The paper shows how to construct a parent wavelet function based on Bubble function according to feature of seismic event and fault. After using Gauss function as a parent function, a 2 D wavelet analysis has been conducted from seismic data and edges information of seismic event has been detected, which became a two valued image by two valuedness, then joint component with small extension (noise) has been deleted from the picture using CB shaping filtering.

Based on the Bubble function, the seismic signal was analyzed in two dimensions by Mallat algorithm. The reflected in phase axis and fault were detected and extracted using local extreme value theory.

This paper construct wavelets based on Bubble function and decompose seismic signals by using Mallat algorithm. According to the theory of position extreme value, events and faults are detected.

The paper shows how to construct a parent wavelet function based on Bubble function according to feature of seismic event and fault. After using Gauss function as a parent function, a 2 D wavelet analysis has been conducted from seismic data and edges information of seismic event has been detected, which became a two valued image by two valuedness, then joint component with small extension (noise) has been deleted from the picture using CB shaping filtering.

Based on the Bubble function, the seismic signal was analyzed in two dimensions by Mallat algorithm. The reflected in phase axis and fault were detected and extracted using local extreme value theory.

This paper construct wavelets based on Bubble function and decompose seismic signals by using Mallat algorithm. According to the theory of position extreme value, events and faults are detected.

The paper shows how to construct a parent wavelet function based on Bubble function according to feature of seismic event and fault. After using Gauss function as a parent function, a 2 D wavelet analysis has been conducted from seismic data and edges information of seismic event has been detected, which became a two valued image by two valuedness, then joint component with small extension (noise) has been deleted from the picture using CB shaping filtering.

Based on the Bubble function, the seismic signal was analyzed in two dimensions by Mallat algorithm. The reflected in phase axis and fault were detected and extracted using local extreme value theory.

This paper construct wavelets based on Bubble function and decompose seismic signals by using Mallat algorithm. According to the theory of position extreme value, events and faults are detected.

Convergence of simplified and stabilized mixed element formats based on bubble function for the stokes problem

Two simplified and stabilized mixed element formats for the Stokes problem are derived by bubble function, and their convergence, i.

Motivated by this discovery, a new SDFEM is developed based on a special choice of the stabilization bubble function.

It is found that, irrespective of the degree of mean and the rotational pressure interpolation, the linear triangle mesh, with or without central bubble function (incompatible mode), locks when both the constraints are enforced simultaneously.

In order to satisfy the inf-sup condition we need to add to the usual piecewise quadratics a cubic bubble function.

Convergence of simplified and stabilized mixed element formats based on bubble function for the stokes problem

Two simplified and stabilized mixed element formats for the Stokes problem are derived by bubble function, and their convergence, i.

Motivated by this discovery, a new SDFEM is developed based on a special choice of the stabilization bubble function.

It is found that, irrespective of the degree of mean and the rotational pressure interpolation, the linear triangle mesh, with or without central bubble function (incompatible mode), locks when both the constraints are enforced simultaneously.

In order to satisfy the inf-sup condition we need to add to the usual piecewise quadratics a cubic bubble function.

Convergence of simplified and stabilized mixed element formats based on bubble function for the stokes problem

Two simplified and stabilized mixed element formats for the Stokes problem are derived by bubble function, and their convergence, i.

Motivated by this discovery, a new SDFEM is developed based on a special choice of the stabilization bubble function.

It is found that, irrespective of the degree of mean and the rotational pressure interpolation, the linear triangle mesh, with or without central bubble function (incompatible mode), locks when both the constraints are enforced simultaneously.

In order to satisfy the inf-sup condition we need to add to the usual piecewise quadratics a cubic bubble function.

The paper shows how to construct a parent wavelet function based on Bubble function according to feature of seismic event and fault. After using Gauss function as a parent function, a 2 D wavelet analysis has been conducted from seismic data and edges information of seismic event has been detected, which became a two valued image by two valuedness, then joint component with small extension (noise) has been deleted from the picture using CB shaping filtering. Theory and real data showed that the technique...

The paper shows how to construct a parent wavelet function based on Bubble function according to feature of seismic event and fault. After using Gauss function as a parent function, a 2 D wavelet analysis has been conducted from seismic data and edges information of seismic event has been detected, which became a two valued image by two valuedness, then joint component with small extension (noise) has been deleted from the picture using CB shaping filtering. Theory and real data showed that the technique has excellent result.

Based on the Bubble function, the seismic signal was analyzed in two dimensions by Mallat algorithm. The reflected in phase axis and fault were detected and extracted using local extreme value theory. The result shows that the method can detect a sudden change of seismic signal in different levels and reduce noise effectively.

This paper construct wavelets based on Bubble function and decompose seismic signals by using Mallat algorithm. According to the theory of position extreme value, events and faults are detected. Theory and calculation results show that the method can detect the information of sudden change in different scale seismic signals and reduce noise effectively.