Simulation Research Of The Bit-Bouncing And Stick-Slip Recognition Based On Drill String Vibration Signals

In the drilling process, bit-bouncing and stick-slip are two common abnormal drilling conditions. Severe bit-bouncing and stick-slip may cause drilling accidents of drill string elements such as fracture and damage. Identifying abnormal bit-bouncing and stick-slip accurately at the first time and taking some appropriate measures to deal with can not only improve drilling efficiency and shorten the drilling cycle, but also reduce the occurrence of abnormal drilling accident. Then the overall economic efficiency can be improved. It is vital to drilling safety, speediness and high-efficiency.In order to prevent the occurrence of drilling accidents such as drilling bit abnormal and drilling tool fracture, the thesis recognize bit-bouncing and stick-slip in the drilling process. Firstly, the thesis analyzed the drill string vibration signal measured by the three-dimensional acceleration sensor. By referring to a large number of literatures, the time domain and frequency domain features of the drill string vibration signals in normal drilling, bit-bouncing and stick-slip were summarized. In addition, the characteristics of the drill string vibration signal noise and the law of its influence were analyzed. Secondly, for the problem such as white noise severely impacts on the time-domain analysis, adopting a feature extraction method which was based on Empirical Mode Decomposition(EMD). This method extracted the drill string vibration signal’s IMF energy entropy as characteristic parameters to characterize the time-domain features of bit-bouncing and stick-slip. For the problem of performing only qualitative analysis methods based on spectral analysis and wavelet analysis to recognize drilling conditions, a feature extraction method based on power spectrum analysis was adopted. According to the frequency band energy change of drill string vibration signals in bit-bouncing and stick-slip, the method located the abnormal frequency band. The characteristic frequency in the abnormal frequency band was extracted to characterize the frequency-domain feature of bit-bouncing and stick-slip. Finally, on the basis of the research and analysis of the drill string vibration signal features and extraction methods in bit-bouncing and stick-slip, a drilling condition recognition method based on empirical mode decomposition and power spectral analysis was proposed. Through threshold judgment of the drill string vibration signals IMF energy entropy and characteristic frequency, the recognition of bit-bouncing and stick-slip abnormal drilling condition was achieved.Through numerical simulations, the effectiveness of the time-domain and frequency-domain feature extraction methods which were based on EMD and power spectrum analysis was verified respectively. Besides, the effectiveness of recognizing bit-bouncing and stick-slip through drilling conditions recognition method based on EMD and power spectral analysis was analyzed.