1 Localization and Discrimination of Microseismic/AE Sources …
7
1.2.4 Source Localization Method for Hole-Containing
Structures
A new localization method based on the improved A* search algorithm without
premeasured velocity (ALM) was proposed for source localization in complex
structures. The main steps of ALM are listed as follows.
• Firstly, meshing the location region to the grid and using the grid node P i jk with
the digits 0 or 1 to represent the shape.
• Secondly, searching the fastest wave path between each sensor and each node
by the improved A* search algorithm. The improved A* search algorithm was
based on the A* search algorithm [17, 18] to establish more connection with more
adjacent layer nodes to search the wave path more effectively.
• Thirdly, the coordinates of the kth sensor S k are recorded as (x k , y k , z k ). The
arrivals of the AE event is set as t
k
0 . Calculating the actual time difference of the
two different sensors S l and S m , denoted by t
lm
0 .
• Finally, the D i jk is introduced to describe the degree of deviation of the point P i jk
from the unknown AE source based on the principle of the least square method.
Therefore, the XYZ coordinate corresponding to the minimum D xyz value can be
considered as the coordinate of the AE source.
Compared with the 2D localization method, the 3D localization method needs to
link more nodes in the second step to reduce the location errors and ensure that the
location accuracy meets the high requirements in the complex structure. The number
of the linked nodes reaches 342 in the 3D localization method when the current node
is connected to the adjacent 3 layers, while that in the 2D localization method is only
48. Since the ALM can bypass the empty area, the localization accuracy of the ALM
is much higher than the commonly used methods.
1.3 Source Discrimination and Mechanism Inversion
1.3.1 Discrimination of Microseismic Events and Blasts
Presently, the discrimination for microseismic events and blasts mainly relies on
manual identification, which results in a huge amount of work, high labor costs, and
delayed identification. At the same time, there will also be an error in determining
the source location due to the difference of individual experience, which seriously
restricts the real-time prevention and control of large magnitude microseismic events.
Aiming at solving the problem, a set of classification methods are proposed, as shown
in Fig. 1.3.
7
1.2.4 Source Localization Method for Hole-Containing
Structures
A new localization method based on the improved A* search algorithm without
premeasured velocity (ALM) was proposed for source localization in complex
structures. The main steps of ALM are listed as follows.
• Firstly, meshing the location region to the grid and using the grid node P i jk with
the digits 0 or 1 to represent the shape.
• Secondly, searching the fastest wave path between each sensor and each node
by the improved A* search algorithm. The improved A* search algorithm was
based on the A* search algorithm [17, 18] to establish more connection with more
adjacent layer nodes to search the wave path more effectively.
• Thirdly, the coordinates of the kth sensor S k are recorded as (x k , y k , z k ). The
arrivals of the AE event is set as t
k
0 . Calculating the actual time difference of the
two different sensors S l and S m , denoted by t
lm
0 .
• Finally, the D i jk is introduced to describe the degree of deviation of the point P i jk
from the unknown AE source based on the principle of the least square method.
Therefore, the XYZ coordinate corresponding to the minimum D xyz value can be
considered as the coordinate of the AE source.
Compared with the 2D localization method, the 3D localization method needs to
link more nodes in the second step to reduce the location errors and ensure that the
location accuracy meets the high requirements in the complex structure. The number
of the linked nodes reaches 342 in the 3D localization method when the current node
is connected to the adjacent 3 layers, while that in the 2D localization method is only
48. Since the ALM can bypass the empty area, the localization accuracy of the ALM
is much higher than the commonly used methods.
1.3 Source Discrimination and Mechanism Inversion
1.3.1 Discrimination of Microseismic Events and Blasts
Presently, the discrimination for microseismic events and blasts mainly relies on
manual identification, which results in a huge amount of work, high labor costs, and
delayed identification. At the same time, there will also be an error in determining
the source location due to the difference of individual experience, which seriously
restricts the real-time prevention and control of large magnitude microseismic events.
Aiming at solving the problem, a set of classification methods are proposed, as shown
in Fig. 1.3.