流量变化控制的辫状河心滩演化过程

刘警阳; 李伟; 赵文智; 岳大力; 束青林; 王武荣; 高建; 侯秀林; 吴胜和

doi:10.3799/dqkx.2023.143

流量变化控制的辫状河心滩演化过程

doi: 10.3799/dqkx.2023.143

刘警阳^{1, 2, ,},
李伟^{1, 2},
赵文智^{1, 2, 3},
岳大力^{1, 2, ,},
束青林⁴,
王武荣^{1, 2},
高建³,
侯秀林³,
吴胜和^{1, 2}

1.
中国石油大学油气资源与探测国家重点实验室, 北京 102249
2.
中国石油大学地球科学学院, 北京 102249
3.
中国石油勘探开发研究院, 北京 100083
4.
中国石油化工股份有限公司胜利油田分公司, 山东东营 257015

基金项目:

国家自然科学基金项目 42272186

国家自然科学基金项目 42202109

中国博士后基金项目 BX20220351

中国博士后基金项目 2022M713458

中国博士后基金项目 2022M723489

详细信息

作者简介:
刘警阳（1997-），男，博士研究生，从事油气田开发地质相关研究，ORCID：0000-0003-2376-329X. E-mail：liujingyang0306@163.com

通讯作者:
岳大力(1974-)，男，教授，博士，从事油气田开发地质相关科研与教学工作，E-mail：yuedali@cup.edu.cn

中图分类号: P512
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出版历程
- 收稿日期: 2023-04-17
- 网络出版日期: 2024-11-08
- 刊出日期: 2024-10-25

Evolution of Bars in Braided Rivers Controlled by Discharge Variability

Liu Jingyang^{1, 2
,
,},
Li Wei^{1, 2},
Zhao Wenzhi^{1, 2, 3},
Yue Dali^{1, 2
, ,},
Shu Qinglin⁴,
Wang Wurong^{1, 2},
Gao Jian³,
Hou Xiulin³,
Wu Shenghe^{1, 2}

1.
State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China
2.
College of Geosciences, China University of Petroleum, Beijing 102249, China
3.
Research Institute of Petroleum Exploration and Development, PetroChina, Beijing 100083, China
4.
SINOPEC Shengli Oilfield Company, Dongying 257015, China

摘要

摘要: 流量变化控制辫状河心滩形成演化进而影响心滩内部结构和叠置样式，但目前流量变化控制的辫状河心滩沉积过程与演化特征尚不明确.利用Google Earth软件在全球范围内选取了发育辫状河沉积的13个河段，并在全球径流数据中心（GRDC）中查询整理所选河段的流量数据，通过峰值流量变异系数（CVQ_p）对心滩演化过程进行研究.结果表明：就流量变化程度而言，（1）低流量变化辫状河（CVQ_p < 0.4）心滩演化以坝尾沉积和下游迁移为主，高流量变化辫状河（CVQ_p > 0.4）心滩演化相对快，洪水前后原有心滩易被破坏、改造形成新的心滩，心滩冲裂现象普遍；（2）单一河流内，低流量变化辫状河心滩长宽比分布相对集中，形态较为稳定，易形成相对稳定型辫状河，而高流量变化辫状河心滩长宽比分布离散，形态各异且发育规模变化较大，易形成游荡型辫状河；（3）顺流加积在低流量变化辫状河心滩演化中较常见，因此心滩经过长时间的演化易形成复合心滩，高流量变化辫状河的洪水事件对心滩演化过程影响较强，在时间尺度上心滩演化相对复杂、规律性较差.明确辫状河在不同流量条件下的心滩演化可为辫状河储层的砂体分布预测提供模式指导，也可为古环境重建和古流量恢复提供依据.
- 辫状河 /
- 流量变化 /
- 洪峰流量 /
- 心滩演化 /
- 沉积模式 /
- 石油地质学
Abstract: The discharge variability controls the formation and evolution of braid bars and influences the internal structure and superimposition of braid bars. However, the control of discharge variability on the developments and evolution of braid bars are unclear. Google Earth software was used to selected 13 river reaches with braided river deposits worldwide, and the discharge data of the selected river reaches are collected from the Global Runoff Data Center (GRDC). Then, the coefficient of annual peak discharge variation (CVQ_p) was used to study the process and evolution of the braid bars. The results are as follow. (1) In terms of the degree of discharge variability, the braid bar evolution of braided river with lower discharge variability (CVQ_p < 0.4) mainly develops bar tail deposition and downstream migration. In braided rivers with higher discharge variability (CVQ_p > 0.4), the braid bar evolves relatively fast. Before and after flood event, the original braid bar is easy to be destroyed and transformed into a new braid bar, and the braid bar burst is common. (2) In a single river, the braid bar distribution of length to width ratio of the braided river with lower discharge variability is relatively concentrated, and the morphology is relatively stable, which is easy to form a relatively-stable braided river. While braided river with higher discharge variability is easy to form classical braided river because of the scattered braid bar distribution of length to width ratio, different morphology and great changes in development position.(3) Downstream accumulation is more common in the evolution of braid bar with lower discharge variability, so it is easy to form compound bars after long time evolution. The flood events of braided rivers with higher discharge variability have a strong influence on the evolution process of the bars, and the braid bar evolution is relatively complex and has poor regularity in the time scale. Clarifying the evolution of braid bars under different discharge conditions can provide guidance for the prediction of sandstone distribution of braided river reservoirs and may provide a basis for the paleo-environment reconstruction and paleo-discharge restoration.
- braided river /
- discharge variability /
- peak discharge /
- braid bar evolution /
- depositional model /
- petroleum geology

HTML全文

图 1 研究河段的地理位置

审图号：GS(2016)1666号自然资源部监制

Fig. 1. Locations of the study river reaches

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图 2 低流量变化辫状河的流量参数统计

Fig. 2. Statistics of braided river discharge parameters with lower discharge variabilities

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图 3 低流量变化辫状河心滩演化特征（阿根廷巴拉那河Corrientes段）

a~c.河段卫星照片；d~f. 心滩形态轮廓素描；g~i. 心滩演化过程示意

Fig. 3. Evolutionary characteristics of braid bars with relatively-lower discharge variabilities

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图 4 阿根廷巴拉那河心滩下游迁移特征

红线为2014年心滩轴线，蓝线为2019年心滩轴线

Fig. 4. The characteristics of bar downstream migration in Paraná River, Argentina

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图 5 高流量变化辫状河流量参数统计

Fig. 5. Statistics of braided river discharge parameters with higher discharge variabilities

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图 6 高流量变化辫状河心滩演化特征（加拿大南萨斯喀彻温河Saskatoon段）

a~c. 河段卫星照片；d~f. 心滩形态轮廓素描；g~i. 心滩演化过程示意

Fig. 6. Evolutionary characteristics of braid bars with relatively-higher discharge variabilities

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图 7 加拿大南萨斯喀彻温河心滩下游迁移特征

红线为2012年心滩轴线，蓝线为2013年心滩轴线

Fig. 7. The characteristics of bar downstream migration in South Saskatchewan River, Canada

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图 8 不同流量变化辫状河心滩演化统计

a. 辫状河心滩演化类型统计；b. 辫状河心滩演化阶段统计

Fig. 8. Statistics of the evolution of braid bars with different discharge variabilities

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图 9 辫状河心滩平面形态参数散点分布

a. 低流量辫状河心滩形态参数散点分布；b. 高流量辫状河心滩形态参数散点分布

Fig. 9. Scattered distribution of planar morphological parameters of braid bars

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图 10 不同流量变化辫状河心滩演化模式

a. 低流量变化辫状河心滩演化模式；b. 高流量变化辫状河心滩演化模式

Fig. 10. Evolution models of braid bars with different discharge variabilities

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表 1 流量变化表征参数

Table 1. Characterization parameters for discharge variability

流量变化指标	计算方程
峰值流量变异系数CVQ_p	$ {\sigma }_{{\mathrm{Q}}_{\mathrm{p}}}/{Q}_{{\mathrm{p}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}} $
平均流量变异系数DVI_a	$ ({Q}_{{\mathrm{W}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}}-{Q}_{{\mathrm{D}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}})/{Q}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}} $
累计流量变异系数DVI_c	$ ({Q}_{{{\mathrm{W}}^{\mathrm{R}}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}}-{Q}_{{{\mathrm{D}}^{\mathrm{R}}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}})/{Q}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}} $
年流量变异系数DVI_y	$ [\sum\limits_{i=x}^{x+n}({Q}_{{\mathrm{x}}_{\mathrm{D}\mathrm{a}\mathrm{y}\mathrm{m}\mathrm{a}\mathrm{x}}}-{Q}_{{\mathrm{x}}_{\mathrm{D}\mathrm{a}\mathrm{y}\mathrm{m}\mathrm{i}\mathrm{n}}})/{Q}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}]/n $
洪水强度Q_peakedness	$ {Q}_{{\mathrm{W}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}}/{Q}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}} $
注：σ_Qp为年洪峰流量标准差，Q_Pmean为年平均洪峰流量；Q_Wmean为平均最湿润月流量；Q_Dmean为平均最干旱月流量；Q_W_mean^R为有记录以来平均最湿润月流量；Q_D_mean^R为有记录以来平均最干旱月流量；Q_XDaymax为x年最大日流量；Q_XDaymin为x年最小日流量；Q_mean为平均流量.

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表 2 研究河段参数统计

Table 2. River parameters in the study river reaches

序号	河流	位置	水文站	控制流域面积（m²）	气候	测量心滩个数	测量心滩区域位置	平均洪峰流量（m³/s）	标准差	CVQ_p
1	亚马逊河	巴西	Santo Antonio Do Ica	1 134 540	热带雨林	20	3°58′48″S—3°43′25″S 70°59′47″W—64°4′21″W	68 192.99	5 928.93	0.09
2	巴拉那河	阿根廷	Corrientes	1 950 000	潮湿亚热带	20	27°56′58″S—31°10′37″S 58°49′29″W-59°59′46″W	21 917.69	3 564.69	0.16
3	马更些河	加拿大	Norman Wells	1 570 000	寒冷	20	62°4′7″N-66°48′22″N 122°7′42″W—130°7′40″W	18 130.50	3 444.79	0.19
4	雅鲁藏布江	印度	Bahadurabad	636 130	亚热带季风	20	26°41′55″N—26°0′57″N 93°39′34″E—90°1′38″E	50 531.08	10 106.22	0.20
5	恒河	印度	Farakka	835 000	热带季风	20	26°34′49″N—25°28′16″N 82°39′54″E—85°56′5″E	44 419.30	10 634.65	0.24
6	Rakaia River	新西兰	Fighting Hill	2 560	温带	20	43°34′37″S—43°41′35″S 171°44′38″E—171°55′17″E	398.31	125.36	0.31
7	育空河	美国	Ruby, Alas.	670 810	寒冷	20	65°8′50″N—62°42′5″N 152°5′10″W—160°7′10″W	12 966.21	4 122.94	0.32
8	维斯瓦河	波兰	Warsaw	84 945	温带	20	52°24′56″N—52°28′35″N 20°37′26″E—19°47′1″E	1 151.13	398.48	0.35
9	奈厄布拉勒河	美国	Near Verdel, Nebr.	29 992	半潮湿- 半干旱	25	42°46′1″N—42°49′33″N 99°54′10″W—98°45′44″W	98.11	43.37	0.44
10	南萨斯喀彻温河	加拿大	Saskatoon	141 000	半潮湿- 半干旱	25	51°49′4″N—51°25′40″N 106°44′2″W—107°4′41″W	846.79	389.52	0.46
11	松花江	中国	哈尔滨	391 000	季风	27	45°55′9″N—46°17′22″N 128°5′30″E—129°27′55″E	3 397.06	1 624.19	0.48
12	普拉特河	美国	Louisville, Nebr.	218 078	干旱	25	40°53′3″N—40°56′41″N 98°16′23″W—98°12′1″W	534.69	302.25	0.57
13	HalilRud River	伊朗	Hossein Abad Jiroft	8 420	干旱	20	28°40′32″N—28°39′29″N 58°32′13″E—58°28′55″E	36.40	43.58	1.20

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