Quantitative prediction of channel sand bodies based on seismic peak attributes in the frequency domain and its application

The boundary identification and quantitative thickness prediction of channel sand bodies are always difficult in seismic exploration.We present a new method for boundary identification and quantitative thickness prediction of channel sand bodies based on seismic peak attributes in the frequency domain.Using seismic forward modeling of a typical thin channel sand body,a new seismic attribute-the ratio of peak frequency to amplitude was constructed.Theoretical study demonstrated that seismic peak frequency is sensitive to the thickness of the channel sand bodies,while the amplitude attribute is sensitive to the strata lithology.The ratio of the two attributes can highlight the boundaries of the channel sand body.Moreover,the thickness of the thin channel sand bodies can be determined using the relationship between seismic peak frequency and thin layer thickness.Practical applications have demonstrated that the seismic peak frequency attribute can depict the horizontal distribution characteristics of channels very well.The ratio of peak frequency to amplitude attribute can improve the identification ability of channel sand body boundaries.Quantitative prediction and boundary identification of channel sand bodies with seismic peak attributes in the frequency domain are feasible.

Adaptive bands filter bank optimized by genetic algorithm for robust speech recognition system

Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition systems.However,the problem of the design of optimized filter banks that provide higher accuracy in recognition tasks is still open.Owing to spectral analysis in feature extraction,an adaptive bands filter bank (ABFB) is presented.The design adopts flexible bandwidths and center frequencies for the frequency responses of the filters and utilizes genetic algorithm (GA) to optimize the design parameters.The optimization process is realized by combining the front-end filter bank with the back-end recognition network in the performance evaluation loop.The deployment of ABFB together with zero-crossing peak amplitude (ZCPA) feature as a front process for radial basis function (RBF) system shows significant improvement in robustness compared with the Bark-scale filter bank.In ABFB,several sub-bands are still more concentrated toward lower frequency but their exact locations are determined by the performance rather than the perceptual criteria.For the ease of optimization,only symmetrical bands are considered here,which still provide satisfactory results.

Effects of Bearing Type on Seismic Response of Small Base Isolation System Using Friction Bearings

In this study, dynamic characteristics of the small base isolation system using new friction bearings are investigated by excitation experiment, and compared to other one using previous bearings. Peak amplitude of the acceleration response waves on the small base isolation system is decreased to about 10%-25% compared to the input waves. Also root mean square amplitude is decreased to about 10%-40%. In case of the ball embedded a cylindrical sponge, the new bearing, the damping ratio increases with increasing width of the cylindrical sponge. The natural frequency does not change. On the other hand, in case of the marble plate that is previous bearing, the damping ratio increases with increasing curvature radius of the marble plate, the natural frequency also increases. Therefore, the small base isolation system using new friction bearing provides better performance. The responses of the base isolation system indicate nonlinier effects by friction force.

The Improvement of ECG Parameter Estimation Obtained by Up-sampling 500 Hz Data

Nowadays, numerous commercial electrocardiographs(ECG) have500 Hz output sampling rate, i.e., 2 ms corresponding sampling interval. Medical workers who have no background of signal processing may worry about whether such low 500 Hz output sampling rate data could support high-precision estimation of electrocardiogram parameters by being up-sampled. With intention to clarify the problem to the medical workers, this paper takes some simulating experiment to illustrate it.The experiment chose the RR interval and R peak amplitude as representative parameters to be estimated. The obtained results were as follows: for RR interval parameter,its estimation error can be lowered to below 0.3 ms by up-sampling; for R peak amplitude, its estimation error can be reduced to below 2.0 μV by up-sampling. It is believed that other ECG parameter estimation can also be improved similarly by up-sampling 500 Hz data.