基于粒子群算法的四川长宁地区印支构造界面反演

doi:10.3969/j.issn.0253-4967.2023.01.010

地震地质 ›› 2023, Vol. 45 ›› Issue (1): 172-189.DOI: 10.3969/j.issn.0253-4967.2023.01.010

基于粒子群算法的四川长宁地区印支构造界面反演

刘奕均¹⁾^,³⁾(), 杨光亮¹⁾^,²⁾^,³⁾^,^*(), 王嘉沛¹⁾^,³⁾, 谈洪波¹⁾^,³⁾, 周怀斌²⁾, 申重阳¹⁾^,³⁾

1)中国地震局地震研究所, 中国地震局地震大地测量重点实验室, 武汉 430071
2)防灾科技学院, 廊坊 065201
3)湖北省地震局, 武汉 430071

收稿日期:2022-02-16 修回日期:2022-10-05 出版日期:2023-02-20 发布日期:2023-03-24
通讯作者: * 杨光亮, 男, 1980年生, 副研究员, 主要从事重力探测与地球动力学相关研究, E-mail: 3193459@qq.com。
作者简介:刘奕均, 男, 1998年生, 现为中国地震局地震研究所固体地球物理学专业硕士研究生, 研究方向为重力反演, E-mail: liuyijun202@mails.ucas.ac.cn。
基金资助:
国家自然科学基金(42174104);国家自然科学基金(U1939204);国家自然科学基金(41204014);湖北省自然科学基金(2022CFB350)

INVERSION OF INDOSINIAN SURFACE IN CHANGNING, SICHUAN BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

LIU Yi-jun¹⁾^,³⁾(), YANG Guang-liang¹⁾^,²⁾^,³⁾^,^*(), WANG Jia-pei¹⁾^,³⁾, TAN Hong-bo¹⁾^,³⁾, ZHOU Huai-bin²⁾, SHEN Chong-yang¹⁾^,³⁾

1)Key Laboratory of Earthquake Geodesy, Institute of Seismology, China Earthquake Administration, Wuhan 430071, China
2)Institute of Disaster Prevention, Langfang 065201, China
3)Hubei Earthquake Agency, Wuhan 430071, China

Received:2022-02-16 Revised:2022-10-05 Online:2023-02-20 Published:2023-03-24

摘要/Abstract

摘要：

为减少密度界面重力反演的非唯一性, 文中对经典粒子群算法的初值模型和参数设定进行优化, 并通过理论模型验证其有效性。基于该改进算法, 采用长宁科考的多条实测重力剖面数据反演计算了长宁地区印支密度界面的深度, 并结合界面起伏形态分析该地区的构造特征及其与地震的关系。研究结果表明, 经优化的粒子群算法全局搜寻最优解的性能稳定, 深度误差更小。对长宁地区印支密度界面的反演显示, 该界面总体呈现中间隆起、四周凹陷的特征, 深度介于0.3~3.3km, 与前人的结果基本一致, 文中所得结果的细节更精细。研究区东侧界面的凹陷程度显著大于西侧, 界面隆起部分对应长宁-双河复式大背斜, 深度介于0.3~1.9km, 背斜核部受到构造运动的抬升侵蚀作用导致古老地层出露地表。大背斜北翼处的界面较南翼陡峻, 呈条带状分布的北翼浅层地震发震位置与界面起伏具有高相关性, 地震多发生在印支界面剧烈起伏处; 呈团状分布的南翼浅层地震发震位置处的印支界面存在明显凹陷。文中的反演结果为该地区地震构造环境研究提供了基础信息, 也是后续多层密度界面模型的重要参考。

关键词: 长宁地区, 粒子群算法, 印支界面, 重力反演

Abstract:

The gravity inversion results of three-dimensional density interface are often not unique, which brings some difficulties to further scientific research. The classical particle swarm optimization algorithm has a higher global extremum search ability, faster inversion speed in computing high-dimensional nonlinear inversion problems, and the final solution is independent of the initial model compared with traditional inversion density interface algorithms such as L-M, Tikhonov regularization, Gauss-Newton method, etc. However, in classical particle swarm optimization, the initial model setting and parameter selection are not perfect. Therefore, this paper further enhances the algorithm based on the classical particle swarm optimization algorithm, referring to the previous optimization ideas. The test results of various models show that the optimized particle swarm optimization algorithm has a stable ability to search for the optimal global solution, and the depth error is smaller. In addition, if we adopt parallel computing, the inversion speed can be effectively improved.

We obtained the Indosinian density interface depth model of the Changning area by inversion using multiple measured high-density gravity profile data based on the improved algorithm. The overall scope of the survey area is small and diamond-shaped, including the complete Changning-Shuanghe anticline and some surrounding synclines. The inversion results show that the Indosinian density interface generally presents the characteristics of uplift in the middle and depressions around it, and the depth range is 0.3~3.3km, which is basically consistent with the inversion results of the drilling data and previous gravity data, and the details are more prominent. It can better express its structural characteristics. The depression degree of the interface on the right side is significantly larger than that on the left side. The uplift part corresponds to the Changning-Shuanghe complex large anticline, and the depth varies from 0.3km to 1.9km. The core of the anticline is exposed to the surface by uplifting and erosion of the tectonic movement. The inversion result provides essential information for studying the seismotectonic environment and is also a vital reference for studying the multi-layer density interface model.

Density interface fluctuation is the product and sign of a specific area under the action of multi-stage tectonic movement, which plays an essential role in studying basin basement, regional structure, and deep structural fluctuation. It provides critical information for the analysis of the origin of earthquakes. Therefore, we analyzed the structural characteristics of this area and its relationship with earthquakes combined with the undulating morphology of the Indosinian surface. Earthquakes in the Changning area are concentrated on the north and south sides of the large anticline. The seismic distribution pattern and focal parameters on both sides are obviously different. The main reason for this phenomenon is that there are significant differences in the causes of earthquakes. The Indosinian surface in the north wing of the anticline is steeper than that in the south wing. The location of the strip distributed shallow earthquakes in the north wing is highly related to the fluctuation of the Indosinian surface, and they mainly occur at the places where the Indosinian surface fluctuates violently. The local density changes drastically, and the earthquakes’ occurrence is greatly affected by hidden faults. The clumped distributed shallow earthquakes in the south wing occur at locations where there is an apparent depression on the Indosinian surface, which may be caused by shale gas exploitation, and the earthquakes are more affected by local stress changes. Deep earthquakes may be closely related to the revival of basement faults. There may still be seismic risk in the northeast wing of the large anticline in the future.

In general, the optimized particle swarm algorithm has achieved good results in both model testing and practical applications. In order to further improve the accuracy of the inversion results, we will focus on improving the applicability of the algorithm in various situations and the ways of adding multiple constraint information. More detailed geophysical research should be carried out in this area, which will help to better understand its crustal structure, earthquake mechanism, geological structure, and the development of earthquake prevention and disaster reduction.

Key words: Changning area, PSO, Indosinian surface, gravity inversion

中图分类号:

P315.726

刘奕均, 杨光亮, 王嘉沛, 谈洪波, 周怀斌, 申重阳. 基于粒子群算法的四川长宁地区印支构造界面反演[J]. 地震地质, 2023, 45(1): 172-189.

LIU Yi-jun, YANG Guang-liang, WANG Jia-pei, TAN Hong-bo, ZHOU Huai-bin, SHEN Chong-yang. INVERSION OF INDOSINIAN SURFACE IN CHANGNING, SICHUAN BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM[J]. SEISMOLOGY AND GEOLOGY, 2023, 45(1): 172-189.

图/表 10

图1 利用PSO算法反演密度界面的流程图

Fig. 1 Flow chart of inversion of density interface by PSO algorithm.

图2 不加噪算法检验 a 深度模型设定; b 模拟实际布格重力异常分布; c 剩余重力异常分布; d 初始深度模型计算; e 最佳深度模型; f 深度误差

Fig. 2 No-noise algorithm test.

表1 模型密度差的横纵向分配

Table1 Horizontal and vertical distribution of density contrast of the synthetic model

X(0~3000m)		X(3000~6000m)
深度/m	密度差/kg·m^-3	深度/m	密度差/kg·m^-3
0	-580	0	-600
100	-580	110	-600
150	-540	150	-570

图3 加噪算法检验 a 模拟实际布格重力异常分布; b 剩余重力异常分布; c 最佳深度模型; d 深度误差

Fig. 3 Noise algorithm test.

图4 实测点位的分布及测区的布格重力异常

Fig. 4 The distribution of observation points and Bouguer gravity anomaly in the survey area.

图5 剩余重力异常

Fig. 5 Residual gravity anomaly.

表2 反演所需参数设置

Table2 Set parameters required for inversion

密度差	网格大小	粒子数	迭代次数
-160kg/m³	2km×2km	100	60

图7 长宁地区印支界面的反演结果(二维) a 长宁地区印支界面的深度; be 长宁地区所截取的4条剖面切片。背斜、向斜及断层的位置分布参考文献(常祖峰等, 2020; 孙权等, 2021)。地震数量分布的热力图数据来自国家地震科学数据中心, 选取自2019年6月17日起2a内发生在该地区的地震。地表高程数据来源于ASTER GDEM v3。长宁-双河大背斜北翼的精定位地震数据由易桂喜等(2019)提供, 南翼选取自2019年6月17日起2a内发生在该区域的地震(龙锋, 私人通讯)进行绘图。图7a中黄色加粗虚线为推测的隐伏断裂的大致位置, 红色五角星自北向南依次表示长宁 MS6.0 地震、珙县 MS5.1 地震、长宁 MS5.3 地震和珙县 MS5.4 地震。图be中蓝色圆形代表震级在0~1的地震, 红色圆形指示 1~2级地震, 绿色星形指示2~3级地震, 紫色星形指示震级>3级的地震

Fig. 7 Inversion results of the Indosinian unconformity in the Changning area(2D).

图6 北翼浅层地震发育示意图

Fig. 6 Schematic diagram of shallow earthquakes development in the north wing.

图8 长宁地区印支界面的反演结果及地震位置分布(三维) a 震源深度为0~3.5km的地震分布; b、 c 发生在此地区的所有地震的位置分布。反演图像包含外推结果; 地震位置信息来自国家地震科学数据中心, 选取自2019年6月17日起2a内发生在该地区的地震, 图例斜杠左侧文字为图a中的符号说明, 右侧为图b、 c中的符号说明; 灰点组成的椭球为页岩气开采的大致位置

Fig. 8 Inversion results of Indosinian unconformity and regional earthquake distribution in Changning area(3D).

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基于粒子群算法的四川长宁地区印支构造界面反演

INVERSION OF INDOSINIAN SURFACE IN CHANGNING, SICHUAN BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

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