矿山微地震全波自动定位的层析成像方法(英文)
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摘要
针对在矿山微地震监测过程中纵横波及其传播速度难以确定的难点,在球坐标系中以波动方程为基础,推导出了矿山微地震全波自动定位的层析成像的计算公式,并给出了参数选择准则,藉此可以获得微地震成像能量最大值及其对应参数。通过判断能量最大值在风险区内的位置,可以将风险区内外的微地震事件区分出来。对于能量最大值位于风险区域内的微地震事件,其震源位置和震动时间以及传播速度与能量最大值对应的坐标参数相同,能量最大值对应于震源函数相对强度;当能量最大值位于风险区域边界上时,微地震事件不在风险区域范围之内。理论模型试算和矿山实际微地震资料的应用表明:层析成像方法无需纵横波识别和传播速度假定,只要给定事故风险区域范围及其传播速度范围,便可完成微地震事件定位,是一种全波全自动定位方法,具有进一步研究价值。
For microseisimic monitoring it is difficult to determine wave modes and their propagation velocity. In this paper, we propose a new method for automatically inverting in real time the source characteristics of microseismic events in mine engineering without wave mode identification and velocities. Based on the wave equation in a spherical coordinate system, we derive a tomographic imaging equation and formulate a scanning parameter selection criterion by which the microseisimic event maximum energy and corresponding parameters can be determined. By determining the maximum energy positions inside a given risk district, we can indentify microseismic events inside or outside the risk districts. The synthetic and field examples demonstrate that the proposed tomographic imaging method can automatically position microseismic events by only knowing the risk district dimensions and range of velocities without identifying the wavefield modes and accurate velocities. Therefore, the new method utilizes the full wavefields to automatically monitor microseismic events.
For microseisimic monitoring it is difficult to determine wave modes and their propagation velocity. In this paper, we propose a new method for automatically inverting in real time the source characteristics of microseismic events in mine engineering without wave mode identification and velocities. Based on the wave equation in a spherical coordinate system, we derive a tomographic imaging equation and formulate a scanning parameter selection criterion by which the microseisimic event maximum energy and corresponding parameters can be determined. By determining the maximum energy positions inside a given risk district, we can indentify microseismic events inside or outside the risk districts. The synthetic and field examples demonstrate that the proposed tomographic imaging method can automatically position microseismic events by only knowing the risk district dimensions and range of velocities without identifying the wavefield modes and accurate velocities. Therefore, the new method utilizes the full wavefields to automatically monitor microseismic events.
引文
Billette, F., and Lambar′e, G., 1998, Velocity macro-model estimation from seismic reflection data bystereotomography: Geophys. J. Int, 135, 671 – 690.
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Geiger, L., 1912, Probability method for the determination of earthquake epicenters from the arrival time only: Bull.St. Louis Univ., 8, 60 – 71.
Lavaud , B . , Baina , R . , and Landa , E . ,2004 ,Automatic robust velocity estimation by poststackstereotomography: 74th Ann. Internat. Mtg., Soc. Expl.Geophys.,Expanded Abstracts, 2351 – 2354.
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Thurber, C. H., 1985, Nonlinear earthquake location: theory and examples: Bull. Seism. Soc. Am., 75(3), 779 – 790.
Waldhauser, F., and Ellsworth, W. L., 2000, A double-difference earthquake location algorithm: method andapplication to the Northern Hayward Fault, California:Bull. Seism. Soc. Am., 90(6), 1353 – 1368.
Xia, Y. Y., and Li., S. X., 2010, Application of polarization analysis to microseismic three-dimensional positioningbased on Matlab: Metal Mine, 405, 119 – 121.
Chalard, E., Podvin, P., Le B′egat, S., Berthet, P., and David, B., 2002, 3D stereotomographic inversion on real data set: 72nd Ann. Internat. Mtg., Soc. Expl. Geophys.,Expanded Abstracts, 946 – 948.
Chapman, C. H., 1981, Generalized radon transforms and slant stacks: Geophys, J. Royal Astronomical Society,66(2), 445 – 453
Geiger, L., 1912, Probability method for the determination of earthquake epicenters from the arrival time only: Bull.St. Louis Univ., 8, 60 – 71.
Lavaud , B . , Baina , R . , and Landa , E . ,2004 ,Automatic robust velocity estimation by poststackstereotomography: 74th Ann. Internat. Mtg., Soc. Expl.Geophys.,Expanded Abstracts, 2351 – 2354.
Lee, W. H. K., and Lahr., J. C., 1975, HYPO71: A computer program for determining hypocenter, magnitude, and firstmotion pattern of local earthquakes: U. S. Geol. Surv.Open-File Rept, 75 – 311.
Pang , H . D . , and Jiang , F. X . , 2004 , Study on nonhomogeneous material’s AE by image processingmethod: Rock and Soil Mechanics, 25(Supp), 60 – 62.
Thurber, C. H., 1985, Nonlinear earthquake location: theory and examples: Bull. Seism. Soc. Am., 75(3), 779 – 790.
Waldhauser, F., and Ellsworth, W. L., 2000, A double-difference earthquake location algorithm: method andapplication to the Northern Hayward Fault, California:Bull. Seism. Soc. Am., 90(6), 1353 – 1368.
Xia, Y. Y., and Li., S. X., 2010, Application of polarization analysis to microseismic three-dimensional positioningbased on Matlab: Metal Mine, 405, 119 – 121.
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