Logging Signal Separation Based On Basis Pursuit

Oil is not only related to our national economy but also is an important strategic resource, and our country dependence on foreign oil consumption accounted for more than half of this severe, which threat to China's energy security. Thus, to develop oil exploration technology is not only for the sustainability and rapid development of our economy, but also for the strategic security of the energy supply.Acoustic logging signal processing technology is an powerful means for oil and other energy resources prospecting currently, but this technology still has some flaws. At home and abroad using only the information of the first wave, to obtain the formation of lithology, porosity, oil content and other key information, Usually there are some errors with the actual situation. In recent years, the Basis Pursuit(BP) algorithm is the research focus of sparse representation of the signal field, the idea of the algorithm is to find the most sparse representation of signals based on the over-complete dictionary. In other words, using as little atoms to respect the original signal as possible, then obtaining the intrinsic properties of the signal, using this method to handle the logging data based on the characteristics of acoustic logging signal, providing a new direction to get more comprehensive logging information.The signal representation and signal sparse decomposition were introduced firstly in this thesis, and then to the basic knowledge of short-time Fourier transformation for example, the defects of common time-frequency analysis method were introduced, and based on BP the sparse decomposition method was raised. Based on model signal processing, experimental results prove BP signal separation is feasible. In will acoustic logging signal model on the basis of successful separation, the BP algorithm applied to actual acoustic logging signal. According to the different conditions actual acoustic logging signal processing, the experiment proved that BP algorithm can still achieve separation. According to the analysis of separation results under different conditions, and the characteristic of well logging signal experimental proof under various conditions, the separation effect of different logging signal. Finally, the practical with noise acoustic logging signal processing, the experimental results show the BP algorithm can still will signal, but because the separation of the noise, with noise signals than separation results after pretreatment is a bit poor.