Characteristics of surface deformation field of Changning shale gas block in southern Sichuan basin with InSAR data
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摘要: 近年来随着我国页岩气大规模开采,四川盆地南部活动构造相对稳定的地区出现了一系列微震和有感地震,甚至是破坏性地震。这些地震是否为工业开采所诱发,目前已有研究从时空相关性给出了一些统计推断,本文则从形变观测角度分析页岩气开采能否产生可以检测到的地面形变,以揭示形变信息与页岩气开采的关系,尝试为页岩气开采提供有效的监测手段。基于长波ALOS-2卫星雷达数据对长宁页岩气区块近两三年内的InSAR地表形变展开探测,检测页岩气大规模生产可能造成的地面形变及其基本特征,同时使用Sentinel-1卫星雷达数据分析页岩气开发活跃时段内的形变时间序列信息。结果显示:考虑到不同观测技术的误差水平和观测角度差异,两种卫星数据均反映了一致的地表形变分布,且形变场与页岩气开采井的空间分布有很好的对应关系;压裂注液过程会造成地表快速隆升,生产过程中随着流体扩散地表会出现沉降和水平运动,初步揭示出页岩气生产过程中地面形变的非稳态变形特征。这表明在四川盆地南部复杂的形变观测条件下,InSAR技术是页岩气开采有效的监测手段,能够弥补地震学观测的不足。Abstract: In recent years, along with large-scale development of shale gas, the seismicity rate has increased dramatically, a series of microseismicity, felt earthquakes and even destructive earthquakes occurred in southern Sichuan basin, a relatively tectonic stable area. Some studies statistically infer whether these earthquakes were induced by industrial activities by using spatio-temporal correlations. This study, on the other hand, uses deformation measurements to analyze whether shale gas exploitation can produce detectable surface deformation, so as to analyze the relationship between deformation and shale gas exploitation, in an attempt to find an effective approach for shale gas exploitation monitoring. Long wavelength ALOS-2 satellite radar data has the potential for minimizing decorrelation effects of radar signals caused by vegetation, heavy water vapor and topographic relief in Sichuan basin. We used ALOS-2 InSAR data to measure surface deformation in Changning shale gas block in the past two or three years, found possible ground deformation caused by massive shale gas production and analyzed its basic characteristics. Meanwhile we also processed time-series of Sentinel-1 satellite radar data to measure the surface deformation during active periods of shale gas exploitation. Considering the errors and different observation geometries of the two datasets, the results from two databases are consistent in revealing the surface deformation. Furthermore, the meaured deformation field is in agreement with the spatial distribution of shale gas wells. Our observations show fast surface uplift during hydrofracture injection, also ground subsidence and horizontal motion in production period with fliud diffusion. We preliminarily reveal the non-steady deformation characteristics during shale gas production. Our study suggests that InSAR is an effective technique for shale gas production monitoring even in southern Sichuan basin where complex deformation occurs, and can provide insights supplementary for seismological observations.
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Keywords:
- shale gas exploitation /
- differential interferometry /
- ALOS-2 /
- PS-InSAR
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引言
目前关于地下结构的研究发展迅速,众多研究人员认为地下结构的抗震性能优于地上结构,因而大量建成的地下结构均未考虑抗震设计(Hashash et al,2001;于翔,2002)。但近年来大量震后调查(Wang et al,2001;Scawthorn et al,2006;崔光耀等,2017)表明以地铁、隧道为代表的地下结构也遭遇了严重的震害。通常对于地下结构所遭受的损害,其修复费用和时间远超地上结构。因此对于地下结构抗震性能的研究尤为重要。确定一个合理的地震动强度指标(intensity measure,缩写为IM)是基于性能的抗震设计方法的重要环节之一,同时合理的IM可以有效地降低结构响应预测的离散性,因此确定合理的IM具有重要的意义。
目前已有不少针对IM与地上结构响应之间关系的研究,并取得了诸多成果,相同IM对预测不同结构形式响应时的效用不同,不同IM对相似结构的效用也不同。Riddell (2007)和Yang等(2009)选择单自由度体系展开研究,其结果表明加速度型指标适用于刚性系统,速度型指标适用于中频系统,位移型指标适用于柔性系统。于晓辉(2012)选取了60个地震动强度参数和6个结构反应参数,经过综合性评价分析得出与结构性质有关的地震动强度参数有更好的评价效果。陈健云等(2017)利用相关系数对不同周期框架结构进行三维分析,给出了13种常用的地震动强度指标与不同周期结构响应之间的相关性,其结果表明加速度型、速度型及位移型强度指标与不同周期结构响应参数的相关性不同。左占宣等(2019)采用变异系数对比了新强度指标等效周期谱加速度Sa(Teq)与已有的强度指标结构弹性基本周期对应的谱加速度Sa(T1),结果表明运用Sa(Teq)可以有效地降低倒塌分析结果的离散性。Yang等(2019)对两种不同形式的隔震结构进行了有效性、充分性以及灵敏度的分析,进而得出修正速度谱强度是预测大部分工程需求参数(engineering demand parameter,缩写为EDP)的有效指标。另有众多研究人员也针对诸如隔震结构(耿方方等,2013)、桥梁(李雪红等,2014)、超高建筑(卢啸等,2014)、网壳结构(于天昊,2016)等不同结构与多种IM之间的关系展开了研究。
由于受到围岩土体的约束,地下结构的地震响应不同于地上结构。适用于地下结构的地震动强度指标IM的研究还相对有限。Chen和Wei (2013)分析了埋深44 m的山岭隧道衬砌整体损伤指数与地震动强度指标之间的关系,结果表明山岭隧道衬砌整体损伤指数与速度相关型地震动强度指标的相关性较高。钟紫蓝等(2020)以日本神户埋深4.8 m的大开地铁车站为研究对象,分析了22个地震动强度指标的有效性、效益性和实用性,其结果表明对于文中采用的结构形式,以峰值加速度(peak ground acceleration,缩写为PGA)和复合加速度Ia为代表的加速度型指标和以加速度谱强度为代表的谱相关型地震动强度指标有更强的适用性。
目前针对地下结构的研究都是固定埋深的,但地下结构埋深的变化对地下结构的内力、变形等地震响应具有显著的影响(李长青等,2011;Pitilakis et al,2014),而且埋深是地下结构抗震设计不可忽视的重要因素之一。随着城市用地紧张,对地下空间的开发日趋加深,日本就设想将城市地下规划到50—80 m (董正方等,2017),因此研究最优地震动峰值指标随地下结构埋深变化的规律具有重要的意义。由于地下结构受周围土体的约束,其地震响应与周围场地变形密切相关,因此本文从简单一维场地地震响应着手,拟采用从太平洋地震工程研究中心(Pacific Earthquake Engineering Research Center,缩写为PEER)获取的实际地震动作为输入,以不同波速的均匀半空间场地以及成层半空间场地为对象,基于效益性准则探究最优地震动峰值指标随埋深变化的规律,以期确定不同埋深下的最优地震动强度指标,为结构抗震性能评价提供合理的地震动指标参考。
1. 模型与计算方法
本文涉及的均匀半空间场地以实际场地为例,剪切波速从100 m/s到500 m/s,每间隔50 m/s设计一个场地,加上波速为85 m/s的场地共计10个均匀半空间场地,囊括了 《GB 50011—2010建筑地震设计规范》(中华人民共和国住房和城乡建设部,中华人民共和国国家质量监督检验检疫总局,2010)中Ⅰ —Ⅳ类场地条件,均匀半空间场地均为线弹性无阻尼介质,相关信息详见表1。
表 1 均匀半空间场地信息Table 1. Information of homogeneous half-space sites场地序号 密度/(kg·m−3) 剪切波速/(m·s−1) 场地类别 1 1 800 85 Ⅳ 2 1 820 100 Ⅳ 3 1 850 150 Ⅲ 4 1 920 200 Ⅲ 5 1 920 250 Ⅲ 6 1 970 300 Ⅱ 7 1 970 350 Ⅱ 8 2 100 400 Ⅱ 9 2 100 450 Ⅱ 10 2 300 500 Ⅰ 成层半空间场地由一层土层和半空间基岩层组成,土层参数参考某地铁工程场地的地震安全性报告①选取。为方便对比,设计土层厚度为40 m,所有场地基岩取相同深度,其详细信息见表2,土体剪切模量比和阻尼比随剪应变的变化曲线如图1所 示。基岩为线弹性无阻尼介质。
表 2 成层半空间场地信息Table 2. Information of layered half-space sites场地序号 分层 土类号 厚度/m 泊松比 密度/(kg·m−3) 剪切波速/(m·s−1) 场地类别 11 土层 1 40 0.42 1 820 113 Ⅲ 基岩 6 ∞ 0.20 2 300 500 12 土层 2 40 0.38 1 850 166 Ⅱ 基岩 6 ∞ 0.20 2 300 500 13 土层 3 40 0.35 1 920 210 Ⅱ 基岩 6 ∞ 0.20 2 300 500 14 土层 4 40 0.26 1 920 254 Ⅱ 基岩 6 ∞ 0.20 2 300 500 15 土层 5 40 0.30 1 970 312 Ⅱ 基岩 6 ∞ 0.20 2 300 500 16 土层 5 40 0.30 1 970 360 Ⅱ 基岩 6 ∞ 0.20 2 300 500 17 土层 5 40 0.27 2 100 425 Ⅱ 基岩 6 ∞ 0.20 2 300 500 18 土层 5 40 0.27 2 100 493 Ⅱ 基岩 6 ∞ 0.20 2 300 500 采用等效线性化方法考虑土的非线性特性,从目前较常用的等效线性化分析软件中选择EERA软件进行分析,分析时场地底部采用开放边界,统一在200 m基岩处输入地震动。
2. 地震动及指标的选取
2.1 地震动记录的选取
Dávalos和Miranda (2019)指出仅采用简单的地震动振幅缩放进行结构非线性分析,可能会使得IM与结构地震响应之间的相关性出现偏差;同时,地震记录的选取还要综合考虑工程场地条件并避免对某个地震事件的依赖性。本文从PEER强震记录数据库中选取25个不同地震事件的50条远场地震动记录。到目前为止,对于近远场地震的划分并无统一的规定,通常以断层距作为近远场的划分依据。已有文献给出了不同的划分标准,如20 km (Bray,Rodriguez-Marek,2004),23 km (Akkar,Özen,2005),10 km (FEMA,2009)等,综合考虑后本文选取15 km作为近远场的划分依据。因此,本文所选取地震动记录的断层距均大于15 km,其PGA范围为0.019g—0.229g,PGV范围为0.52—19.07 cm/s,PGD范围为0.07—11.58 cm。所选取地震动的详细信息见表3,相应的伪加速度反应谱如图2所示。
表 3 本研究中使用的地震动记录Table 3. Ground motions records used in this study编号 地震名称 年份 vS30/(m·s−1) 地震动分量 断层距/km PGA/g PGV/(cm·s−1) PGD/cm 1 Kern County 1952 514.99 SBA042 82.19 0.090 11.41 3.43 SBA132 0.132 19.07 5.49 2 Lytle Creek 1970 667.13 DCF090 20.24 0.172 3.57 0.40 DCF180 0.162 6.50 0.99 3 San Fernando 1971 529.09 PPP000 38.97 0.104 4.95 1.26 PPP270 0.138 5.46 1.09 4 Northern Calif-07 1975 518.98 SCP070 63.64 0.074 2.13 0.09 SCP160 0.108 2.28 0.09 5 Livermore-01 1980 517.06 A3E146 30.59 0.065 3.91 0.79 A3E236 0.057 2.68 0.50 6 Anza (Horse Canyon)-01 1980 724.89 PFT045 17.26 0.099 2.04 0.18 PFT135 0.122 5.19 0.59 7 Coalinga-01 1983 522.74 TM2000 42.92 0.026 3.61 1.13 TM2090 0.037 5.72 1.43 8 Taiwan SMART1(25) 1983 671.52 25EO2EW 92.04 0.020 1.45 0.36 25EO2NS 0.020 2.50 0.44 9 Borah Peak_ID-02 1983 612.78 HAU000 49.02 0.029 0.63 0.07 HAU090 0.033 0.52 0.08 10 Morgan Hill 1984 543.63 SJL270 31.88 0.081 7.31 3.74 SJL360 0.070 5.22 2.20 11 Veroia_Greece 1984 551.30 NS 16.89 0.032 3.13 0.26 WE 0.044 3.94 0.35 12 N. Palm Springs 1986 532.85 H01000 54.82 0.054 1.70 0.13 H01090 0.049 1.28 0.16 13 Chalfant Valley-02 1986 529.39 MAM020 36.47 0.042 2.15 0.60 MAM290 0.048 3.17 0.70 14 Taiwan SMART1(45) 1986 671.52 45EO2EW 51.35 0.136 14.42 6.72 45EO2NS 0.142 12.54 6.61 15 Whittier Narrows-01 1987 508.08 PKC000 36.12 0.158 7.73 1.08 PKC090 0.163 7.71 1.08 16 Loma Prieta 1989 517.06 A3E000 52.53 0.079 6.14 4.64 A3E090 0.084 7.07 4.27 17 Griva_Greece 1990 551.30 NS 33.29 0.103 11.03 1.22 WE 0.098 8.69 0.89 18 Cape Mendocino 1992 518.98 SHL000 28.78 0.229 6.92 0.39 SHL090 0.189 6.30 0.52 19 Landers 1992 659.09 SIL000 50.85 0.050 3.76 1.93 SIL090 0.040 5.08 4.04 20 Big Bear-01 1992 509.10 CUC090 59.87 0.051 3.42 0.59 CUC180 0.032 1.95 0.43 21 Northridge-01 1994 572.57 ATB000 46.91 0.046 3.20 1.82 ATB090 0.068 4.16 1.97 22 Kobe_Japan 1995 609.00 CHY000 49.91 0.092 5.32 2.86 CHY090 0.110 4.12 0.97 23 Kozani_Greece-01 1995 579.40 L 49.66 0.019 1.40 0.27 T 0.019 1.49 0.26 24 Hector Mine 1999 724.89 PFT090 89.98 0.036 5.12 1.77 PFT360 0.027 2.30 1.90 25 Duzce_Turkey 1999 782.00 N 25.88 0.053 5.75 5.28 E 0.025 9.98 11.58 2.2 地震动强度指标
研究人员基于不同的标准提出了多种IM,包括单一参数型和复合型。Nau和Hall (1984)指出复合型IM针对地面运动也未能全面反映输入地震动记录对结构损伤程度的影响规律,且复合型指标的计算较为复杂,不便于工程应用,因此形式简单、使用方便的地震动峰值指标仍旧使用较多,故本文选择PGA,PGV和PGD作为研究指标。Riddell (2007)将指标分为加速度相关型、速度相关型以及位移相关型三种,本文选取的三个指标分别作为这三种指标类型的代表。
2.3 工程需求参数
工程需求参数EDP是用来描述结构地震响应及损伤的参数。在基于性能的地震工程计算中,EDP的选取对计算结果的准确性至关重要。对于地上结构,诸如最大层间位移比、最大层间加速度等EDP被广泛应用(Luco,Cornell,2007;Padgett et al,2008;Yang et al,2009)。而针对地下结构的EDP目前尚无统一标准,多项研究选择了各种各样的结构地震响应进行地下结构的评价分析(An et al,1997;Liu et al,2017;钟紫蓝等,2020),但地下结构的最大层间位移被广泛应用。因此,本文选择矩形地下结构(结构高度为7 m)顶底板处对应场地的最大水平位移差作为场地的EDP,埋深设定为结构顶板到地表的距离,如图3所示。因地下结构的响应受到周围场地变形的控制,该EDP的选择有一定的代表性。
3. 最优地震动强度指标的评价
3.1 有效性
有效性可以描述在确定的地震动强度指标IM下响应的离散程度,即在确定的IM下,EDP的离散性较小,有效性较好,此时,可以在不降低精度的情况下减少计算时输入地震动记录的数量和动力时程分析的次数(Luco,Cornell,2007)。Cornell等(2002)指出EDP与IM之间大致满足幂函数关系,可以写为对数线性关系,即
$$ \ln {\rm{EDP}} {\text{=}} \ln a {\text{+}} b\ln {\rm{IM}}{\text{.}} $$ (1) 对计算结果进行线性回归,可得常数a和b的值,进而求得代表有效性的标准差β
$$ \beta {\text{=}} \sqrt {\frac{{\displaystyle\sum\limits_{i {\text{=}} 1}^n {{{{\text{[}} \;{\ln {{\rm{ED}}{{\rm{P}}_{i}}} {\text{-}} \ln ( {a \cdot {\rm{I}}{{\rm{M}}^{b}_{i}}} {\text{)}}} {\text{]}}}^2}} }}{{n {\text{-}} 2}}} {\text{,}} $$ (2) 式中,EDPi为每条地震动下的场地响应值,IMi为每条地震动的指标值,n为地震动数量。有效性越好,β越小。如图4所示,PGV的有效性优于PGA。
3.2 实用性
实用性是指EDP与IM之间是否存在直接关系,如果某IM实用性不强,则表明EDP几乎不受该IM变化的影响。实用性采用式(1)中的线性回归常数b来判断,b值越大,地面运动强度指标变化对EDP的影响就越大,即实用性较高。如果b值趋于0,则IM的变化对EDP无影响。由图4可见PGA比PGV的实用性更强。
3.3 效益性
只使用有效性或实用性来评价IM可能会出现相互矛盾的情况,如图4所示,基于有效性评价,PGV的有效性优于PGA,而基于实用性评价,PGA的实用性优于PGV。效益性综合考虑有效性和实用性(Padgett et al,2008),采用
$$ \zeta {\text{=}} \frac{\beta }{b} $$ (3) 表示,ζ值越小表示IM的效益性越强。本文以效益性作为IM的评价准则。
4. 计算结果与讨论
通常地下结构响应受控于周围岩土体的变形,所以从简单场地开始探索规律。本文将设计均匀半空间和成层半空间两类场地展开规律的探究,对均匀半空间场地先粗略地取0,2,5,7,10,13,15,18,20,25,30,35,40,60 m等14个埋深进行研究,由此获得效益性结果随埋深的变化曲线。
4.1 最优IM转折位置
4.1.1 均匀半空间场地
图5为10个场地的效益性随埋深的变化曲线,可以看到:对于剪切波速较小的场地1,所有埋深下PGV均为最优IM;对于剪切波速相对较大的场地2—10,在埋深浅时PGA为最优IM,埋深较深时PGV为最优IM,因此存在一个随埋深增加最优IM由PGA转变为PGV的转折深度。为了更准确地确定转折深度,在转折深度附近每隔1 m取一个埋深值加密计算。
图 5 均匀半空间场地1—10中效益性ζ随埋深变化图(a) 场地1;(b) 场地 2;(c) 场地 3;(d) 场地 4;(e) 场地 5;(f) 场地 6;(g)场地 7;(h) 场地 8 ;(i) 场地 9;(j) 场地 10Figure 5. The proficiency ζ varying with burial depth in homogeneous half-space sites 1−10(a) Site 1;(b) Site 2;(c) Site 3;(d) Site 4;(e) Site 5;(f) Site 6;(g) Site 7;(h) Site 8;(i) Site 9;(j) Site 10存在上述转折现象的原因可能是由于埋深较浅时,场地响应受惯性力的影响较大,因此PGA为最优IM;随着埋深增加,场地响应受土体剪切变形控制,而场地土体剪应变与PGV具有相关性,因此埋深较深时PGV为最优IM。
4.1.2 成层半空间场地
成层半空间场地的埋深取值与均匀半空间场地一致。图6为场地11—18的效益性随埋深的变化曲线。从图中可以看到:对于剪切波速较小的场地11,所有埋深下PGV均为最优IM;对于剪切波速相对较大的场地12—18,在埋深浅时PGA为最优IM,埋深较深时PGV为最优IM,存在一个随埋深增加最优IM由PGA转变为PGV的转折深度,规律与均匀半空间场地相同。
4.2 IM转折深度与场地剪切波速的关系
从图5和图6可以看到,在均匀半空间和成层半空间场地中,不同场地条件下最优IM的转折深度不同。图7给出了两种场地类型下最优IM的转折深度随场地剪切波速变化的关系,两者的线性回归曲线也绘于图中。
$$ H{\text{=}}\left\{\begin{array}{c}0.06{v}_{{\rm{S}}}{\text{-}}5.27\qquad ({\text{均匀半空间}}) \\ 0.06{v}_{{\rm{S}}}{\text{-}}9.00\qquad ({\text{成层半空间}})\end{array}\right. $$ (4) 为两种场地的线性回归方程,式中H为转折深度,vS为场地剪切波速。
从图7可以看到,最优IM的转折深度与场地剪切波速较好地符合线性关系,因此可用回归方程计算其它剪切波速大于100 m/s的均匀半空间场地以及本文涉及的成层半空间场地的最优IM转折深度。从图中还可看出,均匀半空间场地中的线性拟合优于成层半空间场地,这可能是由于成层半空间引入了阻尼和覆盖层厚度等参数,对其产生了一定的影响。
5. 结论
本文基于从PEER中获取的实际地震动,采用EERA软件计算得到均匀半空间场地、成层半空间场地不同埋深处的水平位移差,利用效益性评价了地震动峰值指标(PGA,PGV,PGD)随埋深的变化规律,得到以下结论:
1) 最优IM随埋深变化,个别波速较小场地的最优IM始终为PGV;大多数场地下,随着埋深增加出现最优IM由PGA转向PGV的转折深度。本文研究场地条件下的转折深度范围为0—25 m。
2) 最优IM的转折深度与场地剪切波速存在线性关系。均匀半空间场地的转折深度与回归直线相差0—1.1%,成层半空间场地的相差2.64%—18.75%。
本文将场地水平位移差作为EDP,后续研究中应考虑将结构响应作为EDP进行研究;同时实际场地的覆盖层厚度各不相同,后续将考虑不同的覆盖层厚度展开研究。
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图 4 大气对流层延迟校正及长波趋势相位校正
(a,b) 基于ERA5模型去除升、降轨对流层延迟误差后的图像;(c,d) 长波趋势相位校正后的图像,其中蓝色方框表示本研究的形变区
Figure 4. Atmospheric troposphere delay correction and long wavelength trend phase correction
(a,b) Images after removing tropospheric delay errors in ascending and descending orbits based on the ERA5 model, respectively;(c,d) Images after long wavelength trend phase correction,where blue boxes denote the deformation area of this study
图 1 四川盆地构造背景及地震活动性时空分布
(a) 四川盆地地震构造和1970年之后的地震分布,地震目录数据来源于国家地震科学数据中心(2021),GPS数据来源于Wang和Shen (2020)
Figure 1. Tectonic settings of Sichuan basin and spatio-temporal distribution of its seismicity
(a) Seismotectonics of Sichuan basin and earthquake distribution since 1970,where earthquake catalog from National Earthquake Data Center (2021),GPS data from Wang and Shen (2020)
图 1 四川盆地构造背景及地震活动性时空分布
(b) 2009年以来威远和长宁地区地震的空间分布及M4以上地震的震源机制解(GCMT,2021),其中红色震源机制球代表疑似采盐注水引起的地震事件,蓝色代表疑似水力压裂引起的事件,黑色代表天然地震;(c) 长宁页岩气开采区块附近褶皱迹线和地表断层分布;(d) 2009年以来长宁区块M>0地震的时间演化图
Figure 1. Tectonic settings of Sichuan basin and spatio-temporal distribution of its seismicity
(b) Spatial distribution of earthquakes in Weiyuan and Changning areas since 2009 and focal mechanisms of earthquakes larger than M4 (GCMT,2021),where red beach balls represent seismic events suspected to be caused by water injection and salt extraction,blue ones represent events suspected to be caused by hydraulic fracturing,and black ones represent natural earthquakes;(c) Fold traces and surface faults around Changning shale gas block. Solid black lines are Changning anticline and Jianwu syncline;(d) Evolution of M>0 earthquakes in Changning block since 2009
图 2 功率谱滤波后的ALOS-2差分干涉相位结果
(a) 升轨ScanSAR模式差分干涉图,成像时间为2016年8月7日至2019年9月15日;(b) 降轨StripMap模式差分干涉图,成像时间为2017年6月12日至2019年7月8日
Figure 2. ALOS-2 differential interferometry phases with power spectrum filtering
(a) Differential interferogram in ascending orbit with ScanSAR mode,imaging from August 7,2016 to September 15,2019; (b) Differential interferogram in descending orbit with StripMap mode,imaging from June 12,2017 to July 8,2019
图 3 利用距离向信号频谱分割法估计电离层延迟相位
(a) 升轨ScanSAR模式图像的电离层相位估计结果;(b) 降轨StripMap模式图像的电离层相位估计结果;(c) 升轨ScanSAR模式图像去除电离层相位的缠绕相位;(d) 降轨StripMap模式图像去除电离层相位的缠绕相位
Figure 3. Estimation of the ionospheric phase delay by range split-spectrum method
(a) Ionospheric phase estimated from ascending orbit image with ScanSAR mode;(b) Ionospheric phase estimated from descending orbit image with StripMap mode;(c) Wrapped phase estimated from ascending orbit image with ScanSAR mode after removing ionospheric phase;(d) Wrapped phase estimated from descending orbit image with StripMap mode after removing ionospheric phase
图 5 基于长宁页岩气开发区Sentinel-1雷达数据得到的升轨(a)和降轨(b) PS-InSAR线性速度场
图中黑点表示该区块中已知页岩气井的空间分布
Figure 5. PS-InSAR linear velocity field in ascending (a) and descending (b) orbits obtained from Sentinel-1 radar data around Changning shale gas block
The black dots indicate spatial distribution of known shale gas wells in Changning shale gas block
图 6 长宁页岩气区块近场ALOS-2干涉形变位移场及剖面图
长宁地震序列和水力压裂致震的震源机制解来源于Lei等(2019a),其余2015年和2017年的两次地震的震源机制解来源于GCMT (2021);白色虚线框表示2019年6月17日长宁地震形变场(a) 升轨ScanSAR模式图像得到的页岩气区块形变位移场,成像间隔为3年;(b) 降轨StripMap模式图像得到的页岩气区块形变位移场,成像间隔为2年;(c) 图(a)中的AA′和图(b)中的BB′形变位移场剖面,两剖面在同一位置
Figure 6. ALOS-2 interferometry displacement field and profiles in the near field of Changning shale gas block
The focal mechanism solution of the Changning earthquake sequence and hydraulic fracturing are from Lei et al (2019a),the remaining two earthquakes in 2015 and 2017 are from GCMT (2021). The white dashed box represents the deformation field of the Changning earthquake occurred on June 17,2019 (a) Deformation displacement field of shale gas block obtained from ascending orbit data in ScanSAR mode,and the imaging interval is three years;(b) Deformation displacement field of shale gas block obtained from descending orbit data in StripMap mode,and the imaging interval is two years; (c) Deformation displacements on the profiles AA′ in Fig. (a) and BB′ in Fig. (b),and the two profiles are at the same location
图 7 长宁页岩气区块近场升降轨Sentinel-1数据的LOS向线性速度场
图(a)和(b)中KK′为图8a中二维地震反射剖面位置,OO′为图8b中断层破碎带的北界;图(c)中红色直线为线性速度模型拟合的各点位移。(a) 升轨速度场;(b) 降轨速度场;(c) 图(a)和图(b)中P1,P2,P3和P4点的位移时间序列;(d) 升轨数据剖面CC′和降轨数据剖面DD′上的形变速率变化
Figure 7. Linear velocity field of Sentinel-1 data in LOS direction in the near field of Changning shale gas block
In Figs. (a) and (b) KK′ is the location of the two-dimensional seismic reflection profile in Fig. 8a,and OO′ is the north boundary of a fault fracture zone in Fig. 8b;in Fig. (c) the red straight lines are the displacements of each point by linear velocity fitting. (a) Velocity field in ascending orbit;(b) Velocity field in descending orbit;(c) The displacement time series of points P1,P2,P3 and P4 in Figs. (a) and (b),respectively;(d) Variation of deformation rates on the profile CC′ in ascending orbit and profile DD′ in descending orbit
图 8 跨越长宁开采区的二维地震反射剖面
(a) KK′剖面(图7)对应的地层结构和近年来长宁附近发生的较大地震事件及其震源机制解(Li et al,2021);(b) 图7d形变剖面中15—17 km处断层破碎带附近的二维地震反射剖面,其位置见图1c;(c) 长宁地区的沉积地层序列(Li et al,2021)
Figure 8. Two-dimensional seismic reflection profile across the Changning shale gas block
(a) The stratigraphic structure corresponding to the profile KK′ (Fig. 7) and several large-magnitude events near Changning area in recent years and their focal mechanism solutions (Li et al,2021);(b) The two-dimensional seismic reflection profile near a fault fracture zone at 15−17 km of the deformation profile in Fig. 7d,and the location of the profile is shown in Fig. 1c;(c) Sedimentary stratigraphic sequence in Changning area (Li et al,2021)
图 9 MS≥5.0地震引起的地表形变与页岩气开采区形变的关系
(a) 2017年6月12日至2019年7月8日期间的ALOS-2降轨页岩气区块形变场,图中矩形A和B分别为珙县地震和兴文地震引起的地表形变,区域C为页岩气开采引起的地表形变,地震定位结果来自Lei等(2019b),H18井位置源于本研究实地野外调查;(b) 2018年12月30日至2019年1月11日期间的Sentinel-1 LOS向InSAR形变图
Figure 9. The relationship between the surface deformation caused by the MS≥5.0 earthquakes and the deformation of shale gas exploitation
(a) ALOS-2 descending deformation field of shale gas block from June 12,2017 to July 8,2019,where the rectangles A and B are the surface deformation caused by the Gongxian and Xingwen earthquakes,C is the surface deformation caused by shale gas exploitation,earthquake location results are from Lei et al (2019b),and the location of well H18 is from our field investigation; (b) Sentinel-1 LOS InSAR deformation map from December 30,2018 to January 11,2019
表 1 本研究所用ALOS-2 PALSAR数据的参数
Table 1 ALOS-2 PALSAR data parameters used in this study
主景日期 从景日期 入射角/° 卫星方向角/° 轨道 垂直基线/m 2016-08-07 2019-09-15 39 −10.2 升轨(146) 75.7 2017-06-12 2019-07-08 40 −169.9 降轨(37) −27.6 -
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