地震波传播模拟的边界元―体积元积分方程法及其近似求解

To improve the efficiency of boundary-volume integral equation technique, this paper is involved in the approximate solutions of boundary-volume integral equation technique. Firstly, based on different interpretations of the self-interaction and extrapolation operators of the resulting boundary integral equation matrix, two different hybrid BEM+Born series modeling schemes are formulated and validated through comparisons with the full-waveform BE numerical solutions for wave propagation simulation in a semicircular alluvial valley and a complex fault model respectively. Numerical experiments indicate that both the BEM+Born series modeling schemes are suitable for complex geological structures and significantly improve computational efficiency especially for the cases of high frequencies and multisource seismic survey. Then boundary-volume integral equation technique is illuminated in detail and verified by modeling wave propagation in complex media. Furthermore, the first-order and second-order Born approximate solutions for the volume-scattering waves are studied and quantified by numerical simulation in different random medium models. Finally, preconditioning generalized minimal residual method is applied to solve boundary-volume integral equation and compared with Gaussian elimination method. Numerical experiments indicate this method makes the calculations more efficient.

指数矩阵近似计算在地震波场延拓中的应用

Seismic wave field numerical modeling and seismic migration imaging based on wave equation have become useful and absolutely necessarily tools for imaging of complex geological objects. An important task for numerical modeling is to deal with the matrix exponential approximation in wave field extrapolation. For small value size matrix exponential, we can approximate the square root operator in exponential using different splitting algorithms. Splitting algorithms are usually used on the order or the dimension of one-way wave equation to reduce the complexity of the question. In this paper, we achieve approximate equation of 2-D Helmholtz operator inversion using multi-way splitting operation. Analysis on Gauss integral and coefficient of optimized partial fraction show that dispersion may accumulate by splitting algorithms for steep dipping imaging. High-order symplectic Pade approximation may deal with this problem, However, approximation of square root operator in exponential using splitting algorithm cannot solve dispersion problem during one-way wave field migration imaging. We try to implement exact approximation through eigenfunction expansion in matrix. Fast Fourier Transformation (FFT) method is selected because of its lowest computation. An 8-order Laplace matrix splitting is performed to achieve a assemblage of small matrixes using FFT method. Along with the introduction of Lie group and symplectic method into seismic wave-field extrapolation, accurate approximation of matrix exponential based on Lie group and symplectic method becomes the hot research field. To solve matrix exponential approximation problem, the Second-kind Coordinates (SKC) method and Generalized Polar Decompositions (GPD) method of Lie group are of choice. SKC method utilizes generalized Strang-splitting algorithm. While GPD method utilizes polar-type splitting and symmetric polar-type splitting algorithm. Comparing to Pade approximation, these two methods are less in computation, but they can both assure the Lie group structure. We think SKC and GPD methods are prospective and attractive in research and practice.

An empirical equation for the calculation of retention time with extrapolation of temperature in gas chromatography

An empirical equation is proposed to accurately correlate isothermal data over a wide range of temperature With the equation ln k = A* + B*/T-lambda the retention times of different solutes tested on OV-101, SE-54 and PEG 20M capillary columns have been achieved even when lambda is assigned a constant value of 1.7 Comparison with ln k = A + B/T and in k = c + d/T+ h/T-2, shows that the proposed equation is of higher accuracy and is applicable to extrapolation calculation, especially from data at high temperature to those at low temperature. Parameters A* and B* as well as A and B are also discussed. The linear correlation of A* and B* is weaker than that of A and B.