High Contrast Parameters Research Articles

Improved numerical solution of anisotropic poroelastic wave equation in microseismicity: Graphic process unit acceleration and moment tensor implementation

AbstractThe accuracy and computational efficiency of full waveform forward modelling in poroelastic media are crucial for microseismic monitoring. It enables intuitive, precise and efficient simulation of subsurface responses, thereby improving the reliability of moment tensor inversion and seismic source mechanism interpretation. Additionally, it reflects the role of fluid effects in waveform evolution. In this paper, based on the Biot mechanism, we derived the first‐order velocity–stress equation of poroelastic media and discretized the model using a rotated staggered grid. The rotated staggered grid can well adapt to anisotropic media with high contrast parameters. We provide the finite difference formula based on graphic process unit–acceleration and moment tensor and also provide the graphic process unit workflow for forward modelling of anisotropic poroelastic media. First, two models with different grid sizes were run based on single graphic process unit, 1‐thread Central Processing Unit (CPU) and 16‐thread CPU. The results show that the speedup factors are approximately 14.3 and 3.7, respectively, compared with the running time of 1‐thread CPU and 16‐thread CPU. Then, we compare and evaluate the response of three basic source mechanisms (isotropic expansion, double couple and compensated linear vector dipole) in the model. The comparison of analytical and numerical results verifies the effectiveness of the method. Furthermore, wavefield snapshots of two typical anisotropic media (vertical transversely isotropic and horizontal transversely isotropic) are analysed to correspond to different moment tensor sources. The results showed that the source mechanism does not change the isotropic and anisotropic plane and the wave travel time, but it does change the polarization amplitude of the velocity component. The attenuation of slow qP‐wave increases along with the increase of the value of viscosity. The effect of permeability on wavefield appears with the opposite effect of viscosity. Finally, the seismic waveform differences between multi‐layer elastic media and poroelastic media are compared and analysed. The results showed that the seismic wavefield and waveform of poroelastic media are more complex, the propagation speed of seismic waves is faster, but the attenuation of seismic waves is stronger.

Discrete Quasi-Helmholtz Decomposition for 3-D High-Contrast Lossy Dielectric Problems

By applying Loop-Star decomposition of basis functions to form orthogonal transformation matrices, an efficient method for the analysis of electromagnetic scattering from three-dimensional dielectric and lossy objects, especially with high-contrast parameters to the background media, has been presented in this letter. The analysis of the diagonal blocks of the impedance matrix shows that the vector potential and scalar potential subspaces scale differently in relation to the material parameters, which may have a negative effect on the conditioning of the matrix and iteration efficiency. Therefore, new equations corresponding to the exterior and interior equations have been presented, respectively, by constructing discrete quasi-Helmholtz projection operators, based on the traditional dielectric integral formulations, i.e., Poggio–Miller–Chang–Harrington–Wu–Tsai. Numerical examples show that the proposed method is effective for high-contrast lossy dielectric objects by improving the condition number and decreasing the number of iterations.

Detection of breast cancer by soft-copy reading of digital mammograms: Comparison between a routine image-processing parameter and high-contrast parameters

Recent studies have reported the clinical usefulness of the soft-copy reading of mammograms. However, image-processing parameters for soft-copy reading of digital mammograms have not been established. To compare observer performance in detecting breast cancer by soft-copy reading of digital mammograms using a routine image-processing parameter versus each of several high-contrast parameters. The mammograms of 154 breasts, including 48 abnormal breasts with breast cancer and 106 normal breasts, were examined. Cancers were classified into 34 mass-dominant cancers, 11 microcalcification-dominant cancers, two cancers showing only architectural distortion, and one cancer without abnormal findings. All mammograms were performed using a computed radiography (CR) system. Each image was processed using GA (1.2), which was the contrast parameter recommended by the manufacturer for hard-copy film, GA (1.4), GA (1.6), and GA (1.8). These images were displayed on 5-megapixel (M) liquid-crystal display monitors. Five experienced radiologists classified them into BI-RADS category 1-2 or 3-5, and were also asked to rate the images on a scale of 0 to 100 for the likelihood of the presence of masses and microcalcifications in each breast. In mass-dominant cancers of dense breast tissue, the mean sensitivities of GA (1.2), GA (1.4), GA (1.6), and GA (1.8) were 32.7, 38.2, 36.4, and 40.0, and the A(Z) values were 0.67, 0.73, 0.71, and 0.73, respectively; in microcalcification-dominant cancers, the mean sensitivities were 80.0, 74.5, 80.0, and 78.2, respectively; however, there were no significant differences among them. High-contrast parameters tended to show relatively high sensitivity and A(Z) values in the detection of masses in dense breast tissue, but relatively low sensitivity for microcalcifications.