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Research into the inversion of the induced polarization relaxation time spectrum based on the uniform amplitude sampling method 被引量:1
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作者 Pu Zhang Sheng Wang +2 位作者 Kai-Bo Zhou Li Kong Hua-Xiu Zeng 《Petroleum Science》 SCIE CAS CSCD 2016年第1期64-76,共13页
The induced polarization relaxation time spectrum(RTS) reflects the distribution of rock pore size,which is a key factor in estimating the oil or water storage capacity of strata.However,as the data acquisition and ... The induced polarization relaxation time spectrum(RTS) reflects the distribution of rock pore size,which is a key factor in estimating the oil or water storage capacity of strata.However,as the data acquisition and transmission abilities of well logging instruments are much limited due to the underground environment,it is necessary to explore suitable sampling methods which can be used to obtain an accurate RST with less sampling data.This paper presents a uniform amplitude sampling method(UASM),and compares it with the conventional uniform time sampling method(UTSM) and logarithm time sampling method(LTSM) in terms of the adaptability to different strata,RTS inversion accuracy,and stratum vertical resolution.Numerical simulation results show that the UASM can obtain high inversion accuracy of RTS with different kinds of pore size distribution formation,with high dynamic ranges of pore size,and with a small number of sampling points.The UASM,being able to adapt to the attenuation speed of polarization curve automatically,thus has the highest vertical resolution.The inversion results of rock samples also show that the UASM is superior to the UTSM and LTSM. 展开更多
关键词 relaxation automatically adaptability instruments strata estimating inversion logarithm rock normalized
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Feature Extraction of Radar Range Profiles Based on Normalized Central Moments
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作者 傅雄军 高梅国 《Journal of Beijing Institute of Technology》 EI CAS 2004年第S1期17-20,共4页
The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as ... The normalized central moments are widely used in pattern recognition because of scale and translation invariance. The moduli of normalized central moments of the 1-dimensional complex range profiles are used here as feature vector for radar target recognition. The common feature extraction method for high resolution range profile obtained by using Fourier-modified direct Mellin transform is inefficient and unsatisfactory in recognition rate And. generally speaking, the automatic target recognition method based on inverse synthetic aperture radar 2-dimensional imaging is not competent for real time object identification task because it needs complicated motion compensation which is sometimes too difficult to carry out. While the method applied here is competent for real-time recognition because of its computational efficiency. The result of processing experimental data indicates that this method is good at recognition. 展开更多
关键词 radar range profile: automatic target recognition: normalized central moment: clustering analysis: nearest neighbor classifier
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