Heavy mineral composition of the Songhua River system identified by manual and TIMA automatic methods and implications for provenance tracing
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摘要: 松花江水系作为中国东北地区最主要的河流系统，其重矿物组成对于揭示其沉积环境、沉积物源-汇过程和水系演化等地表过程具有重要意义。但目前对松花江水系重矿物组成了解有限，对影响其重矿物组成的控制因素尚不明晰。为此，在松花江干流和10个主要支流的边滩采集河流沙样品，在通河获取2个松花江T3阶地样品，分别采用TESCAN Integrated Mineral Analyzer（TIMA）自动化矿物识别技术和人工方法，对63～250 μm粒级组分进行重矿物分析，旨在给出松花江水系的重矿物组成，并分析物源、河流过程和化学风化等因素对重矿物组成的影响和控制，以及评估人工和TIMA方法在重矿物鉴定中的应用情况。结果表明，发源于不同山岭（大兴安岭、小兴安岭和长白山）的各支流具有显著不同的重矿物组成，角闪石、榍石、绿帘石、白钛石、辉石、钛铁矿和赤、褐铁矿是区分各物源的指示性矿物。源自大兴安岭的嫩江支流具有显著高含量的辉石（诺敏河）、钛铁矿（甘河、多布库尔河和阿伦河）和赤、褐铁矿（甘河、多布库尔河和雅鲁河），显示了基性火成岩物质对重矿物组成的控制，这在现代河床砾石的岩性中得到证明。然而，在松花江干流中，这些重矿物含量显著降低，显示了极弱的大兴安岭源区信息，表明支流物源对重矿物组成的控制受到干流所携带沉积物的削弱，干流物源占据了主导地位。值得指出的是，松花江干流的重矿物组成显示出为拉林河和第二松花江物源的混合，表明干流更多地继承了松嫩平原东南山岭（长白山余脉）的重矿物信息。受到严重化学风化影响的通河T3阶地样品的重矿物组成简单，辉石和角闪石等抗风化能力弱的不稳定重矿物已完全消失，而稳定矿物高度富集，反映了化学风化对重矿物组成起到主要控制作用。相对于传统人工鉴定方法得到的重矿物组成（通常只能鉴定出20余种矿物相），TIMA方法能够给出更多的矿物种类信息（通常能识别出40余种矿物相），但在识别同质异相和多晶型矿物方面存在不足。Abstract: The Songhua River is the most important fluvial system in northeast China and its heavy mineral composition is of great significance to the revealing of depositional environment, source-sink relationship and drainage evolution. However, the current study concerning the heavy mineral composition of the Songhua River system is very limited, and the factors affecting the composition of heavy minerals are not clear up to date. In order to solve the problem, sand samples are collected along the banks of the main stream and 10 major tributaries of the river system, in addition to the two from the T3 terraces of the Tonghe River. Using the new automated mineral identification technology TESCAN Integrated Mineral Analyzer (TIMA) and the manual method respectively, heavy mineral analysis of the sample components in depth of 63~250 m is carried out for the samples. The influences of sediment sources, fluvial processes and chemical weathering on the heavy mineral composition of the Songhua River system are discussed. The results show that the tributaries sediments are sourced from different mountains, such as the Great Hinggan Mountains, the Lesser Hinggan Mountains and the Changbai Mountains. These mountains are significantly different in heavy mineral composition, and the heavy minerals of hornblende, titanite, epidote, leucoxene, augite, ilmenite and hematite+limonite are effective indicators to distinguish the water systems of different sources. The Nenjiang tributaries are originated from the Great Hinggan Mountains, of which sediments are rich in augite (the Nuomin River), ilmenite (the Ganhe River, Duobukuer River and Alun River) and hematite+limonite (the Ganhe River, Duobukuer River and Yalu River), showing the control of the basal source over heavy mineral composition, which can be observed in the modern riverbed gravels. However, in the main stream of the Songhua River, those heavy minerals are significantly reduced, suggesting that the influence of the Great Hinggan Mountains, as a source area, is extremely weak and the source control of heavy mineral composition is heavily influenced by river process. It is worth to point out that the heavy mineral composition of the Songhua River main stream is the mixture of the Lalin River and the Second Songhua River, indicating that the main stream of the Songhua River has inherited more heavy mineral information from the southeastern mountains of the Songnen Plain (the remnants of Changbai Mountain). The composition of heavy minerals in T3 terrace samples of Tonghe, which was severely affected by chemical weathering, is extremely simple, the unstable heavy minerals such as augite and hornblende have completely disappeared, and stable minerals are highly enriched, reflecting the control of chemical weathering over heavy mineral composition. Compared with the traditional manual identification of monotonous heavy mineral composition (usually only more than 20 mineral species can be identified), the TIMA method can reveal more mineral information (usually more than 40 mineral species can be identified), but there are shortcomings in identifying homogenous and polymorphic minerals.
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Keywords:
- heavy minerals /
- TIMA analyses /
- provenance /
- chemical weathering /
- river processes /
- Songhua River system
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深水盆地沉积物的压实状态直接关系到沉积物本身的稳定性以及钻井工程的安全问题，随着近年南海北部深水盆地油气资源的开发，钻井灾害的预防越来越受到重视，特别是浅层地质灾害，如滑坡、浅水流、浅层气、天然气水合物等[1-4]。超压是引起大部分深水盆地地质灾害的主要因素，在南海北部珠江口盆地、莺歌海盆地、琼东南盆地等也已经进行了广泛研究[5-11]。超压主要是指沉积物孔隙压力高于静水压力，超压的形成和增长会驱使沉积物结构发生变化，导致岩层破裂形成断层或造成滑坡。钻井过程中，钻井液的注入低于超压值会造成井漏，而高于超压值会造成围岩破坏，未固结沉积物上涌[1-2, 4, 12]。超压问题的解决是南海北部深水盆地油气资源钻探开发的重点研究对象。
孔隙压力是指沉积物孔隙中流体的压力，现阶段主要的孔隙压力预测方法都是基于Eaton和Bowers的经典方法改进而来[13-20]。孔隙压力的预测需要利用沉积物正常压实系数来实现计算，正常压实系数是根据相关沉积物正常压实层段测井数据，如孔隙度、声波时差等进行拟合获得[8, 10, 21, 22]。沉积物的正常压实是通过上覆沉积物的不断沉积，对下伏沉积物加压使其孔隙内流体随时间、压力增加逐渐排出而进行的[14]，这一过程可能受沉积物组成成分、沉积速率、沉积区域、沉积物埋藏深度、计算拟合方式等的影响，从而造成不同的结果。
本文旨在通过对ODP184航次1144、1146、1148站位与IODP349航次U1431、U1432、U1433、U1435站位的测井数据进行分析，通过正常压实沉积物孔隙度随深度呈指数变化的关系来拟合不同情况下南海深水盆地沉积物的正常压实系数与初始孔隙度，分析南海深水盆地沉积物正常压实系数的影响因素与变化规律，为今后南海深水盆地超压预测提供有效的借鉴与参考，获得更加有效、精确的超压预测值。
1. 地质背景
南海是西太平洋面积最大的边缘海，处于欧亚板块、太平洋板块和印度-澳大利亚板块3大板块的边界地带，共计约35 000 000 km2(图 1)。南海在各大板块与地幔物质的共同作用下经历了复杂的演化历史[23]。现今的南海主要是在渐新世-中新世时期洋壳沿WSW-ENE向扩张而成[24, 25]。新生代南海的构造演化主要分为始新世-渐新世裂谷期和新近纪-第四纪裂后沉降期两个阶段[26-29]，经历了从早期湖泊相、海湾浅海相，到最终的开阔大洋沉积环境的演化过程[28, 29]。
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图 1 研究区域构造划分与地形地貌Figure 1. The tectonic division and Geomorphologic map of the study areaODP184航次是中国南海首次深水钻探航次，主要钻探了南海北部陆坡6个站位的17口井，共钻取了5 463 m沉积物，其中32 Ma以来的深水沉积层序记录了南海扩张后的整个沉积环境演化历史[30]。1144站位位于南海北部陆坡的一个厚层沉积漂积体中，具有高沉积速率，水深2 037 m，最大钻进深度453 m，250 m以上平均沉积速率达0.87 mm/a(图 1)。1146站位位于南海北部中部陆坡小型裂谷盆地内，水深2 092 m，最大钻进深度607 m, 沉积速率较稳定，在更新世时期的最大平均沉积速率只有0.15 mm/a，分布着连续的半深海沉积层序。1148站位位于ODP184航次中南海北部陆坡边缘最深处，接近于洋陆边界，水深3 246 m，最大钻进深度853 m，沉积速率变化较大，中间还存在3 Ma的沉积缺失[31]。
IODP349航次在南海深水盆地主要钻探了5个站位，其中在扩张中心附近的3个(U1431, U1433和U1434)钻穿了洋壳[32](图 1)。U1431站位位于南海中央海盆残余扩张中心附近，水深4 237 m，最大钻进深度1 008 m，周围被洋壳上海山等洋底高地包围，属于远洋沉积。U1432站位位于1148站位南部约60 km处，处于洋陆边界地带，水深3 829 m，最大钻进深度110 m，钻取沉积物年龄不超过0.91 Ma。U1433站位位于南海中央海盆南部残余扩张中心附近，水深4 379 m，最大钻进深度857 m，早中新世到中中新世沉积物沉积速率极低(∠0.005 m/a), 晚中新世到早更新世沉积物沉积速率在0.05~0.09 mm/a，之后在1 Ma内快速上升到0.2 mm/a。U1435站位位于洋陆边界地带，作为U1432站位的补充，水深3 252 m，最大钻进深度300 m[32]。
2. 数据与方法
本研究使用的测井孔隙度数据均来自于ODP184航次与IODP349航次初始报告，是由岩心干湿样品的质量和体积测量获得。这一方法主要是利用对流烘箱将湿样放置在温度为100~110 ℃中烘干24 h，这样不仅除去了孔隙水，但也除去了大量存在于黏土矿物(如蒙脱石)内的层间水(结合水)，导致计算的孔隙度偏大约20%[33]。层间水对有效压实的孔隙流体压力并无作用，所以本文使用孔隙度数据都经过了20%的误差校正。
沉积物正常压实孔隙度随深度(海底泥线以下)呈指数变化[20, 34]：
$$ {\phi _n} = {\phi _0}{e^{ - cz}} $$ (1) 式中，ϕn为实际孔隙度；ϕ0为初始孔隙度(海底泥线处)；c 为沉积物正常压实系数；z 为海底泥线下深度。通过ODP184航次与IODP349航次各站位测井孔隙度数据随深度变化情况识别出正常压实沉积物层段，在科学绘图软件Grapher9.0上利用公式(1)对测井孔隙度数据与深度进行拟合，获得沉积物正常压实系数与初始孔隙度。
3. 结果与讨论
3.1 沉积物的正常压实
ODP184航次与IODP349航次各站位沉积物正常压实层段，孔隙度随深度(海底泥线以下，以下简称深度)呈指数变化趋势，其中1144站位正常压实层段沉积物深度为450 m, 1146站位为170 m，1148站位为460 m, U1431站位为500 m, U1432站位为120 m, U1433站位为700 m，U1435站位为300 m(图 2)。通过公式(1)对各站位钻井正常压实沉积物层段进行拟合，同时对所有站位钻井深度100 m以上沉积物进行拟合(图 3-7)。
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图 2 南海深水盆地ODP184航次1144、1146、1148站位与IODP349航次U1431、U1432、U1433、U1435站位孔隙度随深度(海底泥线以下)变化趋势图(红线为钻井深度100 m所处位置，蓝线为各站位钻井沉积物正常压实层段深度所处位置)Figure 2. The porosity versus depth (below the mudine) at ODP Leg 184 Site 1144、1146、1148 and IODP Leg 349 Site U1431、U1432、U1433、U1435 in deepwater basin of the South China Sea(Red line is the location of 100 m drilling depth, blue line is the depth of the normal compaction sediments)![]()
图 3 1144站位钻井沉积物正常压实层段(450 m)孔隙度与深度(海底泥线以下)拟合结果(A)及正常压实层段(170 m)孔隙度与深度(海底泥线以下)拟合结果(B)(红线为拟合曲线)Figure 3. A. Fitted result of porosity and depth (below the mudline) in normal compaction sediments (450 m) at Site 1144; B. Fitted result of the porosity and depth (below the mudline) in normal compaction sediments (170 m) at Site 1146;(Red lines are the fitted curves)![]()
图 4 1148站位钻井深度100 m以上沉积物正常压实孔隙度与深度(海底泥线以下)拟合结果(A)及钻井沉积物正常压实层段(460 m)孔隙度与深度(海底泥线以下)拟合结果(B)(红线为拟合曲线)Figure 4. A. Fitted result of porosity and depth (below the mudline) in 100 m drilling depth at Site 1148; B. Fitted result of the porosity and depth (below the mudline) in normal compaction sediments (460 m) at Site 1148(Red lines are the fitted curves)![]()
图 5 U1431站位钻井深度100 m以上沉积物正常压实孔隙度与深度(海底泥线以下)拟合结果(A)及沉积物正常压实层段(500 m)孔隙度与深度(海底泥线以下)拟合结果(B)(红线为拟合曲线)Figure 5. A. Fitted result of porosity and depth (below the mudline) in 100 m drilling depth at Site U1431; B. Fitted result of the porosity and depth (below the mudline) in normal compaction sediments (500 m) at Site U1431(Red lines are the fitted curves)![]()
图 6 U1432站位钻井沉积物正常压实层段(120 m)孔隙度与深度(海底泥线以下)拟合结果(A)及U1435站位钻井沉积物正常压实层段(300 m)孔隙度与深度(海底泥线以下)拟合结果(B)(红线为拟合曲线)Figure 6. A. Fitted result of porosity and depth (below the mudline) in normal compaction sediments (120 m) at Site U1432; B. Fitted result of the porosity and depth (below the mudline) in normal compaction sediments (300 m) at Site U1435(Red lines are the fitted curves)![]()
图 7 U1433站位钻井深度100 m以上沉积物正常压实孔隙度与深度(海底泥线以下)拟合结果(A)及钻井沉积物正常压实层段(700 m)孔隙度与深度(海底泥线以下)拟合结果(B)(红线为拟合曲线)Figure 7. A. Fitted result of porosity and depth (below the mudline) in 100 m drilling depth at Site U1433; B. Fitted result of the porosity and depth (below the mudline) in normal compaction sediments (700 m) at Site U1433(Red lines are the fitted curves)通过对各站位钻井孔隙度与深度拟合的正常压实曲线可见(图 3-7)，7个站位沉积物正常压实层段的指数拟合曲线决定系数都在0.6以上，具有很好的可靠性。其中ODP184航次的3个站位决定系数都在0.81以上，1146站位与1148站位更是在0.9以上，拟合程度非常好。IODP349航次5个站位拟合曲线决定系数都在0.6以上，较ODP184航次3个站位低，但具有可靠性。同时ODP184航次3个站位相比于IODP349航次的5个站位，数据相对于拟合曲线也表现出更明显的收敛效果。
3.2 沉积物正常压实系数影响因素分析
各站位正常压实沉积物由于沉积物组分、沉积速率、沉积区域与沉积物深度等的差异，其拟合的压实系数和初始孔隙度并没有明显的规律性(表 1)。通过拟合各站位钻井深度100 m以上沉积物压实系数来分析沉积物组分、沉积速率、沉积区域与沉积物深度等对沉积物压实效果的影响，其中U1435站位钻井正常压实层段沉积物(300 m)拟合与钻井深度100 m以上沉积物拟合分别表现出明显的过低初始孔隙度和过高初始孔隙度与异常压实系数，这可能与该站位浅层测井数据量有关，数据量的不足导致拟合计算过程中出现深部拟合忽略浅部少量数据和浅部拟合缺乏有效数据量收敛而出现误差，所以在分析过程中不做分析(表 2，图 8)。
表 1 各站位钻井沉积物正常压实层段孔隙度与深度(泥海底线以下)拟合结果Table 1. Fitted results of porosity and depth (below the mudline) in normal compaction sediments at all Sites站位 水深/m 拟合深度/m 压实系数 初始孔隙度 R2 1144 2 037 450 0.000 755 547 0.584 485 608 0.815 559 1146 2 092 170 0.002 213 826 0.674 115 233 0.912 179 1148 3 246 460 0.001 374 514 0.584 401 796 0.912 126 U1431 4 237 500 0.000 888 844 0.565 614 573 0.636 038 U1432 3 829 120 0.003 646 652 0.649 199 6 0.705 043 U1433 4 379 700 0.000 621 063 0.535 213 818 0.675 121 U1435 3 252 300 0.003 301 695 0.497 459 197 0.718 408 表 2 各站位钻井深度100 m以上沉积物正常压实孔隙度与深度(海底泥线以下)拟合结果Table 2. Fitted results of porosity and depth (below the mudline) in 100 m drilling depth at all Sites站位 水深/m 拟合深度/m 压实系数c 初始孔隙度ϕ0 R2 数据量 1144 2 037 100 0.002 175 931 0.635 431 987 0.871 93 73 1146 2 092 100 0.001 566 811 0.656 554 092 0.771 10 54 1148 3 246 100 0.003 514 827 0.667 174 148 0.919 59 53 U1431 4 237 100 0.002 630 228 0.639 528 484 0.480 00 71 U1432 3 829 100 0.003 993 244 0.656 653 229 0.677 15 57 U1433 4 379 100 0.002 860 513 0.625 794 137 0.542 06 57 U1435 3 252 100 0.009 452 971 0.775 503 404 0.552 29 21 ![]()
图 8 各站位钻井深度100 m以上沉积物正常压实孔隙度与深度(海底泥线以下)拟合压实系数与初始孔隙度分布Figure 8. Fitted coefficients of normal compaction and mudline porosity of porosity and depth (below the mudline) in 100 m drilling depth at all Sites通过公式(1)可知，在假设初始孔隙度相同的情况下，同一深度下，压实系数越大，孔隙度越小，沉积物压实效果越好。1144站位与1146站位水深相近，钻井深度100 m以上沉积物同属于更新世沉积[31]，在拟合结果中，1146站位压实系数比1144站位小0.000 6，初始孔隙度差-0.02，1144站位区域钻井深度100 m以上沉积物相比1146站位区域较压实。1144站位所在区域是高速率沉积区，据计算1144站位钻井深度250 m以上平均沉积速率达0.87 mm/a。据Prell等(1999)研究报告, 1144站位位于南海北部陆坡的一个厚层沉积漂积体中，该处沉积漂积体是底流与南海暖流支流共同作用的结果[35]，厚层沉积漂积体沉积过程中沉积物组分中较粗物质被底流冲刷带走，沉积较细的沉积物。1146站位所在区域沉积速率较稳定，在更新世时期的最大平均沉积速率只有0.15 mm/a。在钻井深度100 m以上沉积物的沉积过程中，1144站位区域沉积物普遍比1146站位区域沉积物沉积时期较新[31]。
U1431站位与U1433站位基本处于相近深度下，同属于远洋深海沉积，分别位于南海中央海盆中部残余扩张中心北侧与南海中央海盆南部残余扩张中心南侧。钻井深度100 m以上沉积物拟合压实系数相差0.000 2；初始孔隙度差-0.01。据Li等(2015)的IODP349航次报告，U1431站位钻井深度300 m以上沉积物的平均沉积速率约0.05 mm/a，100 m以上沉积物属于更新世以来沉积，主要是黏土与粉砂质黏土沉积，含有丰富的浊流形成沙质沉积物。U1433站位钻井深度200 m以上沉积物的平均沉积速率约0.2 mm/a，主要沉积黏土夹杂极少量薄层粉砂，300 m以上沉积物属于更新世以来沉积。在钻井深度100 m以上沉积物的沉积过程中，U1433站位区域沉积物明显比U1431站位区域沉积物沉积时期较新，同时沉积速率明显较快。
一般情况下，上覆低渗透率沉积物快速沉积会导致下伏沉积物孔隙中流体无法及时排除而造成高孔隙度，进而超压[14]。在钻井深度100 m以上沉积物中，1144站位与1146站位、U1431站位与U1433站位都是在相近水深处，沉积速率较快的站位区域(1144站位与U1433站位)出现沉积物压实效果更好的现象，这说明沉积速率对这两个对比区域的沉积物压实影响较小。1144站位与U1433站位钻井显示，钻井深度100 m以上沉积物组分分别要比1146站位与U1431站位沉积物组分细，这就导致了1146站位与U1431站位钻井深度100 m以上沉积物孔隙较大，压实效果较差。
通过图 8可见，在不同水深下的各站位钻井深度100 m以上沉积物压实系数并没有表现出很好的规律性。1144站位与1146站位同属于2 000 m水深，压实系数最小。U1431站位与U1433站位同属于4 300 m左右水深，压实系数大于1144站位与1146站位，但小于1148站位与U1432站位。除U1435站位拟合数据异常不做对比外，U1432站位钻井深度100 m以上沉积物压实系数最大，1148站位次之。U1432站位与1148站位位于南海北部洋陆边界地带，其中U1432站位基本处于边界上[31, 32]，属于被动大陆边缘的陆隆区域。1144站位与1146站位位于南海北部陆坡上，而U1431站位与U1433站位位于南海中央海盆裂谷附近，属于远洋深海盆地沉积区域。可见不同沉积环境对沉积物正常压实具有不同的影响，南海北部洋陆边界区域压实效果最好，洋盆裂谷附近次之，陆坡上沉积物压实效果最差。
通过各站位正常压实沉积物拟合压实系数(表 1)与钻井深度100 m以上沉积物拟合压实系数(表 2)对比可见，不同深度正常压实沉积物拟合的压实系数不同。其中1148站位正常压实沉积物(460 m)拟合决定系数与钻井深度100 m以上沉积物拟合决定系数都在0.91以上，拟合效果非常好，但压实系数相差约0.002，初始孔隙度差约0.08(图 4)。U1431站位与U1433站位也表现出较大的差异性，压实系数相差约0.002，初始孔隙度分别相差约0.07与0.09(图 5, 7)。1148站位、U1431站位与U1433站位是研究井位中正常压实沉积物深度最大的3个站位，正常压实沉积物层段拟合压实系数与初始孔隙度相比钻井深度100 m以上沉积物拟合压实系数与初始孔隙度表现出明显的减小现象，压实系数减小值都在0.002左右，初始孔隙度减少值也极其相近，沉积物压实系数与初始孔隙度随深度增加呈现下降趋势。选取1144、1148与U1433站位分别代表南海北部陆坡、南海北部陆隆与洋盆沉积环境分析沉积物正常压实系数与初始孔隙度随深度的变化关系。
3.3 压实系数与初始孔隙度随深度变化趋势分析
1144站位、1148站位与U1433站位从海底泥线开始，每隔50 m利用公式(1)进行一次拟合计算，每次拟合深度都是从海底泥线开始到目标深度层位，获得压实系数与初始孔隙度如图 9分布。1144站位与1148站位的拟合目标深度到450 m，共拟合9次，U1433站位的拟合目标深度到700 m，共拟合14次。
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图 9 1144、1148、U1433站位各钻井深度上沉积物孔隙度与深度拟合的压实系数(红色圆点)与初始孔隙度(蓝色三角)随拟合深度(海底泥线以下)变化趋势Figure 9. Variation of the fitted coefficients of normal compaction (red dot) and mudline porosity (blue triangle) for porosity and depth (below the mudline) in different drilling depth at Site 1144、1148、U1433U1433站位处于洋盆环境下，沉积速率与沉积物质都比较稳定，钻井深度700 m以上沉积物都处于正常压实状态下。通过图 9可见，U1433压实系数随深度增加呈先减小再趋于稳定的变化趋势，最后压实系数约在0.000 6左右，初始孔隙度也随深度增加呈先减小再趋于稳定的变化趋势，最终趋于0.53左右。1144站位位于南海北部陆坡沉积环境，属于受底流与暖流共同影响的厚层沉积漂积体，沉积颗粒较细，上覆钻井深度450 m以上沉积物较稳定，其压实系数随深度增加呈先减小再趋于稳定在约0.000 7左右的变化趋势，初始孔隙度也随深度增加呈先减小再趋于稳定在约0.58的变化趋势。而1148站位属于洋陆边缘沉积，其钻井深度50 m以上沉积物拟合压实系数与初始孔隙度在整体上表现出异常偏小值，压实系数随深度增加逐渐减小至0.001 4左右，初始孔隙度随深度增加逐渐减小至0.59左右，都还没有趋于稳定，变化趋势也没有1144站位与U1433站位平滑。
在正常压实环境下，1144站位与U1433站位显示，压实系数与初始孔隙度随深度增加会先减小后逐渐趋于稳定，这趋于稳定的深度应该是沉积物成岩并完全固结所在的深度。上覆浅层正常压实沉积物的拟合压实系数较大，是由于浅层沉积物孔隙中流体排除明显，而到下伏沉积物后，孔隙中流体基本已排除，沉积物已趋于完全压实固结。1148站位正常压实系数与初始孔隙度随深度增加还没有趋于稳定，可能存在孔隙流体异常与压力异常所致，沉积物还没有达到完全压实固结状态。
4. 结论
(1) 南海深水盆地沉积物正常压实效果受沉积物组分、沉积速率、沉积区域、沉积物深度等因素的影响，沉积物组分是影响正常压实系数的主要因素。南海北部陆坡、南海北部陆隆与南海洋盆等不同区域表现出明显不同的沉积物正常压实效果，其中处于洋陆边界地带的压实效果最好，压实系数最大，处于南海北部陆坡处的压实效果最差。
(2) 南海深水盆地中沉积物的压实随深度表现出明显的渐变过程。浅层沉积物孔隙度大，孔隙中流体含量充足，随着压实进行流体排出效果明显，压实系数较大。随着沉积物深度增加，压实系数逐渐减小到趋于稳定，到达沉积物已完全压实固结层位。这一压实系数的变化规律可以更好地厘定浅层正常压实沉积物层段深度，有助于今后在南海深水盆地沉积物孔隙压力和有效应力方面的研究。
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图 1 松花江水系及采样位置示意图
Figure 1. DEM map of Songnen Plain, showing the distribution of the Songhua River drainage system and sample
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图 3 松花江水系代表性样品的 TIMA 分析识别结果
a. BSE 图, b. SEM 图, c. 矿物相图, d. 各矿物面积比图, e. 各矿物周长比图, f. 各矿物元素比图。
Figure 3. Identification results of TIMA analysis of representative samples from the Songhua River system
a. BSE diagram, b. SEM diagram, c. mineral phase diagram, d. diagram of the area of each mineral, e. the perimeter ratio of each mineral, f. comparison of mineral elements.
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图 4 松花江水系重矿物特征指数
a. ZTR 指数, b. 稳定系数 (W), c. 风化系数 (HW), d. ATi 指数。
Figure 4. Heavy mineral characteristic index of the Songhua River system
with (a) ZTR Index, (b) Stability coefficient (W), (c) Weathering coefficient (HW), and (d) ATi Index.
表 1 人工和 TIMA 检测松花江水系重矿物结果对比
Table 1 Comparison of artificial and TIMA results for heavy minerals in the Songhua River drainage
% 河流名 方法 Zr Ap Rt Ant Lcx Spn Amp Tur Gt Ep Px Ilm Hem+Lm Mag Ky 通河T3阶地a 人工 1.4 0.0 0.5 0.0 11.9 0.0 0.0 1.4 2.6 3.0 0.0 53.1 3.6 1.8 0.0 通河T3阶地b 3.9 1.1 0.4 0.07 0.8 2.0 0.0 4.7 2.7 0.07 0.0 74.4 2.7 0.0 0.0 牡丹江 0.01 0.3 0.03 0.03 0.6 7.2 56.7 0.2 3.5 14.0 6.0 1.2 1.0 1.2 0.0 第二松花江 0.05 0.5 0.0 0.0 1.5 3.2 59.2 0.0 2.8 12.7 6.0 2.8 2.8 1.8 0.05 拉林河 0.8 0.2 0.0 0.03 0.5 4.1 74.0 0.05 0.6 7.6 1.2 4.5 0.8 1.0 0.01 蚂蜒河 0.4 0.2 0.0 0.03 1.1 21.5 55.5 0.0 0.2 6.4 2.1 5.2 1.0 2.0 0.0 巴兰河 0.05 0.2 0.0 0.0 1.2 22.1 54.3 0.2 1.0 5.6 3.3 2.1 0.8 1.2 0.0 岔林河 0.6 0.8 0.04 0.07 0.4 28.5 46.8 0.0 0.2 4.7 1.6 5.1 2.6 5.1 0.0 阿伦河 1.2 0.3 0.1 0.2 3.8 7.0 8.1 0.7 0.07 57.9 1.1 11.7 1.8 0.5 0.0 诺敏河 0.01 0.3 0.0 0.0 3.9 2.3 14.6 0.0 0.0 37.2 27.1 1.4 2.3 0.5 0.0 甘河 2.1 0.4 0.06 0.2 1.8 6.7 8.3 0.1 0.06 25.9 4.0 19.6 23.2 4.2 0.0 多布库尔河 1.6 1.1 0.03 0.3 2.3 11.4 8.6 0.0 0.5 27.4 1.1 22.8 13.0 4.6 0.0 雅鲁河 0.08 0.2 0.0 0.05 2.7 6.8 5.1 0.0 0.1 60.9 1.2 4.5 10.2 1.2 0.0 松花江哈尔滨段 0.6 1.1 0.06 0.03 1.5 4.4 48.7 0.5 1.5 24.6 4.4 5.0 1.3 2.5 0.04 牡丹江 TIMA 0.02 0.7 0.7 0.0 1.0 7.2 48.2 3.9 4.8 23.8 0.5 0.5 0.0 3.2 2.3 第二松花江 0.03 0.1 0.3 0.0 0.1 4.0 54.2 1.0 0.9 25.8 0.1 1.6 0.0 6.1 0.0 拉林河 0.0 0.7 0.7 0.0 0.3 3.7 74.0 1.1 0.1 13.1 0.05 1.5 0.0 0.7 2.0 蚂蜒河 0.2 0.04 0.6 0.0 0.4 27.2 44.3 1.2 1.6 16.1 0.03 5.3 0.0 1.3 0.2 巴兰河 0.4 0.3 0.5 0.0 0.3 19.8 37.1 4.7 3.4 22.5 0.1 2.0 0.0 1.8 1.3 岔林河 0.2 0.7 1.9 0.0 2.1 32.4 35.8 0.5 0.5 8.9 0.1 9.9 0.0 4.4 0.09 阿伦河 0.05 0.3 3.1 0.0 2.6 6.9 11.6 0.4 1.7 67.7 0.01 1.2 0.0 1.5 1.8 诺敏河 0.01 0.9 1.3 0.0 2.0 2.8 12.1 0.7 2.6 43.3 25.2 1.4 0.0 4.8 0.0 甘河 1.0 0.2 3.4 0.0 2.3 12.4 10.0 1.0 4.1 42.0 0.03 13.5 0.0 9.1 0.0 多布库尔河 0.7 1.3 3.5 0.0 2.9 15.5 6.7 1.1 8.5 32.6 0.09 13.4 0.0 13.1 0.2 雅鲁河 0.1 0.1 2.2 0.0 1.9 5.0 6.6 1.1 3.2 72.4 0.04 3.6 0.0 2.9 0.4 松花江哈尔滨段 0.2 1.4 0.6 0.0 1.1 4.4 53.0 2.1 1.1 29.6 0.04 2.8 0.0 1.4 0.2 注：Zr为锆石，Ap为磷灰石，Rt为金红石，Ant为锐钛矿，Lcx为白钛石，Spn为榍石，Amp为角闪石，Tur为电气石，Gt为石榴子石，Ep为绿帘石，Px为辉石，Ilm为钛铁矿，Hem+Lm为赤铁矿+褐铁矿，Mag为磁铁矿，Ky为蓝晶石。 
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表 2 TIMA 鉴定松花江水系矿物分类
Table 2 Mineral classification of the Songhua River water system as identified by TIMA
矿物名称 矿物分类 金红石类 金红石、钛铁金红石 闪石类 角闪石、阳起石、钙镁闪石、红闪石、
铝铁钙闪石、直闪石电气石类 黑电气石、钙镁电气石 石榴子石类 钙铁榴石、钙铝榴石、镁铝榴石 帘石类 绿帘石、褐帘石、黝帘石、红帘石 辉石类 普通辉石、顽火辉石
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[1] 曾方侣, 姜楷, 黄超, 等. 砂岩中重矿物的成因意义[J]. 四川地质学报, 2020, 40(1):26-29,50 doi: 10.3969/j.issn.1006-0995.2020.01.006 ZENG Fanglü, JIANG Kai, HUANG Chao, et al. Genetic significance of heavy minerals in sandstone [J]. Acta Geologica Sichuan, 2020, 40(1): 26-29,50. doi: 10.3969/j.issn.1006-0995.2020.01.006
[2] 许苗苗, 魏晓椿, 杨蓉, 等. 重矿物分析物源示踪方法研究进展[J]. 地球科学进展, 2021, 36(2):154-171 XU Miaomiao, WEI Xiaochun, YANG Rong, et al. Research progress of provenance tracing method for heavy mineral analysis [J]. Advances in Earth Science, 2021, 36(2): 154-171.
[3] 王国茹, 陈洪德, 朱志军, 等. 川东南-湘西地区志留系小河坝组砂岩中重矿物特征及地质意义[J]. 成都理工大学学报:自然科学版, 2011, 38(1):7-14 WANG Guoru, CHEN Hongde, ZHU Zhijun, et al. Characteristics and geological implications of heavy minerals in Lower Silurian Xiaoheba Formation sandstones in Southeast Sichuan-West Hunan [J]. Journal of Chengdu University of Technology: Science & Technology Edition, 2011, 38(1): 7-14.
[4] 李明月, 孙学军, Karki K, 等. 喜马拉雅山中段柯西河跨境流域河流沉积物的矿物和元素特征[J]. 矿物岩石地球化学通报, 2019, 38(5):989-997 LI Mingyue, SUN Xuejun, Karki K, et al. Mineral and elemental characteristics of bed sediments in the Trans-boundary Koshi River Basin in the central Himalayas [J]. Bulletin of Mineralogy, Petrology and Geochemistry, 2019, 38(5): 989-997.
[5] 周国华, 孙彬彬, 刘占元, 等. 中国东部主要河流稀土元素地球化学特征[J]. 现代地质, 2012, 26(5):1028-1042 doi: 10.3969/j.issn.1000-8527.2012.05.024 ZHOU Guohua, SUN Binbin, LIU Zhanyuan, et al. Geochemical feature of rare earth elements in major rivers of eastern China [J]. Geoscience, 2012, 26(5): 1028-1042. doi: 10.3969/j.issn.1000-8527.2012.05.024
[6] Singh P, Rajamani V. REE geochemistry of recent clastic sediments from the Kaveri floodplains, southern India: Implication to source area weathering and sedimentary processes [J]. Geochimica et Cosmochimica Acta, 2001, 65(18): 3093-3108. doi: 10.1016/S0016-7037(01)00636-6
[7] Tripathi J K, Ghazanfari P, Rajamani V, et al. Geochemistry of sediments of the Ganges alluvial plains: evidence of large-scale sediment recycling [J]. Quaternary International, 2007, 159(1): 119-130. doi: 10.1016/j.quaint.2006.08.016
[8] 童胜琪, 刘志飞, Le K P, 等. 红河盆地的化学风化作用: 主要和微量元素地球化学记录[J]. 矿物岩石地球化学通报, 2006, 25(3):218-225 doi: 10.3969/j.issn.1007-2802.2006.03.002 TONG Shengqi, LIU Zhifei, Le K P, et al. Chemical weathering in the Red River Basin: records of major and trace elemental geochemistry [J]. Bulletin of Mineralogy, Petrology and Geochemistry, 2006, 25(3): 218-225. doi: 10.3969/j.issn.1007-2802.2006.03.002
[9] 刘文, 徐士进, 杨杰东, 等. 金沙江河流悬浮物与沉积物的矿物学特征及其表生地球化学意义[J]. 矿物岩石地球化学通报, 2007, 26(2):164-169 doi: 10.3969/j.issn.1007-2802.2007.02.012 LIU Wen, XU Shijin, YANG Jiedong, et al. Mineralogical characteristics of suspended matters and sediments in the Jinshajiang River and their superficial geochemical significance [J]. Bulletin of Mineralogy, Petrology and Geochemistry, 2007, 26(2): 164-169. doi: 10.3969/j.issn.1007-2802.2007.02.012
[10] 周天琪, 吴朝东, 袁波, 等. 准噶尔盆地南缘侏罗系重矿物特征及其物源指示意义[J]. 石油勘探与开发, 2019, 46(1):65-78 ZHOU Tianqi, WU Chaodong, YUAN Bo, et al. New insights into multiple provenances evolution of the Jurassic from heavy minerals characteristics in southern Junggar Basin, NW China [J]. Petroleum Exploration and Development, 2019, 46(1): 65-78.
[11] Song H Y, Liu J Q, Yin P, et al. Characteristics of heavy minerals and quantitative provenance identification of sediments from the muddy area outside the Oujiang estuary since 5.8 kyr [J]. Journal of Ocean University of China, 2018, 17(6): 1325-1335. doi: 10.1007/s11802-018-3684-6
[12] 武法东, 陆永潮, 阮小燕, 等. 重矿物聚类分析在物源分析及地层对比中的应用: 以东海陆架盆地西湖凹陷平湖地区为例[J]. 现代地质, 1996, 10(3):106-112 WU Fadong, LU Yongchao, RUAN Xiaoyan, et al. Application of heavy minerals cluster analysis to study of clastic sources and stratigraphic correlation [J]. Geoscience, 1996, 10(3): 106-112.
[13] Herbig H G, Stattegger K. Late Palaeozoic heavy mineral and clast modes from the Betic Cordillera (southern Spain): transition from a passive to an active continental margin [J]. Sedimentary Geology, 1989, 63(1-2): 93-108. doi: 10.1016/0037-0738(89)90073-0
[14] 冉波, 王成善, 朱利东, 等. 距今40~30Ma时期青藏高原北缘酒西盆地沉积物重矿物分析和构造意义[J]. 地学前缘, 2008, 15(5):388-397 doi: 10.3321/j.issn:1005-2321.2008.05.040 RAN Bo, WANG Chengshan, ZHU Lidong, et al. Analysis of heavy minerals in sediments of Jiuxi Basin in north margin of the Tibet plateau in 40-30 Ma and its tectonic implication [J]. Earth Science Frontiers, 2008, 15(5): 388-397. doi: 10.3321/j.issn:1005-2321.2008.05.040
[15] 宋春晖, 孙淑荣, 方小敏, 等. 酒西盆地晚新生代沉积物重矿物分析与高原北部隆升[J]. 沉积学报, 2002, 20(4):552-559 doi: 10.3969/j.issn.1000-0550.2002.04.004 SONG Chunhui, SUN Shurong, FANG Xiaomin, et al. Analysis of tectonic uplift and heavy minerals of sediments on Jiuxi Basin in the northern margin of Tibetan Plateau since the late Cenozoic [J]. Acta Sedimentologica Sinica, 2002, 20(4): 552-559. doi: 10.3969/j.issn.1000-0550.2002.04.004
[16] 方世虎, 郭召杰, 贾承造, 等. 准噶尔盆地南缘中-新生界沉积物重矿物分析与盆山格局演化[J]. 地质科学, 2006, 41(4):648-662 doi: 10.3321/j.issn:0563-5020.2006.04.008 FANG Shihu, GUO Zhaojie, JIA Chengzao, et al. Meso-cenozoic heavy minerals' assemblages in the southern Junggar Basin and its implications for basin-orogen pattern [J]. Chinese Journal of Geology, 2006, 41(4): 648-662. doi: 10.3321/j.issn:0563-5020.2006.04.008
[17] 赵雪松, 高志勇, 冯佳睿, 等. 库车前陆盆地三叠系: 新近系重矿物组合特征与盆山构造演化关系[J]. 沉积学报, 2014, 32(1):68-77 ZHAO Xuesong, GAO Zhiyong, FENG Jiarui, et al. Triassic-neogene heavy minerals' assemblages characteristics and Basin-Orogen tectonic evolution relationship in the Kuqa Foreland Basin [J]. Acta Sedimentologica Sinica, 2014, 32(1): 68-77.
[18] Cheng L Q, Song Y G, Chang H, et al. Heavy mineral assemblages and sedimentation rates of eastern Central Asian loess: paleoenvironmental implications [J]. Palaeogeography, Palaeoclimatology, Palaeoecology, 2020, 551: 109747. doi: 10.1016/j.palaeo.2020.109747
[19] 中国地质科学院地矿所. 砂矿物鉴定手册[M]. 北京: 地质出版社, 1977 Chinese Academy of Geological Sciences. Handbook of Sand Mineral Identification[M]. Beijing: Geological Publishing House, 1977.
[20] 谢小敏, 李利, 袁秋云, 等. 应用TIMA分析技术研究Alum页岩有机质和黄铁矿粒度分布及沉积环境特征[J]. 岩矿测试, 2021, 40(1):50-60 XIE Xiaomin, LI Li, YUAN Qiuyun, et al. Grain size distribution of organic matter and pyrite in Alum shales characterized by TIMA and its paleo-environmental significance [J]. Rock and Mineral Analysis, 2021, 40(1): 50-60.
[21] 陈倩, 宋文磊, 杨金昆, 等. 矿物自动定量分析系统的基本原理及其在岩矿研究中的应用: 以捷克泰思肯公司TIMA为例[J]. 矿床地质, 2021, 40(2):345-368 CHEN Qian, SONG Wenlei, YANG Jinkun, et al. Principle of automated mineral quantitative analysis system and its application in petrology and mineralogy: an example from TESCAN TIMA [J]. Mineral Deposits, 2021, 40(2): 345-368.
[22] Sutherland D N, Gottlieb P. Application of automated quantitative mineralogy in mineral processing [J]. Minerals Engineering, 1991, 4(7-11): 753-762. doi: 10.1016/0892-6875(91)90063-2
[23] Haberlah D, Williams M A J, Halverson G, et al. Loess and floods: high-resolution multi-proxy data of Last Glacial Maximum (LGM) slackwater deposition in the Flinders Ranges, semi-arid South Australia [J]. Quaternary Science Reviews, 2010, 29(19-20): 2673-2693. doi: 10.1016/j.quascirev.2010.04.014
[24] Martin R S, Mather T A, Pyle D M, et al. Composition‐resolved size distributions of volcanic aerosols in the Mt. Etna plumes [J]. Journal of Geophysical Research:Atmospheres, 2008, 113(D17): D17211. doi: 10.1029/2007JD009648
[25] Speirs J C, McGowan H A, Neil D T. Polar eolian sand transport: grain characteristics determined by an automated scanning electron microscope (QEMSCAN®) [J]. Arctic, Antarctic, and Alpine Research, 2008, 40(4): 731-743. doi: 10.1657/1523-0430(07-029)[SPEIRS]2.0.CO;2
[26] Meyer M C, Austin P, Tropper P. Quantitative evaluation of mineral grains using automated SEM–EDS analysis and its application potential in optically stimulated luminescence dating [J]. Radiation Measurements, 2013, 58: 1-11. doi: 10.1016/j.radmeas.2013.07.004
[27] 孙白云. 黄河、长江和珠江三角洲沉积物中碎屑矿物的组合特征[J]. 海洋地质与第四纪地质, 1990, 10(3):23-34 SUN Baiyun. Detrital mineral assemblages in the Huanghe, Changjiang and Zhujiang River delta sediments [J]. Marine Geology & Quaternary Geology, 1990, 10(3): 23-34.
[28] 邵磊, 李长安, 张玉芬, 等. 长江川江段现代沉积物的重矿物组合特征[J]. 地质科技情报, 2010, 29(3):49-54 doi: 10.3969/j.issn.1000-7849.2010.03.007 SHAO Lei, LI Chang’an, ZHANG Yufen, et al. Heavy mineral assemblages in modern sediments of the Chuanjiang River [J]. Geological Science and Technology Information, 2010, 29(3): 49-54. doi: 10.3969/j.issn.1000-7849.2010.03.007
[29] 李维东. 黄河上游晚新生代沉积物的物源分析与河流演化[D]. 中国地质科学院博士学位论文, 2020 LI Weidong. Provenance analysis of the Late Cenozoic sediment of the Upper Yellow River and its evolution[D]. Doctor Dissertation of Chinese Academy of Geological Sciences, 2020.
[30] 王嘉新, 谢远云, 康春国, 等. 哈尔滨荒山岩芯重矿物特征对松花江第四纪水系演化的指示[J]. 第四纪研究, 2020, 40(1):79-94 doi: 10.11928/j.issn.1001-7410.2020.01.08 WANG Jiaxin, XIE Yuanyun, KANG Chunguo, et al. The indication of the heavy mineral characteristics of the core in Harbin Huangshan to the Quaternary drainage evolution of Songhua River [J]. Quaternary Sciences, 2020, 40(1): 79-94. doi: 10.11928/j.issn.1001-7410.2020.01.08
[31] 魏振宇, 谢远云, 康春国, 等. 早更新世松花江水系反转: 来自荒山岩芯Sr-Nd同位素特征指示[J]. 沉积学报, 2020, 38(6):1192-1203 WEI Zhenyu, XIE Yuanyun, KANG Chunguo, et al. The inversion of the Songhua River system in the early pleistocene: implications from Sr-Nd isotopic composition in the Harbin Huangshan cores [J]. Acta Sedimentologica Sinica, 2020, 38(6): 1192-1203.
[32] Xie Y Y, Kang C G, Chi Y P, et al. Reversal of the middle-upper Songhua River in the late Early Pleistocene, Northeast China [J]. Geomorphology, 2020, 369: 107373. doi: 10.1016/j.geomorph.2020.107373
[33] 宋国利, 刘钊, 于桂云. 黑龙江省松花江流域主要岩石类型中若干元素的背景含量及其环境意义[J]. 哈尔滨师范大学自然科学学报, 1986(4):113-121 SONG Guoli, LIU Zhao, YU Guiyun. Background contents of some elements in the main rock types of the Songhua River basin in Heilongjiang Province and their environmental significance [J]. Natural Science Journal of Harbin Normal University, 1986(4): 113-121.
[34] 张玉娟, 赵鹤, 钟浩. 松花江流域(哈尔滨段)景观格局脆弱性高程分异[J]. 测绘与空间地理信息, 2020, 43(5):11-15,18 doi: 10.3969/j.issn.1672-5867.2020.05.004 ZHANG Yujuan, ZHAO He, ZHONG Hao. Elevation differentiation of landscape pattern vulnerability in Songhua River Basin (Harbin Section) [J]. Geomatics & Spatial Information Technology, 2020, 43(5): 11-15,18. doi: 10.3969/j.issn.1672-5867.2020.05.004
[35] 董爱民. 松花江流域地势图晕渲配色方案及优化[J]. 北京测绘, 2021, 35(7):981-985 DONG Aimin. Color scheme and optimization of shading in relief map of Songhua River Basin [J]. Beijing Surveying and Mapping, 2021, 35(7): 981-985.
[36] 孙忠, 贾长青. 松花江流域蓄滞洪区建设有关问题探讨[J]. 东北水利水电, 2007, 25(10):31-33 doi: 10.3969/j.issn.1002-0624.2007.10.012 SUN Zhong, JIA Changqing. Discussion on detention basin construction in Songhuajiang river basin [J]. Water Resources & Hydropower of Northeast China, 2007, 25(10): 31-33. doi: 10.3969/j.issn.1002-0624.2007.10.012
[37] Wu F Y, Yang J H, Lo C H, et al. The Heilongjiang Group: a Jurassic accretionary complex in the Jiamusi Massif at the western Pacific margin of northeastern China [J]. Island Arc, 2007, 16(1): 156-172. doi: 10.1111/j.1440-1738.2007.00564.x
[38] 付俊彧, 朱群, 杨雅军, 等. 中华人民共和国(东北)地质图(1∶1500000)[M]. 北京: 地质出版社, 2019: 1-147. FU Junyu, ZHU Qun, YANG Yajun, et al. Geological map of the People’s Republic of China (Northeast) (1: 1500000)[M]. Beijing: Geological Publishing House, 2009: 1-147.
[39] 韩梅, 梁贞堂. 关于松花江河源的再研究[J]. 水利水电技术, 2004, 35(12):10-14,27 doi: 10.3969/j.issn.1000-0860.2004.12.003 HAN Mei, LIANG Zhentang. Another investigation for the source of Songhua River [J]. Water Resources and Hydropower Engineering, 2004, 35(12): 10-14,27. doi: 10.3969/j.issn.1000-0860.2004.12.003
[40] 吴鹏, 谢远云, 康春国, 等. 早更新世晚期松花江水系袭夺: 地球化学和沉积学记录[J]. 地质学报, 2020, 94(10):3144-3160 doi: 10.3969/j.issn.0001-5717.2020.10.024 WU Peng, XIE Yuanyun, KANG Chunguo, et al. The capture of the Songhua River system in the late Early Pleistocene: geochemical and sedimentological records [J]. Acta Geologica Sinica, 2020, 94(10): 3144-3160. doi: 10.3969/j.issn.0001-5717.2020.10.024
[41] 康春国, 李长安, 王节涛, 等. 江汉平原沉积物重矿物特征及其对三峡贯通的指示[J]. 地球科学-中国地质大学学报, 2009, 34(3):419-427 doi: 10.3321/j.issn:1000-2383.2009.03.006 KANG Chunguo, LI Chang’an, WANG Jietao, et al. Heavy minerals characteristics of sediments in Jianghan Plain and its indication to the forming of the Three Gorges [J]. Earth Science-Journal of China University of Geosciences, 2009, 34(3): 419-427. doi: 10.3321/j.issn:1000-2383.2009.03.006
[42] 康春国, 李长安, 谢远云, 等. 哈尔滨地区风尘黄土重矿物特征及物源分析[J]. 自然灾害学报, 2011, 20(4):43-51 KANG Chunguo, LI Chang’an, XIE Yuanyun, et al. Heavy mineral characteristics of eolian loess deposits in Harbin area and its provenance implications [J]. Journal of Natural Disasters, 2011, 20(4): 43-51.
[43] Ward I, Merigot K, McInnes B I A. Application of quantitative mineralogical analysis in archaeological micromorphology: a case study from barrow is., western Australia [J]. Journal of Archaeological Method and Theory, 2018, 25(1): 45-68. doi: 10.1007/s10816-017-9330-6
[44] Yue W, Yue X Y, Zhang L M, et al. Morphology of detrital zircon as a fingerprint to trace sediment provenance: case study of the Yangtze delta [J]. Minerals, 2019, 9(7): 438. doi: 10.3390/min9070438
[45] Dunkl I, von Eynatten H, Andò S, et al. Comparability of heavy mineral data: the first interlaboratory round robin test [J]. Earth-Science Reviews, 2020, 211: 103210. doi: 10.1016/j.earscirev.2020.103210
[46] Ishikawa S T, Gulick V C. An automated mineral classifier using Raman spectra [J]. Computers & Geosciences, 2013, 54: 259-268.
[47] Haddad J E, de Lima Filho E S, Vanier F, et al. Multiphase mineral identification and quantification by laser-induced breakdown spectroscopy [J]. Minerals Engineering, 2019, 134: 281-290. doi: 10.1016/j.mineng.2019.02.025
[48] Rifai K, Paradis M M, Swierczek Z, et al. Emergences of new technology for ultrafast automated mineral phase identification and quantitative analysis using the CORIOSITY laser-induced breakdown spectroscopy (LIBS) system [J]. Minerals, 2020, 10(10): 918. doi: 10.3390/min10100918
[49] Gu Y. Automated scanning electron microscope based mineral liberation analysis an introduction to JKMRC/FEI mineral liberation analyser [J]. Journal of Minerals & Materials Characterization & Engineering, 2003, 2(1): 33-41.
[50] Hrstka T, Gottlieb P, Skála R, et al. Automated mineralogy and petrology-applications of TESCAN Integrated Mineral Analyzer (TIMA) [J]. Journal of Geosciences, 2018, 63(1): 47-63.
[51] Zhang X J, Pease V, Omma J, et al. Provenance of Late Carboniferous to Jurassic sandstones for southern Taimyr, Arctic Russia: a comparison of heavy mineral analysis by optical and QEMSCAN methods [J]. Sedimentary Geology, 2015, 329: 166-176. doi: 10.1016/j.sedgeo.2015.09.008
[52] Schulz B, Sandmann D, Gilbricht S. SEM-based automated mineralogy and its application in geo- and material sciences [J]. Minerals, 2020, 10(11): 1004. doi: 10.3390/min10111004
[53] 狄会哲, 邓宾, 赵高平, 等. 云贵高原河流水系演化与高原形成过程: 基于现代河流沉积物示踪[J]. 四川地质学报, 2018, 38(4):536-541 doi: 10.3969/j.issn.1006-0995.2018.04.002 DI Huizhe, DENG Bin, ZHAO Gaoping, et al. The evolution of the river system on the Yunnan-Guizhou Plateau and formation process of the plateau based on modern river sediment [J]. Acta Geologica Sichuan, 2018, 38(4): 536-541. doi: 10.3969/j.issn.1006-0995.2018.04.002
[54] Nie J S, Peng W B, Pfaff K, et al. Controlling factors on heavy mineral assemblages in Chinese loess and Red Clay [J]. Palaeogeography, Palaeoclimatology, Palaeoecology, 2013, 381-382: 110-118. doi: 10.1016/j.palaeo.2013.04.020
[55] 和钟铧, 刘招君, 张峰. 重矿物在盆地分析中的应用研究进展[J]. 地质科技情报, 2001, 20(4):29-32 doi: 10.3969/j.issn.1000-7849.2001.04.006 HE Zhonghua, LIU Zhaojun, ZHANG Feng. Latest progress of heavy mineral research in the basin analysis [J]. Geological Science and Technology Information, 2001, 20(4): 29-32. doi: 10.3969/j.issn.1000-7849.2001.04.006
[56] 赵红格, 刘池洋. 物源分析方法及研究进展[J]. 沉积学报, 2003, 21(3):409-415 doi: 10.3969/j.issn.1000-0550.2003.03.007 ZHAO Hongge, LIU Chiyang. Approaches and prospects of provenance analysis [J]. Acta Sedimentologica Sinica, 2003, 21(3): 409-415. doi: 10.3969/j.issn.1000-0550.2003.03.007
[57] 朱筱敏. 沉积岩石学[M]. 4版. 北京: 石油工业出版社, 2008: 90-105. ZHU Xiaomin. Sedimentary Petrology[M]. 4th ed. Beijing: Petroleum Industry Press, 2008: 90-105.
[58] 康春国, 李长安, 邵磊. 江汉平原主要河流沉积物重矿物特征与物源区岩性的响应[J]. 第四纪研究, 2009, 29(2):334-342 doi: 10.3969/j.issn.1001-7410.2009.02.18 KANG Chunguo, LI Chang’an, SHAO Lei. Heavy mineral characteristics of river sediments in Jianghan Plain and its response to provenance rock types [J]. Quaternary Sciences, 2009, 29(2): 334-342. doi: 10.3969/j.issn.1001-7410.2009.02.18
[59] 胡鹏, 鲍志东, 于兴河, 等. 碎屑重矿物差异与物源演化: 以长岭凹陷乾北地区青三段-姚一段为例[J]. 中国矿业大学学报, 2017, 46(2):375-387 HU Peng, BAO Zhidong, YU Xinghe, et al. Detrital heavy mineral difference and its implication for provenance: a case study of the third member of Qingshankou formation and the first member of Yaojia formation in Qianbei area, Changling sag [J]. Journal of China University of Mining & Technology, 2017, 46(2): 375-387.
[60] 蔡芃睿, 王涛, 王宗起, 等. 大兴安岭中段乐平统-中三叠统沉积物源分析: 来自重矿物组合及碎屑锆石年代学证据[J]. 岩石学报, 2019, 35(11):3549-3564 doi: 10.18654/1000-0569/2019.11.18 CAI Pengrui, WANG Tao, WANG Zongqi, et al. Lopingian to Middle Triassic provenance analysis of sedimentary rocks in the middle segment of the Da Hinggan Mountains: evidence from the heavy mineral assemblage and the detrital zircon U-Pb ages [J]. Acta Petrologica Sinica, 2019, 35(11): 3549-3564. doi: 10.18654/1000-0569/2019.11.18
[61] 马丽芳. 中国地质图集[M]. 北京: 地质出版社, 2002 MA Lifang. Geological Atlas of China[M]. Beijing: Geological Publishing House, 2002.
[62] 和钟铧, 刘招君, 郭巍. 柴达木盆地北缘大煤沟剖面重矿物分析及其地质意义[J]. 世界地质, 2001, 20(3):279-284,312 doi: 10.3969/j.issn.1004-5589.2001.03.012 HE Zhonghua, LIU Zhaojun, GUO Wei. The heavy mineral analysis and its geological significance of Dameigou section in northern Caidam Basin [J]. World Geology, 2001, 20(3): 279-284,312. doi: 10.3969/j.issn.1004-5589.2001.03.012
[63] 苗小龙, 杜燕. 与胡修棉的讨论: 水流搬运与沉积过程中掺和作用对碎屑颗粒的重要影响[J]. 古地理学报, 2017, 19(4):648-652 doi: 10.7605/gdlxb.2017.04.050 MIAO Xiaolong, DU Yan. Discussion with Hu: significant influence of mixing action to clastic particles during the process of flowing transportation and sedimentation [J]. Journal of Palaeogeography, 2017, 19(4): 648-652. doi: 10.7605/gdlxb.2017.04.050
[64] 胡修棉. 物源分析的一个误区: 砂粒在河流搬运过程中的变化[J]. 古地理学报, 2017, 19(1):175-184 doi: 10.7605/gdlxb.2017.01.014 HU Xiumian. A misunderstanding in provenance analysis: sand changes of mineral, roundness, and size in flowing-water transportation [J]. Journal of Palaeogeography, 2017, 19(1): 175-184. doi: 10.7605/gdlxb.2017.01.014
[65] Morton A C, Hallsworth C. Identifying provenance-specific features of detrital heavy mineral assemblages in sandstones [J]. Sedimentary Geology, 1994, 90(3-4): 241-256. doi: 10.1016/0037-0738(94)90041-8
[66] Morton A C, Hallsworth C. Chapter 7 stability of detrital heavy minerals during burial diagenesis [J]. Developments in Sedimentology, 2007, 58: 215-245.
[67] 蒋玺, 陈文奇, 宁凡, 等. 贵州高原北部河流阶地发育与喀斯特地貌演化[J]. 地理研究, 2021, 40(1):81-92 doi: 10.11821/dlyj020200485 JIANG Xi, CHEN Wenqi, NING Fan, et al. River terraces in the northern Guizhou Plateau and their implications for karst landform evolution [J]. Geographical Research, 2021, 40(1): 81-92. doi: 10.11821/dlyj020200485
[68] 董铭, 苏怀, 史正涛, 等. 金沙江金江街段河流阶地年代及对河谷水系演化历史的启示[J]. 地理学报, 2018, 73(9):1728-1736 doi: 10.11821/dlxb201809009 DONG Ming, SU Huai, SHI Zhengtao, et al. The age of river terraces in the Jinjiangjie reach of the Jinsha River and its implications for valley and drainage evolution [J]. Acta Geographica Sinica, 2018, 73(9): 1728-1736. doi: 10.11821/dlxb201809009
[69] 陆洁民, 郭召杰, 赵泽辉, 等. 新生代酒西盆地沉积特征及其与祁连山隆升关系的研究[J]. 高校地质学报, 2004, 10(1):50-61 doi: 10.3969/j.issn.1006-7493.2004.01.004 LU Jiemin, GUO Zhaojie, ZHAO Zehui, et al. Cenozoic sedimentation characteristics of Jiuxi Basin and uplift history of northern Qilian Mountain [J]. Geological Journal of China Universities, 2004, 10(1): 50-61. doi: 10.3969/j.issn.1006-7493.2004.01.004
[70] 程岩, 刘月, 李富祥, 等. 鸭绿江口及邻近浅海碎屑矿物特征与物源辨识[J]. 地理研究, 2010, 29(11):1950-1960 CHENG Yan, LIU Yue, LI Fuxiang, et al. Detrital mineral characteristics and material source identification in surface sediments of Yalu River estuary and adjacent waters [J]. Geographical Research, 2010, 29(11): 1950-1960.
[71] 牛东风, 李保生, 王丰年, 等. 不同沉积相重矿物组成及其对气候的指示: 以米浪沟湾全新统MGS1层段为例[J]. 实验室研究与探索, 2015, 34(7):7-11 doi: 10.3969/j.issn.1006-7167.2015.07.003 NIU Dongfeng, LI Baosheng, WANG Fengnian, et al. Heavy mineral composition and its climatic indication for the MGS1 Segment in the holocene in Milanggouwan [J]. Research and Exploration in Laboratory, 2015, 34(7): 7-11. doi: 10.3969/j.issn.1006-7167.2015.07.003
[72] 李艳, 李安春, 黄朋. 大连湾近海表层沉积物重矿物组合分布特征及其物源环境指示[J]. 海洋地质与第四纪地质, 2011, 31(6):13-20 LI Yan, LI Anchun, HUANG Peng. Distribution of heavy mineral assemblages in subsurface sediments of Dalian bay and their implications for provenance and environment [J]. Marine Geology & Quaternary Geology, 2011, 31(6): 13-20.
[73] 马婉仙. 重砂测量与分析[M]. 北京: 地质出版社, 1990 MA Wanxian. Heavy Sand Measurement and Analysis[M]. Beijing: Geological Publishing House, 1990.
[74] 程瑜, 李向前, 赵增玉, 等. 苏北盆地TZK9孔磁性地层及重矿物组合特征研究[J]. 地质力学学报, 2016, 22(4):994-1003 doi: 10.3969/j.issn.1006-6616.2016.04.017 CHENG Yu, LI Xiangqian, ZHAO Zengyu, et al. Magnetostratigraphy and heavy minerals records of TZK9 core in Subei Basin [J]. Journal of Geomechanics, 2016, 22(4): 994-1003. doi: 10.3969/j.issn.1006-6616.2016.04.017
[75] Milliken K L, Mack L E. Subsurface dissolution of heavy minerals, Frio Formation sandstones of the ancestral Rio Grande Province, South Texas [J]. Sedimentary Geology, 1990, 68(3): 187-199. doi: 10.1016/0037-0738(90)90111-6
[76] 李双建, 石永红, 王清晨. 碎屑重矿物分析对库车坳陷白垩: 第三纪物源变化的指示[J]. 沉积学报, 2006, 24(1):28-35 doi: 10.3969/j.issn.1000-0550.2006.01.004 LI Shuangjian, SHI Yonghong, WANG Qingchen. The analysis of detrital heavy minerals in cretaceous-tertiary sandstones, Kuqa depression and their implications for provenance [J]. Acta Sedimentologica Sinica, 2006, 24(1): 28-35. doi: 10.3969/j.issn.1000-0550.2006.01.004
[77] Smale D, Morton A C. Heavy mineral suites of core samples from the McKee Formation (Eocene-Lower Oligocene), Taranaki: implications for provenance and diagenesis [J]. New Zealand Journal of Geology and Geophysics, 1987, 30(3): 299-306. doi: 10.1080/00288306.1987.10552624
[78] 李红, 李飞, 龚峤林, 等. 混积岩中重矿物形貌学特征及物源意义: 以川北寒武系第二统仙女洞组为例[J]. 沉积学报, 2021, 39(3):525-539 LI Hong, LI Fei, GONG Qiaolin, et al. Morphological Characteristics and Provenance Significance of Heavy Minerals in the Mixed Siliciclastic-carbonate Sedimentation: a case study from the Xiannüdong Formation, Cambrian (Series 2), northern Sichuan [J]. Acta Sedimentologica Sinica, 2021, 39(3): 525-539.
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