Spatial variation of aquifer permeability in the North China Plain from large magnitude earthquake signals

doi:10.21203/rs.3.rs-2967689/v1

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Spatial variation of aquifer permeability in the North China Plain from large magnitude earthquake signals

https://doi.org/10.21203/rs.3.rs-2967689/v1

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published 06 Jun, 2024

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Permeability changes induced by earthquakes have been studied widely. However, basic questions still remain: What are the spatial differences in permeability changes induced by far-field earthquakes? Is there an inevitable relationship between seismic energy density, epicenter azimuth and permeability change? We try to answer the above questions by examining records of 11 years of groundwater hydrographs of 7 wells in the North China plain at large distance from the epicenters of 221 earthquakes during the period 2008 ~ 2018. The results shows permeability changes varied between the different wells, with the permeability variation of the JN well most sensitively responding to seismic events, while the least sensitive wells being SH, JZ and LK. We found that the azimuths of seismic waves can greatly influence the changes in permeability, i.e. mainly concentrated between 25° and 295°. The seismic density energy (SDE) value larger than approximately 10^-9 J/m³is likely to induce a change in permeability in the NCP aquifer materials. It is found that SDE is not a predictor of permeability change at a given well, by calculating the seismic energy density which did not cause permeability change. While the permeability change ratio before and after the earthquake can be considered as the ability of permeability respond to the dynamic stress and it shows a weak correlation with depth of aquifer. Thus, Factors that probably affect permeability responses changes would have implications for crustal geomechanics.

Fractured aquifers

Tidal analysis

Horizontal permeability

Earthquakes

North China Plain

(1) Seismic energy density is not a predictor of permeability change at a given well.

(2) The sensitivity to permeability variation is dominated by epicenter azimuth (205° - 295°) in the NCP.

(3) The newly defined permeability change ratio is correlated to aquifer depth.

The phenomenon of earthquakes triggering permeability changes in shallow and deep aquifers of near-surface systems had previously been recognized (Rojstaczer and Wolf, 1992; Rojstaczer et al., 1995; Sato et al., 2000, 2004; Elkhoury et al., 2006; Skelton et al., 2014; Shi and Wang, 2014; Yan et al., 2016; Wang and Barbour, 2017; Shi et al., 2018; Weaver et al., 2019). Both horizontal and vertical permeability may be changed by static and dynamic stress generating by local and distant (with respect to the earthquake epicenter) earthquakes. Co-seismic increase in permeability, as well as permeability decrease and no change in permeability with seismic events have all been observed in the field (Wang et al., 2001; Chi-yuen Wang and Michael Manga, 2009; Menzies et al., 2016; Aben et al., 2017; Rutter et al., 2016; Rosen et al., 2018; Shi et al., 2019). The above previous studies mostly used records of groundwater level changes in a single well as response to multiple earthquakes (Shi and Wang, 2014; Lai et al., 2016; Ma et al., 2017), responses of multiple well hydrographs to a single earthquake (Chi-yuen Wang and Michael Manga, 2009; Chia et al., 2010), and responses of multiple well hydrographs to multiple earthquakes (Wang et al., 2010; Shi, 2015; Weaver et al., 2019). Aquifer lithologies comprised gravel, fine sand, silt, mud and clay (Wang et al., 2009; Geballe et al., 2011; Rutter et al., 2016), sandstone, and quartzitic sandstone (Rojstaczer and Wolf, 1992; Tokunaga, 1999; Shi and Wang, 2016; Liao et al., 2015; Wang et al., 2016), granodiorite (Brodsky and Emily, 2003; Elkhoury et al., 2006), limestones (Shi and Wang, 2014, 2016), and magma pocket material (Shi et al., 2018). The depth to the aquifer systems ranges mainly between 20 m and 614 m, with a maximum depth of 4 km.

In a number of groundwater flow systems, permeability changes could often be explained by earthquake generated interconnections across aquifers and aquitards even at depths of several kilometers, the consolidation of aquifer material and changes in hydraulic regime from a confined aquifer to a semi-confined aquifer in the near field (Liao et al., 2015; Wang et al., 2016; Shi et al., 2018). In the far field, co-seismic water level fluctuations and other hydraulic responses are rather unusual and occur only under very specific conditions, i.e., combinations of the “appropriate” wave period, and well completion - aquifer geometry (e.g. height of water column in the well, well radius, and aquifer thickness) and hydraulic aquifer properties (transmissivity, permeability, storage coefficient; Cooper et al., 1965; Liu et al., 1989). Surprisingly, the 2011 Tohoku earthquake may have significantly changed both the hydraulic and the poroelastic properties of the aquifer at a distance of more than 1,500 km measured from the epicenter (Zhang et al., 2019). The observed property changes are likely to be caused by the mechanical response of the aquifer material to stresses induced by seismic waves (Roeloffs, 1998; Matsumoto and Roeloffs, 2003; Manga and Wang, 2015). Alternatively, dynamic stresses in the elastic waves could cause large oscillations in pore pressure that possibly drive the observed permeability changes, that is, they are often caused by a perturbation of seismic waves (Brodsky and Emily, 2003). In laboratory experiments oscillatory stresses and axial stress oscillations of different amplitudes and frequencies were imposed on intact or fractured sandstone, and corresponding permeability changes be monitored. The results showed that pore pressure oscillations of samples drove the flow with permeability changes as a function of oscillation amplitudes (Shmonov et al., 1999; Roberts, 2005; Liu and Manga, 2009; Elkhoury, 2011). In addition, earthquake-induced permeability changes return to the pre-earthquake values after a certain period of time ranging from between just a few minutes (Geballe et al.,2011) to many years (Cappa, 2009; Kitagawa et al., 2007; Manga et al., 2012).

Several mechanisms have been proposed in recent years to explain the co-seismic and post-seismic changes in permeability (a) dynamic stresses large enough to cause shear failure or create new pathways, (b) preexisting pathways opening and closing, (c) particle mobilization mechanisms, clogging/unclogging of temporary barriers, and (d) mobilization of fluid drops and gas bubbles (Elkhoury et al., 2006; Elkhoury, 2011; Manga et al., 2012; Candela et al., 2014; Crews and Cooper, 2014; Ma et al., 2017; Shi et al., 2019). In previous studies, the above mechanisms were based on a large number of field observations providing direct evidence for changes in permeability with earthquakes as the driving force. However, the difference of spatial response to earthquakes at each observation well and whether there is a depth dependence with the magnitude or range of permeability variation caused by large and distant earthquakes are still unknown.

Here, we present an investigation on the change in horizontal permeability in fractured rock aquifers of the North China Plain (NCP). Groundwater level records of 7 monitoring wells and 221 earthquakes larger than magnitudes of M_S 7.0 for the period 2008 to 2018 were available. We explore a number of issues: (a) variation of permeability change ratio before and after earthquakes in the North China Plain from large earthquake signals; (b) statistical relationship between seismic energy density, azimuths of seismic waves and permeability change. We believe that our understanding of permeability variations of aquifers in NCP derived from large magnitude earthquake signals can contribute largely to the quantitative assessment of the response of the aquifer to seismic events.

The NCP is located in the North China Paraplatform (Fig. 1). The North China Paraplatform (triangular shape) is the Chinese portion of Sino-Korean Paraplatform, which encompasses nearly all of the NCP, a part of northeastern China and the northern part of the Korean peninsula (Zhai et al., 2005). Early Precambrian rocks crop out extensively and constitute the metamorphic basement of the craton. Proterozoic, Paleozoic (largely carbonates) and younger rock sequences (Permo-Carboniferous terrestrial sediments with marine intercalations and purely terrestrial Meso-Cenozoic sediments) partially cover this basement (Zhai et al., 2005). Unconsolidated Quaternary sediments cover the basement and the bedrock units. In the NCP, there are several main faults (Fig. 1): Taihangshan fault is a large-scale and complex structure transition fault zone in the west, Tanlu fault is a deep and active fault in the east, the Zhangjiakou-Penglai fault, located in the north, formed during the Quaternary with intense activity, the southern margin fault of North China block is formed based on the Proterozoic structure, the Cangdong fault is a crust-scaled detachment fault, and the Hengshui fault zone is associated with transfer zones, dividing north and south regions of the depression (Gao et al., 2000;Yanget al., 2004; Xu, 2013). These fault zones can be classified into two categories, approximately north-east striking faults, i.e. Taihangshan, Cangdong and Tanlu faults, and south-east striking faults, i.e. Zhangjiakou-Penglai, Hengshui and the southern margin faults.

The actual study area is located close to the Bohai Sea and Huanghai Sea, with important groundwater resources covering an area of ca. 310,000 km². A fully-developed network of seismic and groundwater monitoring stations had been set up in the past. The CP, SZ, SH, HZ, JZ, JN and LK wells are spatially even distributed (Fig. 1).

The 7 wells were drilled into fractured confined aquifers, with the depths ranging from ca. 220 m to ca. 3100 m, and instrumented with groundwater levels recorders (LN-3A),with a resolution of 1 mm and measurement accuracy and stabilization of ± 0.2% full-scale. The sampling rate is 1/minute. Thus, a series of water level records (Fig.S1 and Fig. S2) were available for the period 2008–2018. The thickness of the aquifer ranges between ca. 15 m and 850 m (Table 1). The lithostratigraphy of aquifers is mainly Late Carboniferous, Ordovician, Cambrian and Sinian, while the lithology is mostly composed of limestone, dolomitic limestone and shale (Fig. 2 and Table 1). 221 earthquakes of magnitudes of at least M_S 7.0 were recorded between 2008 and 2018. The earthquakes, however, are far-field while the magnitudes of near-field are smaller than M_S5.0 during this period.

Table 1

Basic information of monitoring wells in the North China Plain.
Well name	Lon (°)	Lat (°)	Alt (m)	Dep (m)	Aquifer lithostratigraphy and lithology	Average epicenter distance (km)	Screened interval (m)	d (m)	r_c (m)	r_w (m)
CP	116.25	40.04	100	222	Sinian dolomite limestone	7744	200–222	21.86	0.075	0.075
SZ	115.56	38.07	30	3364	Ordovician dolomite limestone	7750	3347.5–3364	16.5	0.08	0.08
SH	117.35	37.2167	50	2836	Ordovician limestone	7700	2799–2836	37	0.12325	0.0762
HZ	115.3	35.37	40	2001	Cambrian limestone and shale	7745	1144–2001	857	0.159	0.108
JZ	113.42	35.33	106	564	Late Carboniferous limestone	7794	555.31–564	8.71	0.0455	0.0375
JN	117.85	35.1666	97	321	Carboniferous limestone	7678	251.86–321	69.14	0.055	0.0455
LK	114.97	34.93	69.9	3138	Cambrian limestone	7753	2908.15–3138	230.22	0.0889	0.0794
Note: Lon, Lat, Alt, Dep, d, r_c, r_w imply longitude, latitude, altitude, depth, aquifer thickness, casing radius and screen radius, respectively.

Wells information is from the Earthquake Monitoring Records of Chinese provinces.

3.1. Tidal analysis

Earth tidal behaviors may induce groundwater flow periodically in the well-aquifer system. The tidal analysis was conducted employing the software package Baytap-G for decomposing the tidal components, produced by solar and lunar forcing, i.e., Q₁, O₁, M₁, S₁, J₁, OO₁, 2N₂, N₂, M₂, L₂, S₂ and M₃ waves (Tamura et al., 1991). The M₂ tidal component is widely used for analysis due to its strong signal and not being affected by barometric pressure (Liao et al. 2015; Weaver et al. 2019). Data window lengths of 30 days with an overlap of 15 days were applied in our calculation.

According to recent studies, earth tide induced groundwater vertical leakage could both caused positive and negative phase shift (Wang et al., 2018); and the exist of wellbore skin effect (Gao et al., 2020) will also lead to the positive and negative phase shift. As the cases in this investigation are large far-field earthquakes, they are unlikely breaching the neighbor aquifer and causing the aquifer vertical leakage occur (Zhang et al., 2022 and Zhang et al., 2021). And the seismic events induced-water level change, the skin effect had been ignored. Therefore, tidal analysis is recently an effective method to estimate aquifer parameters. In this study, we used the Hsieh model (Hsieh et al., 1987) and the Doan model (Doan et al., 2006), combined with the relationship between amplitude and phase shift to distinguish horizontal from vertical groundwater flow directions (Table 2). The results suggest that each aquifer satisfies the horizontal flow conditions.

Table 2

Assessment of groundwater flow direction.
Flow direction	Phase shift	Relationship between phase shift and amplitude
Horizontal flow	η < 0°	Syntropy
Vertical flow	η > 0°	Reverse

We set the criterion to recognize the tidal phase shift and amplitude responses induced by earthquakes (Fig. 3), as the change in phase shift larger than twice the root-mean-square error indicating occurrences of changes. By this criterion, 67 out of 221 earthquakes were deemed to induce a possible change in permeability (Table S3)

3.2. Permeability estimation

The phase shift and amplitude of the water level response to the M₂ tide are determined (Fig. 3). The variations in phase shift reveal changes in hydraulic properties of the aquifer, here, transmissivity (Hsieh et al., 1987; Elkhoury et al., 2006). Based on the results and the screen length of the well, we evaluated the permeability of the seven wells assuming a horizontal flow model (Hsieh et al., 1987). Below, the analytical solutions employed for the assessment of the hydraulic parameters:

$$X={({E}^{2}+{F}^{2})}^{-1/2}$$

$$\eta ={-tan}^{-1}（F/E）$$

with $X$ as the amplitude response; $\eta$ is the phase shift (°); $E$ and $F$ are defined as

$$E\approx 1-\frac{\omega {r}_{c}^{2}}{2T}Kei\left({\alpha }_{w}\right)$$

$$F\approx \frac{\omega {r}_{c}^{2}}{2T}Ker\left({\alpha }_{w}\right)$$

$${\alpha }_{w}={\left(\frac{\omega S}{T}\right)}^{1/2}{r}_{w}$$

$\omega$ is frequency tidal component (0.5175d/cycles of M₂);${ r}_{c}$ is the radius of the well casing (m); ${ r}_{w}$ is the radius of the well screen (m); $Ker\left({\alpha }_{w}\right)$ and $Kei\left({\alpha }_{w}\right)$ are the real and imaginary parts of zero-order Kelvin functions, respectively; $T$ is the horizontal transmissivity (m²/s); $S,$the storativity, can be calculated by

$${S=S}_{S}d$$

$${S}_{S}=7.88\times {10}^{-9}\frac{{A}_{2}(\tau ,\theta )}{{A}_{h}\left(\tau \right)}$$

$${A}_{2}(\tau ,\theta )=g{K}_{m}bf\left(\theta \right)$$

Where ${S}_{S}$ is the specific storativity (m^− 1); $d$ is the thickness of aquifer (m); ${A}_{h}\left(\tau \right)$ is the amplitude of groundwater potential fluctuation caused by different tidal components; ${A}_{2}(\tau ,\theta )$ is the amplitude of second-order tidal potential; ${K}_{m}$ is a constant related to the mass of earth and moon, their distance and the radius of the earth (~ 0.537m); $b$ is a constant associated with the period of a tidal wave component then permeability (~ 0.908 for M₂); $f\left(\theta \right)$ is the function of latitude ($f\left(\theta \right)=0.5{cos}^{2}\theta$ for M₂). The permeability $k$ (m²) can be estimated from

$$k=\frac{\mu }{\rho gd}T$$

Where $\mu$ is dynamic viscosity (~ 10^− 3Pa at 20 ℃); $\rho$ is density (~ 10³kg/m³); $g$ is gravitational acceleration (~ 9.81m/s²), $d$ is the thickness of aquifer (m).

According to the above calculation process, a time series of permeability changes could be obtained (Fig. 3, Fig. S3 and Fig. S4).

4.1 Response times of aquifer permeability changes

Figure 3 shows trends in horizontal permeability changes with time for the seven aquifers in response to the 67 distant, large magnitude earthquakes. From 2008 to 2018. The permeability of target aquifers in the NCP vary between the wells. That the type of change in permeability (decrease, increase and no change) and its magnitude differs with every earthquake, of all aquifers had a certain randomness. Comparing the initial permeability in 2008 with that of 2018, we found a general decrease in permeability for five aquifers (CP, SZ, HZ, JZ and JN) while permeability increases in the remaining two aquifers (SH and LK) (Fig. 4 and Fig. 5).

According to the permeability change criteria set above, if one change in permeability is recorded as one response. From the perspective of a monitoring well responding to multiple shocks, the permeability variation of the JN well responds most sensitive to seismic events (26 times), followed by the SZ well (22 times), while earthquakes induced 7 times permeability changes in the HZ and CP observation wells, SH and JZ wells responded 4 times, LK well responded 3 times. If we examined the response of multiple wells to one single earthquake and we did not find synchronous changes in all seven wells with respect to a single earthquake. Instead, the earthquake that caused possible permeability changes in up to three of the seven wells. That is, permeability decreases in CP, JZ and JN well after the 2009 Greenland Sea M_S 7.0 earthquake and also change in SH, JN and LK well after the 2013 Ms 7.0, Andreanof Islands. In total, 15 of 67 selected earthquakes could trigger the multiple permeability responses, and 10 events triggered consistent permeability changes, i.e. they either show a consistent increase or decrease (Table S3).

4.2 Permeability variations before and after earthquakes

The horizontal permeability ranges between 1.89×10^− 17and 5.49×10^− 13 for all observation wells. In the individual wells, permeability varies in the ranges: 1.89×10^− 17to 3.69×10^− 15m² for well JN, 9.97×10^− 15to 1.43×10^− 13m² for well SZ, 9.03×10^− 15to 9.74×10^− 14m² for well HZ, 1.40×10^− 15 to 1.46×10^− 14m² for well JZ, 9.10×10^− 15to 9.41×10^− 14m² for well LK, 3.57×10^− 14to 1.23×10^− 13m² for well CP and 1.13×10^− 13to 5.49×10^− 13m² for well SH (Fig. 4 and Fig. 5). In well JN, permeability changed by two orders of magnitude, with the ratio between maximum and minimum permeability being ca. 190, while the max-min-ratios of all the other wells range between 7 and 14 (Table S2).

We compiled permeability-depth curves based on the permeability changes determined for the fractured aquifers of the NCP (Fig. 4). No systematics could be determined for the permeability-depth relationship. As apparent, the horizontal permeability is not a fixed parameter as shown in Fig. 4, which is consistent with the understanding of Townend and Zoback (2000) and Weis et al. (2012). Therefore, permeability can be regarded as a dynamic value with earthquakes as a driving force determining the magnitude of its change.

The maximum value of permeability reduction amounts to 2.78×10^− 13 m², i.e. in well SH permeability changed from ca. 5.49×10^− 13m² to ca. 2.71×10^− 13m², i.e. was halved after the 2013 Negros M_S7.1 earthquake. The maximum value of enhanced permeability was assessed at 5.27×10^− 14 m²in HZ well, i.e. permeability increased from ca. 1.52×10^− 14m² to ca. 6.79×10^− 14m² after the 2011 Honshu Coast earthquake. For the study period, data show that permeability decreases range between 2.79% and 87.67% for 38 of total 73 cases, while increases range between 4.6% and 522% for 35 cases (Fig. 5 and Table S3).

In order to quantitatively investigate the spatial characteristics of permeability variations and potentially driving factors, we conducted statistical work related to changes in permeability: epicenter azimuth vs permeability, seismic energy density vs permeability and permeability change ratio assessment.

5.1 Epicenter azimuth affecting spatial horizontal permeability change

Hydraulic property changes in seven aquifers of the NCP showed different sensitivity to a cluster of earthquakes. In terms of the number of responses, the sensitivity of permeability variations from high to low in seven observation wells can be ranked as follows: JN, SZ, CP (HZ), SH (JZ) and LK. We interpreted the difference in permeability change times by investigating the influence of the epicenter azimuth.

Since seismic waves of far-field earthquakes can be categorized as slow-decay and low-frequency surface waves, the azimuths of earthquake epicenter had been examined, believed to exert different effects on the aquifer material with the consequence of permeability.

Figure 6 shows the distributions of epicenter azimuth of permeability changes in response to distant earthquakes. Permeability changes in the NCP induced by earthquakes are concentrated in the azimuth sector 25° − 295°. Especially, large earthquakes induced permeability changes in the SZ well had been observed almost at all azimuths. Surprisingly, in the sector 250° − 295°, Permeability changes in all 7 aquifer horizons had been recorded. Both permeability increases and decreases triggered by different earthquakes were observed in the remaining six wells, except for the JZ well, where only permeability decreases were observed. In sector 205° − 250° permeability changed in 6 observation wells, and in sector 115° − 160° permeability changed in 5 observation wells. In the sector 25° − 75°, only two aquifers (SZ and JN wells) showed permeability increase. Moreover, in JZ well, the permeability responded sensitively to earthquakes arriving from azimuth sectors 115° − 160°, 205° − 250° and 250° − 295°. In each of the three azimuth sectors, permeability responded only with either an increase or decrease, quite different compared to the other 6 wells. While in LK well, the azimuth sector of the permeability change is 70° − 115° and 250° − 295°. The larger the range of azimuth response, the more times of response (JN and SZ), while CP (HZ) well were the second with 4 azimuth spans (7 times), the remaining three well had the least azimuth span (3,2 spans ~ 4,3times) (Fig. 6). Therefore, there may be different dependencies between azimuth and permeability changes in 7 wells. This observation is similar to the permeability decrease recorded in well JN and well DY (Shi et al. 2019).

5.2 Relationship between seismic energy density and permeability change

To further document the difference in sensitivity of the response of the respective aquifers monitored at the different wells. Next we examined the relationship between permeability changes and dynamic strain induced by far-field earthquakes. We employed a function of earthquake magnitude (M_W) and epicentral distance, r (km) to determine seismic energy density e (J/m^− 3), published by Wang (2006) and Wang and Manga (2010).

The seismic energy density (e) ranges between 10^− 10 J/m³ and 10^− 3 J/m³, corresponding to permeability change (67 cases) with the criteria (twice the RSME) of specified above (Table 3). The results indicate that the energy value larger than approximately 10^− 9 J/m³ is likely to induce a change in permeability in the NCP aquifer materials. Our calculation results is different to that of previous studies. Wang (2006), Wang and Manga (2010) stated a statistical empirical seismic energy density threshold of ca. 10^− 4 J/m^− 3 to initiate hydrologic responses and hydraulic property changes.

We also calculated the seismic energy density of 154 earthquakes which did not induce permeability change (Table 3). Documenting non-responses is useful for establishing whether seismic energy density is a predictor of permeability change at a given well. Calculations show that SED (e) value is also between 10^− 10 J/m³ and 10^− 3 J/m³. It can be found that it may not invoke a change in permeability when the seismic energy density reach a certain threshold. Then permeability change vs seismic energy density for all 221 events and all wells are plotting in Fig. 7. Figure 7 illustrates that there is no fixed law in the distribution of seismic events plotting that cause permeability changes.

It can be said that the seismic energy density is not a predictor of permeability change at a given well in NCP. And the mechanism of seismic permeability changes may not be exactly the same for each well in different aquifer background conditions.

Table 3

Seismic energy density for permeability change by empirical relationships of magnitude and epicentral distance.
Well name	Permeability changed or unchanged	Results from log e = 1.45 M − 3 log r − 4.24	Results from log e = 1.45 M – 3.2 log r − 4.24	Results from log e = 1.45 M – 3.5 log r − 4.24
CP	Changed	10^− 7~10^− 3	10^− 8~10^− 3	10^− 9~10^− 4
CP	Unchanged	10^− 7~10^− 2	10^− 8~10^− 3	10^− 10~10^− 4
SZ	Changed	10^− 7~10^− 3	10^− 7~10^− 4	10^− 9~10^− 5
SZ	Unchanged	10^− 7~10^− 2	10^− 8~10^− 3	10^− 10~10^− 3
SH	Changed	10^− 7~10^− 5	10^− 8~10^− 6	10^− 9~10^− 7
SH	Unchanged	10^− 7~10^− 2	10^− 8~10^− 3	10^− 9~10^− 4
HZ	Changed	10^− 6~10^− 4	10^− 7~10^− 5	10^− 8~10^− 6
HZ	Unchanged	10^− 7~10^− 2	10^− 8~10^− 3	10^− 9~10^− 4
JZ	Changed	10^− 6~10^− 4	10^− 7~10^− 5	10^− 8~10^− 6
JZ	Unchanged	10^− 7~10^− 2	10^− 8~10^− 3	10^− 9~10^− 4
JN	Changed	10^− 7~10^− 2	10^− 8~10^− 3	10^− 9~10^− 4
JN	Unchanged	10^− 7~10^− 3	10^− 8~10^− 4	10^− 9~10^− 5
LK	Changed	10^− 6	10^− 7~10^− 6	10^− 8
LK	Unchanged	10^− 7~10^− 2	10^− 8~10^− 3	10^− 10~10^− 4

5.3 Permeability change ratio of aquifers at different depth

For a decade monitoring period, only well JN shows a distinct characteristic maximum - minimum permeability ratio of as high as 190, while maximum - minimum permeability ratios at all other well locations amount to approximately 10. It is found that the initial permeability of JN Well is the lowest among the seven wells, with the largest number of changes in 10 years and the smallest absolute change in permeability. Moreover, the maximum and minimum permeability data of JN well were not obtained before and after the same earthquake, and the time span between the two values amounts to more than six and a half years, while the time interval is three to five years of other well sites, except for well LK with two and a half years with water level recordings during the period 2008–2015. It is difficult to compare permeability changes from well to well. Here, we utilize the permeability change ratio before and after earthquakes from a different standpoint, to analyze the mechanism of permeability change induced by earthquakes.

In current study, the permeability ratio before and after the earthquakes represents the “ability” of permeability to adjust after being subjected to the stress. In Fig. 8 we plotted the calculated permeability ratio after an earthquake against the depth of the screen center. The data points, a significant feature in the permeability ratio, as compared with each well site, all ranges from − 0.9 to 5.0 (Fig. 8 and Table S3). Also, points are distributed in an inverted triangle (Fig. 8), which seemingly illustrates a “weak” reduction in permeability change ratio with depth.

We present analyses of more than a decade of water level measurements across a large region in eastern China to better understand spatial patterns in the seismic-wave-induced changes in permeability, using 7 wells with depths ranging from ~ 220m to 3.3 km. Tidal analysis are used to determine permeability changes related to more than 200 teleseismic events of M > 7.0. The focus of the study is on the factors that influence the sensitivity to changes in permeability and the spatial variation in the changes.

Important implications include:

The background values of permeability vary among aquifers with different characteristics, and each permeability is constantly self-adjusting on its background value, rather than a fixed parameter. The sensitivity and characteristics of permeability responses in different spatial aquifers to multiple earthquakes are different. The permeability of most sensitive JN well responded to 26 times of the 221 earthquakes with the ratio between maximum and minimum permeability being ca. 190, while all the other wells responded from 3 to 26 times with the max-min-ratios ranged between 3 and 14.

The permeability response to different earthquakes is probably influenced by and the azimuth of the epicenter. The seismic energy density greater than 10^− 9 J/m³ could cause permeability change. There are more cases where the value is greater than or equal to this value and no permeability change is observed. So it does not mean that 10^− 9 J/m³ is the threshold of permeability change. The other finding is that the permeability change ratio between before and after earthquake shows a weak correlation with aquifer depth, i.e. permeability change ratio decrease with aquifer depth, which would have implications for crustal geomechanics.

Acknowledgements

This work was supported by the Beijing Natural Science Foundation of China (8222003).

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Spatial variation of aquifer permeability in the North China Plain from large magnitude earthquake signals

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Abstract

Figures

Highlights

1. Introduction

2. Observations

3. Methods and Calculation

3.1. Tidal analysis

3.2. Permeability estimation

4. Results

4.1 Response times of aquifer permeability changes

4.2 Permeability variations before and after earthquakes

5. Discussion

5.1 Epicenter azimuth affecting spatial horizontal permeability change

5.2 Relationship between seismic energy density and permeability change

5.3 Permeability change ratio of aquifers at different depth

6. Conclusions

Declarations

Acknowledgements

References

Additional Declarations

Supplementary Files

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