ЭФФЕКТЫ ЖУПАНОВСКОГО ЗЕМЛЕТРЯСЕНИЯ 30 января 2016 г., Mw=7.2, В ИЗМЕНЕНИЯХ УРОВНЯ ВОДЫ В СКВАЖИНАХ ЮЗ-5 И Е-1, КАМЧАТКА
ЭФФЕКТЫ ЖУПАНОВСКОГО ЗЕМЛЕТРЯСЕНИЯ 30 января 2016 г., Mw=7.2, В ИЗМЕНЕНИЯХ УРОВНЯ ВОДЫ В СКВАЖИНАХ ЮЗ-5 И Е-1, КАМЧАТКА
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30 января 2016 г., Mw=7.2, ИЗМЕНЕНИЯХ УРОВНЯ ВОДЫ В СКВАЖИНАХ ЮЗ-5 И Е-1, КАМЧАТКА
DOI：
10.5800/gt-2017-8-4-0321
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Geodynamics Tectonophysics
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文献类型：
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作者：
S. V. Boldina;G. Kopylova;Geodynamics Tectonophysics
本文描述了2016年1月30日朱帕诺夫斯基地震（M w =7.2，Н =180 km）堪察加半岛YuZ-5井和E-1井水位变化情况。从朱帕诺夫斯基地震震中到E-1井和YuZ-5井的距离分别为70和80公里。玉Z-5井地震波到达后45分钟内水位上升9.4厘米。这种效应是由震源破裂期间含水岩石的体积压缩导致的同震水位上升和地震冲击期间井筒附近流体压力的脉冲增加共同引起的。我们估算了同震水位上升幅度（D h =7.3 cm）和含水岩石体积压缩产生的应变值，这与井深500 m区域同震体积变形的估算值一致：D 1 = –4.5×10 –8 。该估计基于均质各向同性弹性半空间中的位错源模型以及朱帕诺夫斯基地震震源机制的参数。地震发生后，水位下降了三个月，下降幅度约为40厘米。为了估计井对压降源敏感度的半径，我们使用了水位下降模型，该模型是由于地震后含水岩石滤过性能的改善而导致距井一定距离的含水层中的压降导致的。井敏感度的估计半径 R 为 450 m。在朱帕诺夫斯基地震发生前的3.5个月内，观察到水位上升了约20厘米，这与长期观测显示的水位平均季节性变化相比是反常的。我们认为，这种水位上升是在地震准备过程中发生的，可以看作是地震准备过程中的前兆。 E-1井的一系列水位变化表现出水文地质动力前兆：震前21天内水位下降速度加快，震后1个月内水位上升幅度达3.7厘米。实时检测到的水文地球动力前兆为预测一个月内距 E-1 井 350 公里处极有可能发生强地震提供了依据。该预测于2016年1月21日向俄罗斯专家委员会堪察加分会（KB REC）报告。朱帕诺夫斯基地震发生于2016年1月30日，其震级、时间和地点与预测相关。此次地震的案例表明，俄罗斯联邦研究中心“俄罗斯地球物理调查”堪察加分院拥有水位观测和数据处理系统，能够（接近实时和回顾性地）诊断强震事件时井水位不同类型的水文地震变化，并探测强震的水文地球动力前兆。
This paper describes the water level variations in wells YuZ-5 and E-1 inKamchatkaduring the Zhupanovsky earthquake that occurred on January 30, 2016 (M w =7.2, Н =180 km). The distances from the Zhupanovsky earthquake epicenter to wells E-1 and YuZ-5 were 70 and 80 km, respectively. In well YuZ-5 , the water level raised by 9.4 cm during 45 minutes after the seismic wave arrival. This effect was caused by a combination of a co-seismic rise in the water level due to the volumetric compression of the water-bearing rocks during fracturing in the earthquake source and an impulse increase in the fluid pressure near the wellbore during the seismic shocks. We estimated the amplitude of the coseismic water level increase (D h =7.3 cm) and the strain value resulting from the volumetric compression of the water-bearing rocks, which is consistent with the estimated value of the coseismic volumetric deformation in the area of the well at the depth of 500m: D 1 = –4.5×10 –8 . This estimation was based on the model of the dislocation source in the homogeneous isotropic elastic half-space with the parameters of the Zhupanovsky earthquake focal mechanism. After the earthquake, the water level dropped for three months at an amplitude of about ~40 cm. In order to estimate the radius of the well sensitivity to the pressure drop source, we used the model of water level lowering that followed the pressure drop in the aquifer at a distance to the well as a result of the improved filtration properties of the water-bearing rocks after the seismic shocks. The estimated radius of the well sensitivity, R is 450 m. For 3.5 months before the Zhupanovsky earthquake, ~20 cm increase in the water level was observed, which is anomalous in comparison with the average seasonal variations of the water level, as shown by the long-term observations. In our opinion, such a rise in the water level occurred in the process of the earthquake preparation, and can thus be viewed as its precursor. In well E-1, a sequence of water level changes manifested a hydrogeodynamic precursor: the water level dropped at an increased rate for 21 days before the earthquake, and raised at an amplitude of 3.7 cm during one month after the earthquake. The hydrogeodynamic precursor detected in real time gave grounds for forecasting a highly probable strong earthquake at a distance of up to 350 km from wells E-1 within a month. This forecast was reported to the Kamchatka Branch of the Russian Expert Council (KB REC) on January 21, 2016. The Zhupanovsky earthquake occurred on January 30, 2016, and its magnitude, time and location correlated with the prediction. The case of this earthquake shows that the Kamchatka Branch of the Federal Research Center ‘Geophysical Survey of RAS’ has the system of water level observations and data processing, which is capable of diagnosing (close to real time and retrospectively) different types of hydrogeoseismic variations in the water level in wells in case of strong seismic events, and detecting the hydrogeodynamic precursors of strong earthquakes.