the drill bit breaking the rock. Therefore, the tooth profile of the friction block of the conventional downhole traction robot cannot achieve effective support under the simultaneous action of the axial load and circumferential load. In this paper, based on the actual reaction torque conditions generated by CTD, a mechanical model of the friction block teeth of the CTD robot under the conditions of axial traction and reverse torque is established. This reveals the influence of different tooth slope angles, axial-included angles and friction coefficients on the mechanical properties. It provides guidelines for the design of the inclination of the tooth slope, the axial angle of the tooth and the friction coefficient of the friction block of the CTD robot. It has scientific and engineering significance for the promotion of downhole robots in drilling engineering.

Conventional design method of the downhole tractor is based on cementing casing, which is only suitable for the smooth wellbore. For the open hole well, the conventional downhole tractor has poor adaptability and even cannot work normally. In order to improve the obstacle surmounting performance of the wheeled downhole tractor (WDR) and expand the application range of the WDR, a double push rod-double spring support adjustment mechanism (DPRDSSAM) is proposed in this paper. Meanwhile, the proposed DPRDSSAM also needs to increase the traction force and the stability of the WDR in the open hole well. Kinematic simulation numerical models of both conventional support adjustment mechanism and the DPRDSSAM are established. The two models comprehensively considere the influence of different obstacle forms and sizes on the obstacle surmounting performance of the tractor. The influence of different obstacle forms on the obstacle surmounting performance of DPRDSSAM and single push rod support adjustment mechanism (SPRSAM) is analyzed. Results show that the DPRDSSAM has better obstacle surmounting performance than the SPRSAM. The DPRDSSAM can effectively promote further research and application of the tractor in the open hole well.