基于浅地层剖面的海底浅表层沉积物物理性质参数反演技术研究——以渤海海底管线路由区为例

黄必桂; 李家钢; 周庆杰; 李西双; 刘乐军; 高珊; 周航; 张承艺

基于浅地层剖面的海底浅表层沉积物物理性质参数反演技术研究——以渤海海底管线路由区为例

1.
中海油研究总院有限责任公司，北京 100028
2.
自然资源部第一海洋研究所，山东青岛266061

基金项目: 基于地球物理数据的工程地质研究(YXKY-2018-ZY-10)；中央级公益性科研院所基本科研业务费专项资金 (2021Q03)

详细信息

作者简介:
黄必桂（1984-），男，高级工程师，主要从事海洋工程环境条件及设计标准方面的研究。E-mail: huangbg3@cnooc.com.cn

通讯作者:
周庆杰（1989-），男，工程师，主要从事海洋地球物理数据处理及地质灾害风险评估等研究。E-mail: zhouqj@fio.org.cn

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出版历程
- 收稿日期: 2021-12-29
- 修回日期: 2022-04-05
- 网络出版日期: 2022-05-16

Research on inversion technology of physical properties parameters of seafloor sediments based on sub-bottom profile- Taking the Bohai Sea submarine pipeline route as an example

1.
CNOOC Research Institute Co. Ltd., Beijing 100028, China
2.
First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China

摘要

摘要: 海底浅表层（小于1 m）沉积物的物理性质，如粒度、孔隙度、密度等是海洋沉积学研究和海洋工程地质分析的重要内容，而对于这些物理性质的获取目前主要基于有限的海底取样或原位测试。浅地层剖面是基于声学信号（频率几千赫兹）在沉积物中的传播得到可反映沉积地层结构的数据，其中的一些声学参数，如海底反射系数、波阻抗等与沉积物物理性质密切相关。如何充分而有效的利用浅地层剖面资料，反演得到剖面覆盖区海底浅表层沉积物的物理性质参数，极具科学意义和应用价值，且基于声学属性反演沉积物物理性质是当前研究的热点。为此，本文基于渤海LD16-3CEPA至LD10-1PAPD路由段的浅地层剖面数据和海底表层沉积物的实测物理参数，利用Biot-Stoll模型建立研究区海底反射系数和沉积物物理性质之间的关系，并基于浅地层剖面数据计算得到的海底反射系数，反演了研究区海底浅表层沉积物的孔隙度、密度、平均粒径等物理性质参数。其中反演的孔隙度、密度、平均粒径与实测孔隙度、密度、平均粒径基本相符，偏差度基本都在20%的偏差范围内，表明该反演方法在该区的应用是可行的。
- 浅地层剖面 /
- Biot-Stoll模型 /
- 海底反射系数 /
- 沉积物物理性质 /
- 渤海海域
Abstract: The physical properties of seafloor sediments (less than 1 m), such as particle size, porosity and density, are an important part of marine sedimental research and marine engineering geological analysis. The acquisition of these physical properties is currently based on limited seabed sampling or in-situ testing. The sub-bottom profile is based on the propagation of acoustic signals (frequencies in thousands of Hertz) in sediments to obtain the data that can reflect the sedimentary stratigraphic structure. Some of the acoustic parameters, such as seabed reflection coefficient and wave impedance, are closely related to the physical properties of sediments. How to make full and effective use of the sub-bottom profile data to retrieve the physical property parameters of the seafloor sediments in the profile overlying area is of great scientific significance and application value. Moreover, inversion of the physical properties of sediments based on acoustic properties is a hot research topic at present. Therefore, in this paper, the Biot-Stoll model is used to establish the relationship between the seabed reflection coefficient and the physical properties of the sediments in the study area based on the measured physical parameters of the seafloor sediments from LD 16-3CEPA to LD10-1PAPD routing section of the Bohai Sea. Based on the seabed reflection coefficient calculated from the sub-bottom profile data, the physical property parameters such as porosity, density and mean grain size of the seabed sediment in the study area are retrieved. The porosity, density and mean grain size of the inversion are basically consistent with the measured, and the deviation degree is basically within the range of 20%, indicating that the application of the inversion method in this area is feasible.
- sub-bottom profile /
- Biot-Stoll model /
- seafloor reflection coefficient /
- physical properties of sediments /
- Bohai Sea

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图 1 研究区位置及浅剖与取样站位分布

Fig. 1 Location of study area and distribution of sub-bottom profiles and sampling station

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图 2 浅地层剖面频谱分析特征

Fig. 2 Spectral analysis feature of sub-bottom profile

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图 3 对数分解法求取子波的过程图解

Fig. 3 Process diagram of wavelet extraction by logarithmic decomposition method

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图 4 典型浅地层剖面图及该剖面计算得到的海底反射系数

Fig. 4 Typical sub-bottom profile and the calculated seabed reflection coefficients

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图 5 海底反射系数与沉积物物理性质的相关关系

a. 纵波速度随频率的变化；b. 反射系数随孔隙度的变化（f=5 kHz）；c.反射系数随密度的变化（f=5 kHz）；d.反射系数随平均粒径的变化（f=5 kHz）

Fig. 5 Correlation between seafloor reflection coefficient and sediment physical properties

a. Variation of p-wave velocity with frequency; b. variation of reflection coefficient with porosity ( f = 5 kHz); c. variation of reflection coefficient with density ( f = 5 kHz); d. variation of reflection coefficient with mean grain size ( f = 5 kHz)

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图 6 海底表层沉积物物性反演结果与取样测试结果对比

a. 平均粒径；b. 海底反射系数；c. 孔隙度；d. 密度；图中坐标为TM投影，中央经线120°E

Fig. 6 Comparison between inversion results and sampling test results of seafloor surface sediment physical properties

a. Mean grain size; b. seafloor reflection coefficient; c. porosity; d. density; the coordinates in the figure are TM projection and the central meridian is 120°E

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图 7 反演结果与样品测试结果对比

Fig. 7 Comparison between inversion results and sample test results

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表 1 海底浅表层沉积物物理性质

Tab. 1 Physical properties of seabed shallow surface sediments

站位	经度	纬度	密度/（g·m^-3)	平均粒径/ɸ	孔隙度
PL3	120.464 40°E	39.492 31°N	1 636.73	6.56	0.68
PL4	120.476 53°E	39.518 09°N	1 582.65	6.94	0.70
PL5	120.493 21°E	39.537 46°N	1 575.51	—	—
PL6	120.500 19°E	39.568 55°N	1 468.37	7.49	0.73
PL7	120.513 81°E	39.593 29°N	1 597.96	7.25	0.72
PL8	120.524 32°E	39.619 35°N	1 536.73	7.06	0.71
PL9	120.536 22°E	39.644 64°N	1 657.14	7.48	0.73
PL10	120.546 00°E	39.661 17°N	1 674.49	6.78	0.69
PL11	120.554 16°E	39.678 54°N	1 601.02	7.08	0.71
PL12	120.560 21°E	39.695 24°N	1 595.92	6.81	0.70
PL13	120.570 56°E	39.716 87°N	1 728.57	6.64	0.69
PL14	120.575 45°E	39.723 59°N	1 771.43	6.39	0.67
PL15	120.579 86°E	39.732 96°N	1 679.59	6.08	0.66
PL16	120.590 03°E	39.754 23°N	1 682.65	6.27	0.67
PL17	120.597 98°E	39.771 02°N	1 628.57	6.23	0.67

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表 2 Biot-Stoll模型输入的沉积物物理参数

Tab. 2 The input sediment physical parameters of the Biot-Stoll model

参数	Biot-Stoll模型取值
颗粒密度$ {\rho }_{g}/（kg/{m}^{3}) $	2 708
孔隙度$ n $	0.45~0.85
孔隙曲折度$ \alpha $	$ \alpha = \left\{ {\begin{array}{*{20}{l}} {1.35}&{\varphi \leqslant 4} \\ {{{ - }}0.3 + 0.4125\varphi }&{4 < \varphi < 8} \\ {3.0}&{\varphi \geqslant 8} \end{array}} \right. $	$ \varphi = {{ -{\rm{ lo}}}}{{{{\rm{g}}}}_2}d $，$ \varphi $为中值粒径(单位：)，d为颗粒直径（单位：mm）
渗透率$ \kappa /{m^2} $	$ \kappa = \dfrac{{{d^2}{n^3}}}{{180{{(1 - n)}^2}}}\dfrac{1}{{\sqrt {10} }} $
海水动力黏度$ \eta /(Pa \cdot s) $	0.001
颗粒体积模量$ {K_g}/Pa $	3.2×10¹⁰
海水体积模量$ {K_w}/Pa $	2.395×10⁹
海水密度$ {\rho }_{w}/（kg/{m}^{3}) $	102 3
框架剪切模量$ {\mu _0}/Pa $	${\mu _0} = 1.835 \times {10^5}{\left(\dfrac{n}{ {1 - n} }\right)^{ - 1.12} }\sqrt { {\tau _a}(z)}$ $ {\tau _a}(z) = (1 - n)({\rho _s} - {\rho _f})gz $，式中，$ {\tau _a}(z) $为沉积物平均有效压力；重力加速度$ g = 9.8m \cdot {s^{ - 2}} $；为颗粒密度；为孔隙流体密度；z为沉积层厚度（单位：m）
框架体积模量$ {K_0}/Pa $	$ {K_0} = \dfrac{{2{\mu _0}(1 + \sigma )}}{{3(1 - 2\sigma )}} $ ，式中，$ \sigma $为沉积物骨架的泊松比
孔隙大小$ a $	$ a = \dfrac{d}{3}\dfrac{n}{{1 - n}}\dfrac{1}{{1.8}} $
体积对数衰减$ {\delta _f} $	$ {\delta _f}({z_s}) = {\delta _f}({z_0})\sqrt {{\raise0.7ex\hbox{${{z_0}}$} \mathord{\left/ {\vphantom {{{z_0}} {{z_s}}}}\right.}\lower0.7ex\hbox{${{z_s}}$}}} $，式中，z₀，z_s分别为浅部沉积物深度

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表 3 反演结果与取样测试数据对比信息

Tab. 3 Comparison information between inversion results and sampling test data

站位	经度	纬度	样品孔隙度	反演孔隙度	偏差度/%	样品密度	反演密度	偏差度/%	样品平均粒径	反演平均粒径	偏差度/%
PL3	120.464 40°E	39.492 31°N	0.683	0.625	–8.37	1 636.73	1 623.65	–0.80	6.56	5.58	–14.91
PL4	120.476 53°E	39.518 09°N	0.701	0.634	–9.64	1 582.65	1 611.62	1.83	6.94	5.73	–17.46
PL6	120.500 19°E	39.568 55°N	0.727	0.711	–2.18	1 468.37	1 507.18	2.64	7.49	7.24	–3.44
PL7	120.513 81°E	39.593 29°N	0.716	0.724	1.15	1 597.96	1 477.96	–7.51	7.25	7.54	3.99
PL8	120.524 32°E	39.619 35°N	0.707	0.779	10.15	1 536.73	1 416.86	–7.80	7.06	8.69	22.97
PL9	120.536 22°E	39.644 64°N	0.727	0.796	9.54	1 657.14	1 394.14	–15.87	7.48	9.06	21.14
PL10	120.546 00°E	39.661 17°N	0.694	0.775	11.74	1 674.49	1 418.37	–15.30	6.78	8.60	26.74
PL11	120.554 16°E	39.678 54°N	0.708	0.780	10.10	1 601.02	1 414.50	–11.65	7.08	8.71	22.98
PL12	120.560 21°E	39.695 24°N	0.695	0.756	8.79	1 595.92	1 439.56	–9.80	6.81	8.19	20.23
PL13	120.570 56°E	39.716 87°N	0.687	0.751	9.29	1 728.57	1 450.71	–16.07	6.64	8.09	21.79
PL14	120.575 45°E	39.723 59°N	0.674	0.737	9.27	1 771.43	1 461.70	–17.48	6.39	7.78	21.77
PL15	120.579 86°E	39.732 96°N	0.658	0.745	13.26	1 679.59	1 455.37	–13.35	6.08	7.95	30.83
PL16	120.590 03°E	39.754 23°N	0.668	0.747	11.84	1 682.65	1 458.80	–13.30	6.27	7.95	26.70
PL17	120.597 98°E	39.771 02°N	0.666	0.722	8.41	1 628.57	1 489.09	–8.56	6.23	7.46	19.80

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