Prediction method of acoustic scattering from elastic target with structure anechoic coating layer at low frequency

2016 ◽  
Author(s):  
Yang Sun ◽  
Junying An ◽  
Guoqing Ci ◽  
Haiting Xu
Keyword(s):  
Coating Layer ◽  
Acoustic Scattering ◽  
Low Frequency ◽  
Prediction Method

Research on Combined Prediction Model for Busy Telephone Traffic

2014 ◽  
Vol 610 ◽  
pp. 789-796
Author(s):  
Jiang Bao Li ◽  
Zhen Hong Jia ◽  
Xi Zhong Qin ◽  
Lei Sheng ◽  
Li Chen
Keyword(s):  
Prediction Model ◽  
Prediction Accuracy ◽  
Low Frequency ◽  
Prediction Method ◽  
Pso Algorithm ◽  
Frequency Component ◽  
Least Square ◽  
High Frequency Component ◽  
Support Vector ◽  
Telephone Traffic

In order to improve the prediction accuracy of busy telephone traffic, this study proposes a busy telephone traffic prediction method that combines wavelet transformation and least square support vector machine (lssvm) model which is optimized by particle swarm optimization (pso) algorithm. Firstly, decompose the pretreatment of busy telephone traffic data with mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use pso_lssvm model predict each reconfigured one. Then the busy telephone traffic can be achieved. The experimental results show that the prediction model has higher prediction accuracy and stability.

scholarly journals Prediction of Favorable Carbonate Reservoirs under Extremely Thick Salts via Poststack Facies-Controlled and Prestack Zoeppritz Equation Inversions in the Santos Basin of Brazil

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Sheng Zhang ◽  
Suoliang Chang ◽  
Handong Huang ◽  
Yinping Dong ◽  
Youyi Shen ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Large Angle ◽  
Low Frequency ◽  
Prediction Method ◽  
Approximate Equation ◽  
Carbonate Reservoirs ◽  
Linear Inversion ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Oil And Gas Exploration

Subsalt carbonate rocks in Brazil’s deepwater region have broad prospects for oil and gas exploration and development. Due to the low-frequency bandwidth of the seismic data and the poor signal quality for this kind of reservoir target, there is a demand for accurate seismic prediction methods. We employ the facies-controlled inversion using a low-pass filter matrix to ensure the accuracy of the low frequency and to improve the robustness of the inversion results. We integrated the concept of adaptive regularization constraint of the Zoeppritz equation into the generalized linear inversion theory framework, which overcomes the shortcomings of the approximate equation. Making full use of the large angle prestack seismic information, Zoeppritz equation inversion improves the accuracy of the inversion results. The application of this method in carbonate reservoirs under extremely thick salts in the Santos Basin of Brazil indicates the feasibility and practicality of the proposed integrated prediction method.

scholarly journals Simulation and analysis on low-frequency scattering characteristics of the finite cylindrical shell in shallow water

2019 ◽  
Vol 283 ◽  
pp. 03007
Author(s):  
Jinyu Li ◽  
Dejiang Shang ◽  
Yan Xiao
Keyword(s):  
Cylindrical Shell ◽  
Free Space ◽  
Acoustic Scattering ◽  
Low Frequency ◽  
Target Strength ◽  
Wave Direction ◽  
Scattering Field ◽  
Simulation Results ◽  
Finite Cylindrical Shell ◽  
Target Locations

Low-frequency acoustic scatterings from a finite cylindrical shell are numerically analyzed by FEM. The simulation results show that the acoustic-scattering field in waveguide has lots of frequency-related sidelobes, while no sidelobes exist in free space at low frequencies. The simulation also indicates that the module value in waveguide can be almost 20 dB larger than that in free space at low frequency, which is caused by the ocean boundaries. We also demonstrate that when the incident wave direction is normal to the target at low frequency, the target strength will be maximum and the distribution of the acoustic-scattering field is axisymmetric about the incident waving direction. Meanwhile, the acoustic-scattering field is also related to the impedance of the seabed, and the change of the impedance makes just a little contribution to the scattering field. Finally, the influence of different target locations is analyzed, including the targets near the sea surface, seabed and the middle region of the ocean waveguide, respectively. From simulation results, it is evident that the distribution of the acoustic-scattering field at low frequency has a little difference, which is smaller than 0.5 dB with various target locations, and the change is frequency and boundary-related.

CPI Big Data Prediction Based on Wavelet Twin Support Vector Machine

2020 ◽  
pp. 2159013
Author(s):  
Yiqing Fan ◽  
Zhihui Sun
Keyword(s):  
Support Vector Machine ◽  
Big Data ◽  
Consumer Price Index ◽  
Low Frequency ◽  
Prediction Method ◽  
Twin Support Vector Machine ◽  
Support Vector ◽  
Reconstruction Method ◽  
Data Prediction ◽  
Svm Model

In order to effectively improve the accuracy of Consumer Price Index (CPI) prediction so as to more truly reflect the overall level of the country’s macroeconomic situation, a CPI big data prediction method based on wavelet twin support vector machine (SVM) is proposed. First, the historical CPI data are decomposed into high-frequency part and low-frequency part by wavelet transform. Then a more advanced twin SVM is used to build a prediction model to obtain two kinds of prediction results. Finally, the wavelet reconstruction method is used to fuse the two kinds of prediction results to obtain the final CPI prediction results. The wavelet twin SVM model is used to fit and predict CPI index. Experimental results show that compared with the similar prediction methods, the proposed prediction method has higher fitting accuracy and smaller root mean square error.

Reservoir Prediction Under Control of Sedimentary Facies

2017 ◽  
Vol 25 (03) ◽  
pp. 1750022
Author(s):  
Xiuwei Yang ◽  
Peimin Zhu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Prediction Method ◽  
Rock Physics ◽  
Real Data ◽  
Sedimentary Facies ◽  
Seismic Inversion ◽  
Rock Properties ◽  
Reservoir Prediction ◽  
Frequency Model

Acoustic impedance (AI) from seismic inversion can indicate rock properties and can be used, when combined with rock physics, to predict reservoir parameters, such as porosity. Solutions to seismic inversion problem are almost nonunique due to the limited bandwidth of seismic data. Additional constraints from well log data and geology are needed to arrive at a reasonable solution. In this paper, sedimentary facies is used to reduce the uncertainty in inversion and rock physics modeling; the results not only agree with seismic data, but also conform to geology. A reservoir prediction method, which incorporates seismic data, well logs, rock physics and sedimentary facies, is proposed. AI was first derived by constrained sparse spike inversion (CSSI) using a sedimentary facies dependent low-frequency model, and then was transformed to reservoir parameters by sequential simulation, statistical rock physics and [Formula: see text]-model. Two numerical experiments using synthetic model and real data indicated that the sedimentary facies information may help to obtain a more reasonable prediction.

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