摘要
微震监测过程通常分为数据采集、数据处理计算、解释等步骤.所谓解释,就是研究与确定微震4D分布、微震与解释目标之间的关联、以及目标时空特性.本文讨论微破裂向量扫描(Vector Scanning,VS)的解释原则,它是VS系列文章的第五部分.前四部分分别为微地震监测技术研发进展,VS的原理、数据采集、和自动化数据处理.解释同微震监测的前期各项工作类似,它不仅涉及微震学,也很强地同地质、石油煤炭工程、力学、和统计误差等很多学科相关.应用VS的必要条件是避免、去除、和压制干扰信号以获得较小振幅的随机记录.由于微震活动可能是时间上间歇和地域上跳跃的,特别地,存在微震较弱或没有微震活动的时空地段,即使我们在解释前的步骤中,满足了上述必要条件,输出了4D破裂能量分布,在解释中仍需讨论与确立下列原则:(1)VS输出的4D破裂能量分布数据本身的可靠性;(2)地震台网周期性记录数据和残余噪声的扫描叠加干扰特性、以及已知的微震活动分布的时空特性;和(3)微震释放能量的分布与确定解释目标(如压裂裂缝带或注水汽前缘)几何及其多解的可能性;等等.
The Vector Scanning(VS)for microseismic consists of data acquisition,data processing,and interpretation,where the last one is discussed in this paper.The interpretation studies and determines the 4D distribution of microseismic,the relationship between the microseismic and interpretation target,and the target characteristic in time and space.This paper is the 5th sections in our series articles of VS,which include the development of microseismic monitoring,and the principle,data acquisition,data processing of VS.Similarly to the other steps in applying VS,the interpretation requires not only microseismology,but also geology,petroleum and coal engineering,mechanics,and statistics,etc.The necessary condition of applying VS is to achieve the random records with relatively smaller amplitudes and without such undesired signals out of the target.Due to the discontinuous feature of microseismic both in time and space,however,even though the conditions are satisfied within the previous steps,we have to discuss some problems and determine some principles in our interpretation:(1)the reliability of the scanning output data themselves;(2)The characteristics of periodic records and remains of interference from the background noise;and(3)The 4D distribution of microseismic and interpreted target,including their geometric parameters and possibly multiple solutions.
作者
梁北援
王会卿
LIANG Bei-yuan;WANG Hui-qing(GeoImage LLC,CO 80016,USA)
出处
《地球物理学进展》
CSCD
北大核心
2019年第4期1314-1322,共9页
Progress in Geophysics
关键词
微地震
向量扫描
非常规
信噪比
解释
Microseismic
Vector-processing
Unconventional
Signalover-noise
Interpretation
