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深水重力流沉積模擬研究進展與展望

2025-07-18 00:00:00耿軍陽鮮本忠劉振獻玄碩石浩程余志云
沉積學報 2025年3期

關鍵詞深水重力流;濁流;物理模擬;數值模擬;研究進展第一作者簡介,男,1997年生,博士研究生,深水沉積學,E-mail:gjy201572211@163.com通信作者,男,教授,博士生導師,沉積學與儲層地質學,E-mail:xianbzh@cup.edu.cn

中圖分類號 P512.2 文獻標志碼A DOI: 10.14027/j.issn.1000-0550.2024.074 CSTR: 32268.14/j.cjxb.62-1038.2024.074

0 引言

深水重力流是由重力驅動的,富含陸源碎屑的高密度流體[2-3],其攜帶的大量陸源碎屑在海底形成了地球上最大的復合沉積體,儲存了全球 35% 的深水油氣資源。現代海底監測顯示,一期重力流事件可以攜帶超過 150km3 的沉積物,以 19m/s 的速度運行,對海底通信電纜及輸油管道安全具有重大威脅。此外,深水重力流可以將大量陸源和海洋的有機碳輸送至深水環境,在地質時間尺度上實現碳循環的中轉和匯聚,有助于調節全球氣候[4,8-9]。深水重力流具有典型的事件性特征,可以由火山噴發地震活動[11-12]、風暴[13-14]、洪水[15-17]等多種作用觸發。因此,重力流沉積也是地質歷史時期洪水、火山或古地震等極端事件的有效記錄者。最新研究指出,重力流也可不需要明顯的外部觸發機制[8,超低濃度(沉積物含量約 0.07kg/m3 的羽流自加速同樣可以形成深水重力流,因此深水重力流的發生可能遠比想象中更為頻繁。

自1888年Forel2報道日內瓦湖密度流以來,重力流研究迅速發展。時至今日,眾多學者在重力流的沉積類型[21-24]和沉積模式[25-26等方面取得了長足的進步。Middletonetal.根據顆粒支撐機理將重力流劃分為碎屑流、顆粒流、液化流和濁流4種類型;Lowe22依據流體流動狀態,將濁流進一步分為高密度濁流和低密度濁流;Tallingetal.23根據流體黏土含量和流變學特征將碎屑流分為黏性碎屑流和非黏性碎屑流(砂質碎屑流);Baasetal.24發現隨著重力流中黏土含量的增大,會出現一種介于牛頓流體和非牛頓流體之間的過渡型流體;Walker25結合古代露頭和現代實例,提出了經典的海底扇模式;Shanmugam[26]總結了斜坡環境下滑塌型重力流的演化過程,建立了以碎屑流為主導的斜坡扇模式。近年來,由盆外洪水入海(湖)形成的洪水型重力流(異重流)引發了新一輪的重力流研究熱潮[27-29]。事實上,重力流沉積過程極為復雜,觸發機制[16.30-31]、流體性質[23.32]、先存地貌[3-3等多種因素都可能導致沉積產物的巨大差異,經典的沉積模式并非“萬能模板”,新的問題要求研究者們采取針對性的研究手段,提出更合理的解釋。

傳統的重力流研究主要依靠野外露頭、鉆井、地震等手段,以靜態沉積現象分析為基礎從而對沉積產物的形成過程[37-39]、影響因素[40-43]、分布模式[26.4進行解釋。現場觀測能夠直接獲取真實尺度下的動態數據,但限于深水重力流沉積事件的偶然性和發生場所的特殊性,現場流體監測難度較大。相比之下,沉積模擬實驗能夠在不同尺度下通過控制邊界條件,再現各種自然環境中的沉積過程和水動力特征,是理解和認識深水重力流沉積動力過程和沉積規律的最重要手段。本文在國內外深水重力流沉積模擬實驗相關文獻調研的基礎上,系統梳理重力流沉積模擬發展歷程,從重力流沉積模擬的實驗理論、實驗技術、關鍵應用和最新進展等多個方面展開論述,以期能夠推動國內重力流沉積模擬研究,更好的服務于深水油氣勘探。

深水重力流物理模擬

1.1深水重力流物理模擬發展歷程

重力流沉積物理模擬實驗起源于20世紀初,至今已有100余年的歷史。根據不同時期物理模擬實驗的主要關注點,可以將其分為以下4個階段(圖1)。

1960年之前,沉積現象觀察階段。1914年,Gilbert45通過水槽實驗觀察到了類似牽引毯(tractioncarpet)的構造,將其稱為躍變層(saltationlayer),此外他還觀察到沉積物濃度自下而上逐步遞減的現象。Kuenenetal.4于1950年開展了第一次濁流實驗,認識到濁流在深海沉積物輸運的重要性,提出遞變層理是濁流的重要標志,促進了濁流理論的誕生,被譽為\"沉積學研究的一場革命”。

1960一1980年,沉積底形及沉積構造研究階段。Simonsetal.49基于明渠流水實驗討論了底床粗糙度對沖積河道底形的影響,總結了不同流態(上部流態、下部流態和過渡態)的底形特征。盡管該研究目標并非是針對深水重力流沉積,但作為首次系統性的水槽底形實驗研究,激發了重力流沉積底形的水槽研究熱潮;此后,Middleton5開展了涌浪型重力流模擬實驗,將涌浪型重力流分為頭部、體部和尾部,還觀察到了高濃度濁流的粗尾遞變(coarse-tailgrading)構造。

1980一2000年,沉積機理及沉積過程研究階段。Southard etal.52提出密度流自懸浮(auto suspension)這一概念,討論了粒度和坡度對沉積物自懸浮能力的影響;Postmaetal.54通過水槽實驗研究了高密度濁流的分層性,發現高密度濁流實際包含下部塑性層流狀的碎屑流和上部稀性濁流兩種性質各異的流體;Knelleretal.55再現了濁流在封閉盆地邊緣遇到障礙物后的反射過程,提出了邊緣斜坡上內孤立波(internalsolitarywaves)的形成機制;Mohrigetal.基于模擬實驗證實了滑水作用(hydroplaning)的存在,為水下碎屑流和滑塊在低坡度下的長距離搬運提供新解釋;Marretal.8利用水槽實驗討論了黏土礦物對水下碎屑流流體演化的控制作用,研究發現不同類型的黏土礦物形成碎屑流的下限濃度差異較大,蒙脫土最低僅需 0.7% 的質量分數即可形成碎屑流,而高嶺土則需 7% 。

2000年至今,沉積一地貌動力學定量研究階段。高精度監測儀器的快速發展,使得深水重力流水槽實驗逐漸轉向定量階段。Ilstadetal.2基于不同黏土含量條件下重力流模擬實驗,討論了黏土礦物含量對重力流流體類型、流速剖面及沉積厚度分布的影響;Lambetal.基于異重流沉積模擬實驗指出平均深度的異重流流速與河流洪水流量變化相關性較差,而沉積物中的粗細顆粒一定程度上可以反映多重流動的速度波動和河流流量大小;deLeeuwetal.64]認為早期堤岸沉積的形成可能是受控于平坦斜坡上的濁流自生過程,而非濁流漫溢產物;Pohletal.提出了新的流動機制一一流動松弛用以解釋海底水道一朵體過渡帶大量沉積底形的發育機制;Miramontesetal.通過水槽實驗再現了重力流一等深流交互體系中重力流水道的單向遷移過程,總結了等深流流速對堤岸沉積的影響。中國方面,劉忠保等[59重現了陡坡帶砂質碎屑流的形成過程,指出斜坡長度、基準面的相對變化控制了碎屑流沉積體的發育規模和發育部位;鄢繼華等模擬了不同觸發條件下三角洲前緣濁積砂體的形成過程和分布規律。

圖1 深水重力流沉積物理與數值模擬研究階段劃分與主要進展

1.2重力流沉積物理模擬實驗理論與技術

1.2.1 物理模擬實驗原理

物理模擬實驗的關鍵是要解決模型與原型之間 相似性的問題,實驗過程中必須遵從相似性理論。

模型與原型之間必須遵守的相似理論包括幾何相似、運動相似及動力相似

幾何相似是保持實驗模型的幾何形狀、大小與實際原型相似;同時,實驗樣品的物理和力學特性,如密度、粒度、磨圓度等,應與原型相匹配。運動相似要求實驗過程中流體運動狀態和實際情況相似。此外,保持模擬實驗與實際地質過程的時間尺度相似,有助于確保實驗結果能夠準確反映實際流體流動行為。

動力相似要求實驗中液體和顆粒之間的流動和相互作用的動力行為與實際流體的動力行為相似。經典的濁流模擬實驗用弗勞德數 (Fr ,表征為流體動量和重力之比)以及雷諾數 (Re ,表征為動量和黏性力的比值)描述濁流運動的動力特征,實驗過程中一般保證 Fr 與自然值接近, Re 高于層流的閾值以保證紊流狀態。然而,該方法忽略了對顆粒運動狀態的描述,不能確保顆粒主要以懸移態運動。deLeeuwetal.4用希爾茲數 (τ*) ,湍流剪切應力與重力的比值)和顆粒雷諾數 (Rep) 描述顆粒運動狀態,并結合重力流海底監測和水槽實驗資料[71-7],建立顆粒運動機制圖版以約束重力流沉積模擬實驗中的動力邊界條件,從而提高實驗結果的可信度和可靠性(圖2)。

1.2.2 監測技術

重力流物理模擬研究中實驗數據的采集主要可分為三類:水下流速測量、懸移質濃度測量和沉積地貌掃描。水下重力流的速度場是物理模擬實驗最關注的參數之一。目前水槽實驗中主要的測速方法可分為多普勒測速和粒子成像測速兩類,其中多普勒測速法依據測量原理和測量范圍又可分為激光多普勒測速(LDA)、超聲多普勒測速剖面(UDVP)和聲學多普勒測速(ADV)[8]。LDA側重于高空間分辨率的點測量,ADV則注重于高時間分辨率的瞬時三維點測量,UDVP可以實現垂直剖面的流速監測。粒子成像技術(PIV)利用高速相機捕捉示蹤粒子的運動信息,可通過計算機技術生成高精度流場數據,但僅適用于低濃度二維水槽或重力流沉降實驗[78。此外,懸移質濃度測量、沉積地貌掃描等技術也是重力流沉積物理模擬實驗的關鍵手段,對重力流定量化研究具有重要意義。

1.2.3 國內外重力流物理模擬實驗室

20世紀中期以后,重力流沉積模擬迅速發展,以美國、英國、荷蘭等發達國家為代表,全球各大科研機構相繼建立了一批重力流沉積模擬水槽實驗平臺(表1)。國外重力流物理模擬水槽實驗類型多樣,研究內容廣泛,在重力流流體結構、沉積過程、砂體分布等方面涌現出一批代表性成果。如杜倫大學的MatthieuCartigny團隊對超臨界重力流底形和水躍作用進行了深入研究[380;烏德勒支大學的JorisEggenhuisen團隊基于水槽實驗對濁流與深水地貌之間的作用機制提出了新的見解[6-67,74-75];Jaco Baas 團隊在利茲大學期間專注于細粒黏性重力流物理特性和沉積特征[24.76.88];GaryParker團隊在明尼蘇達大學期間針對濁流的沉積物輸運過程和形態動力學開展了一些基礎性研究[89-92]。

20世紀70一80年代長春地質學院和中科院地質所率先揭開了中國沉積物理模擬研究的序幕。隨后,由于國內油氣勘探的需求,長江大學建立了CNPC湖盆沉積模擬實驗室。中國石油大學(華東)、中國地質大學(北京)等也開始各自籌建沉積物理模擬實驗室。當前我國的重力流沉積物理模擬研究主要關注于砂體發育特征及分布規律[59.93-95],對沉積動力過程和地層動力研究比較缺乏,同時相應的監測設備較為落后,定量化與自動化程度較低。由于逐漸認識到物理模擬實驗對沉積學基礎理論研究的重要性,目前中國石油大學(北京)成都理工大學等高校正在籌建現代化沉積物理模擬實驗平臺。

圖2顆粒運動狀態示意圖(據文獻[64]修改)Fig.2Motion state diagram of particles (modified from reference [64])
表1全球主要重力流沉積模擬實驗室Table1 Global major gravity-flow sedimentary simulation laboratories

1.3重力流沉積物理模擬研究主要進展

1.3.1物質組成對流體性質的影響

沉積物組成是決定流體性質的最基本參數,流體的沉積物濃度、砂泥比、黏土類型、顆粒大小等對流體性質均有不同程度的影響。

沉積物濃度直接決定了重力流流體類型,隨著沉積物濃度的降低,碎屑流總是趨于向濁流轉化。一般認為,高密度濁流的體積濃度應大于 6% 或流體密度大于 1.1g/mL[46] ;當沉積物體積濃度達到 25% 時,流體紊流受到完全抑制最終轉化為碎屑流2。沉積物顆粒大小對流體類型與運動狀態同樣具有重要影響。Elerianetal.85發現較大的顆粒粒徑會顯著降低濁流的鋒面速度和搬運距離,而顆粒濃度一定程度上可以中和顆粒尺寸對濁流運動的影響,濁流濃度足夠高時,顆粒尺寸對濁流運動的影響已經微乎其微。此外,粗顆粒相較于細顆粒更易形成碎屑流,且搬運距離更遠[59]。黏土礦物和有機質作為流體內聚力的直接來源,能夠有效的抑制濁流的紊流性質,使流體向層流性質的碎屑流轉變[23]。最新研究發現,濁流與碎屑流之間存在著流體性質介于紊流和層流之間的過渡型流體。隨著黏土礦物的增加,濁流會逐步轉化為紊流增強過渡流、上過渡塞流、準層狀塞流等過渡型流體,并伴隨獨特的底床類型[97-98]。然而,不同類型的黏土礦物由于物質組成和分子結構的差異,其吸水膨脹能力顯著不同,蒙脫土的親水性可達高嶺石的60倍9。水槽實驗指出蒙脫土最低僅需 0.7% 的質量分數即可形成碎屑流,而高嶺土則需7% 的質量分數[58]。

1.3.2沉積地貌單元與重力流交互

經典的海底扇模式由深水水道、堤岸、朵體以及水道一朵體過渡帶等組成[25.100]。重力流通過其強大的侵蝕搬運能力塑造不同的沉積單元,沉積單元又因其內部的形態差異反作用于流體運動過程,兩者之間的相互作用是重力流研究的重點內容。

深水水道是深海沉積物輸送的主要途徑[],其內部充填物記錄了源區古氣候變化[2],同時也是良好的油氣儲層[03]。Keeviletal.[4通過彎曲水道模擬實驗指出深水水道的次級流動對沉積物分配具有重要影響,深水水道處的次級流動有利于堤岸外側粗粒沉積物堆積。Kaneetal.認為深水水道中的大型不平衡流動導致水道外彎處沉積大量泥沙,使水道短暫變直,進而增強了深水水道的平面穩定性,使其不易像陸上河道頻繁發生截彎和決口(圖3a)。

水道一朵體過渡帶是連接深水水道和深海盆地的過渡性區域。當濁流離開水道進入深海盆地,流體失去水道的側向限制發生橫向擴散,進而增加了水體的整體摩擦,導致流體減速和懸浮沉積物沉降,并在水道末端堆積形成朵體復合體。然而,多地海底觀測在水道一朵體過渡帶發現的沖刷場(scourfield)構造[105-108],表明水道—朵體過渡帶可能并非以沉積作用為主。Komar[0]認為沖刷場的形成是由于濁流失去限制性后,流體從超臨界流向亞臨界流轉變,伴隨而來的水躍作用增強了流體的侵蝕能力。Pohletal.在室內水槽實驗中并未發現水道一朵體過渡帶的水躍作用及其伴生的流厚突然增加現象[。結合實驗結果,Pohletal.提出流動松弛機制用來解釋沖刷場現象(圖3b)。當濁流離開水道后,流體失去橫向限制向兩側擴散,流速整體降低,但流體厚度減薄的同時也導致濁流頭部最大流速深度相應降低,進而導致靠近底床的流體剪切速度增大(圖3c),由此增強了濁流的基底剪切能力,有利于沖刷場的形成。

圖3不同沉積單元內部重力流沉積一動力特征 (a)平衡流動和不平衡流動對深水水道的改造(據文獻[73]修改);(b)流動松弛機制(據文獻[66]修改);(c)濁流失去限制性時的水動力參數(據文獻[6]修改) Fig.3Sedimentary-hydrodynamic characteristics of gravity flow in different sedimentary units

1.3.3重力流與等深流交互

深水環境主要發育重力流和等深流兩種沉積物輸送機制。重力流是一種瞬時、高能的事件性流體,而等深流則是受地球自轉作用力影響而產生的持續存在的低能流體。等深流可以改造先存或正在沉積的重力流水道,形成等深流一重力流混合沉積體系[110-12]

Miramontesetal.通過水槽實驗再現了重力流水道的單向遷移模式。當濁流和等深流同時處于活躍時期,一定強度的等深流可以使濁流發生偏移和不對稱溢出,在盆地下游形成不對稱的堤岸系統。

同時,等深流流速對堤岸發育程度具有重要影響,流速越快,上游堤岸沉積越厚,下游堤岸沉積越寬,并導致水道向上游遷移(圖4a\~d)。Fedeleetal.3發現重力流水道的遷移方向取決于等深流流體底部厚度與重力流水道深度的相互關系。當等深流底部邊界層厚度遠小于重力流水道深度時,等深流會完全落入重力流水道,在水道上游處,流體加速下滑,造成侵蝕;下游處,流體減速爬升,并逐漸沉降,由此導致了重力流水道沿等深流流向反向遷移(圖4e);當等深流底部邊界層厚度接近或大于重力流水道深度時,等深流底部邊界層會在水道上游發生分離,等深流攜帶的物質就此沉降,流經水道下游時,底部邊界層與上部等深流附著并收縮,并可能促進沉積物的改造和侵蝕,這種情況下重力流水道順著等深流流動方向遷移(類似于沙丘遷移)圖4f)。

1.3.4超臨界濁流及其底形

超臨界濁流是指密度弗勞德數 (FrD) 大于1的,可通過水躍作用轉化為亞臨界流的深水重力流[09,11415]。研究表明,超臨界濁流與海底峽谷[80.116]深水水道[117-118]、周期階坎[11]等海底地貌的形成密切相關。然而,由于其強大的侵蝕能力,超臨界濁流留下的地質記錄相對較少[63],導致人們對其理解仍然有限。

Sequeiros基于歷年的水槽實驗和現場觀測數據指出當底床坡度大于 0.5° 時,濁流就具備了轉化成超臨界流的條件。隨著弗勞德數的增大,超臨界流底形依次向著逆行沙丘、不穩定逆行沙丘、沖坑和沖槽、旋回階坎轉變[]。其中逆行沙丘和旋回階坎作為該過程的兩大穩定單元,其沉積記錄在海底觀測中多有發現。水躍(hydraulic jump)作用是超臨界流向亞臨界流的突然過渡,其特征是流體厚度急劇增加,流速下降,流體能量大量損失。Cartignyetal.提出在不考慮流體或沉積物夾帶的前提下,用共軛深度比(水躍前超臨界流厚度/水躍后亞臨界流厚度)來衡量水躍強度等級,將其分為波狀水躍、弱水躍、振蕩水躍、穩定水躍、強水躍五類(圖5)。水躍作用的內部結構受控于共軛深度比,共軛深度比越大,水躍過程中的能量損失越大。

圖4重力流水道遷移模式(a~d) 單向遷移模式(據文獻[67]修改);(e,f)水道雙向遷移模式(據文獻[113]修改)Fig.4Migrationmode of gravity flow channel

Onoetal.通過水槽實驗研究了涌浪型濁流中水躍作用對底床形態、粒度分選的影響。單期涌浪型濁流可以在一個旋回階坎的迎流面下部形成多次沖刷,濁流的頭部、體部和尾部可以在迎流面不同位置產生水躍,從而形成多期沖刷充填體,隨著旋回階坎向上游逐漸遷移,同時產生向上變細的沉積序列。該研究為海底旋回階坎中含多重沖刷特征、向上變細的濁積巖序列[120提供了一種新的成因解釋。

2 深水重力流數值模擬

深水重力流數值模擬是通過數學方法來研究和預測重力流運動行為[121]。其原理基于牛頓力學和流體力學的基本方程(包括質量守恒方程、動量守恒方程和能量守恒方程)8。重力流數值模擬能夠在多個尺度上再現重力流沉積演化過程,明確重力流流體動力參數的時空變化,還可以預測海底扇發育模式與構型樣式,指導深水油氣勘探。由于高濃度流體需要考慮顆粒之間的碰撞運動,極大程度上增加了運算的工作量,目前深水重力流數值模擬研究主要集中在低密度濁流領域。

2.1重力流數值模擬發展歷程

1980年之前,經驗公式和簡化模型階段。1845年,用于描述黏性不可壓縮流體動量守恒的納維一斯托克斯(Navier-Stokes,N-S)方程就此問世。雖然N-S方程理論上可以描述湍流在三維時空內的全部流動細節,但由于湍流瞬時運動的極端復雜性,基于N-S方程的直接數值模擬方法仍然極具挑戰性。為了便于計算機求解,科學家們開始提出簡化的計算模型。1952年,Kuenen首次運用切奇公式評估了1929年紐芬蘭大淺灘的濁流事件。隨后,Ellisonetal.4提出了基于N-S方程簡化的深度平均模型(Depth-averagedmoded),該模型假設流體在垂直方向上的性質變化不顯著,允許通過垂直積分來計算流體動力參數。Chuetal.選取深度平均模型,并根據弗勞德數的變化,將濁流的運動過程分為流動建立、均勻流動、水力跳躍和流動衰減4個階段。基于平均深度理論,Parkeretal.53推導出描述濁流動力學的層平均運動方程,再現了濁流的自加速效應;此后,一些研究者開始將盒子模型[56.122]用于重力流數值模擬,并取得了較好的應用效果。事實上,濁流存在顯著的分層結構54,平均深度模型只能描述濁流平面上的運動過程,而忽略了垂直方向上的運動,限制了計算結果的適用性。

圖5水躍作用的形態和水動力結構(據文獻[63]修改)'ig.5Morphology and hydrodynamic structure of hydraulic jump (modified from reference [63])

1980—2000年,二維混合模型階段。1980年起重力流數值模擬理論迅速發展,形成了以雷諾平均數值模擬(ReynoldsAverage Navier-Stockes,RANS)、大渦模擬(LargeEddySimulation,LES)、直接數值模擬(DirectNumericalSimulation,DNS)為主的3類模擬方法。其中RANS的核心思想是應用湍流統計理論,對N-S方程進行時間平均,從而計算得到時均流場數據[123-124]。由于雷諾平均方程并不封閉,需要引入雷諾應力的平均模型[83]。該法可以提供運動的平均物理量,滿足大多數工程計算需求,但在處理強剪切(靠近墻壁或障礙物)以及低至中等雷諾數流動的區域時計算效果不佳[25-126]。大渦模擬通過特定的濾波函數將湍流的瞬時運動分解為大尺度運動和小尺度脈動,大尺度運動通過N-S方程直接求解,小尺度脈動通過特定的湍流模型進行簡化計算[12]。該方法能夠得到流體瞬時運動的脈動量,但其計算量也遠高于RANS法[128]。此外,為了獲取更高精度的模擬結果,一些研究者開始采用直接數值模擬求解湍流方程的全部參數,但由于湍流運動的復雜性,需要極高的計算資源,且不適用于較高雷諾數的濁流運動模擬[69,129]

2000年至今,高分辨率三維數值模擬階段。隨著計算機處理能力的顯著提升,科學家可以進行高分辨率的三維重力流數值模擬。這使得對復雜地形、多粒度分布以及流體一固體相互作用等的高精度模擬成為可能。如Howlettetal.[3o]利用數值模擬技術研究非限制性濁流對海底褶皺地貌的響應機制,觀測到了濁流的開爾文一亥姆霍茲不穩定性和水躍現象;Abdetal.3模擬了尼日爾三角洲大陸斜坡的海底濁流運動,預測了濁流演化過程和不同粒級顆粒的空間分布。此外,機器學習和人工智能技術被逐漸引入到重力流數值模擬中[132-134]。這些技術有助于優化模型參數,識別模式,甚至預測未知條件下的沉積過程。

2.2 重力流數值模擬平臺

重力流數值模擬起源于20世紀中期48],作為一種重要的工程和科學研究手段,被廣泛用于海洋工程災害評估[135]、河流泥沙運移[136-137]、油氣勘探[138-139]等領域。根據不同的應用需求和模擬目標,眾多研究機構或商業公司開發了各具特色的重力流數值模擬平臺。

Flow-3D是一款由美國FlowScience公司開發的商業計算流體動力學(ComputationalFluidDynamics,CFD)軟件。它基于有限體積法建立三維模型,采用多相漂移通量流法預測濁流運動。Flow-3D將泥沙擴散視為連續相,計算流體空間體積濃度。Flow-3D可以監測濁流在時間和空間上的連續流動特征,包括流動密度、沉積物濃度、粒度離析、空間平均速度場、內部剪切應變率(湍流強度)動態黏度和底部剪切應力等[140]

Fluent軟件起源于謝菲爾德大學的Boysanetal.4開發的CFD代碼,后被ANSYS公司收購,并整合為ANSYSFluent。目前,Fluent已成為應用最為廣泛的商業CFD軟件之一。Fluent軟件基于有限體積法,將流動區域離散化為有限體積,并通過求解連續方程、動量方程和能量方程等基本方程來模擬濁流的流動和傳輸過程。Fluent軟件支持GPU并行計算,能夠顯著降低濁流數值模擬的計算時間[142]。

Delft3D是代爾夫特理工大學開發的開源流體動力模擬軟件。該軟件基于泥沙水動力方程,可以實現沉積物輸運和地貌演變的三維模擬。Delft3D側重于河流、三角洲、浪控等的沉積模擬,同時也可用于預測深水重力流的運動過程和水動力特征[43-144]。

CATS(TheCellularAutomataforTurbiditeSystems)是由法國石油研究院開發的一款用于模擬濁積巖儲層的結構和空間分布的工業軟件。該軟件基于勢能、動能平衡和擴散原理,以臨近單元(元細胞自動機)之間的局部規則對給定地形的濁流流動進行建模。CATS軟件無需求解復雜的水動力方程,計算量小,模擬時間短,對濁積體內部結構刻畫效果較好[138]

Sedsim(Sedsim Forward Stratigraphic Modelling)軟件是由斯坦福大學在20世紀80年代開發的三維地層正演模擬軟件。Sedsim軟件基于簡化的N-S水動力學方程,能夠在地質和工程時間尺度上模擬地層或盆地形成過程。Sedsim軟件可以模擬構造、海平面變化、氣候等因素影響下的多類型沉積過程,廣泛應用于油氣勘探預測中[45](表2)。

2.3重力流數值模擬軟件研究主要進展

2.3.1重力流流體結構和水動力參數

三維數值模擬可從不同尺度、不同角度系統對比分析濁流的動力學特征。模擬過程中可以對關鍵參數進行連續監控,分析其變化所伴隨的沉積響應。Salinasetal.基于重力流數值模擬發現,超臨界濁流具有近床層和界面層組成的雙層結構,兩層流體都表現為高度湍流特性,垂向最大流速出現在近底床層和界面層的交界處(圖 6a,b) ;相比之下,亞臨界濁流(體部)自下而上由近床層、中間層、界面層組成。其中僅近床層具有高度湍流性質,該層沉積物具有良好的混合,向上流體雷諾數減低,至界面層時已與環境水體層出現明顯的光滑界線(圖6c,d)。研究表明,亞臨界流體的三層結構可能與海底水道中濁流的超長體部的形成有關[68]。

密度弗雷德數是區分超臨界濁流與亞臨界濁流的關鍵參數,通常認為超臨界濁流的密度弗勞德數大于1,亞臨界濁流的密度弗勞德數小于1。Huangetal.[14提出重力流的臨界密度弗雷德數不一定是一個恒定值。根據周圍流體的夾帶程度和重力流的密度變化,重力流的臨界密度弗雷德數存在3種情況,大于1,不存在或小于1。此外,傳統觀點認為異重流入水后,沉積物顆粒的不斷沉降會降低異重流的密度,導致異重流的搬運距離較短。然而最新研究顯示,沉積物顆粒一鹽的擴散率差異可以使異重流轉為含鹽濁流,異重流損失沉積物的同時會從環境水體(海水)中吸收相應的鹽分,從而維持異重流的密度穩定,并能夠搬運至相當長的距離[147]。

2.3.2 復雜地貌下重力流的沉積過程及分布特征

數值模擬可以提取地下地貌數據,構建多樣化的地質模型,再現深水地貌與重力流沉積的交互過程,并揭示有利沉積體的分布規律。褶皺和斷層作為擠壓構造背景下產生的典型地貌,廣泛存在于陸相斷陷湖盆和深海構造活躍帶,深刻控制著海底沉積物的運輸和沉積[34]。Howlettetal.[30通過數值模擬總結了非限制性濁流對褶皺地貌的響應模式。根據褶皺地貌與濁流的相對大小,可分為大褶皺小濁流和小褶皺大濁流兩種模式(圖7a,b)。當褶皺地貌遠小于濁流體積時,濁流主體能夠越至褶皺后翼,發生水躍作用導致濁流減速、顆粒沉降,在褶皺后翼前緣、后翼反斜坡、褶皺前翼形成明顯的沉積區;當褶皺地貌遠大于濁流體積時,濁流主體在褶皺前翼減速沉積,少量低密度流體越過褶皺后翼并發生水躍作用。Geetal.通過數值模擬揭示了真實尺度下濁流流經正斷層地貌時的沉積過程和沉積模式(圖7c\~e)。研究發現該模式與傳統的斜坡扇模型2存在較大差異:受斷層地貌影響,砂體成斑狀分布,自上而下可分為四個主要沉積區:濁流出口堆積區、下盤邊緣堆積區、斷層頂部堆積區以及上盤頂部堆積區。

表2重力流沉積數值模擬軟件主要優缺點Table2Mainadvantagesanddisadvantagesof gravity flow sedimentary numerical simulation software
圖6超臨界流體結構 Π(Πa,Πb) 與亞臨界流體結構 (c,d) (據文獻[68]修改)Fig.6 Fluid structures: (a,b) supercritical structure;(c,d) subcritical structure (modified from reference [68])

在濁流的沉積過程中,開爾文一亥姆霍茲界面的不穩定性引起了流速大小和泥沙濃度的三維波動,進而調節了沉積物的分配。

2.3.3海底扇發育模式及形態動力學研究

海底扇的形態很大程度上取決于在其表面移動的水道動力學。Wahabetal.通過數值模擬歸納了密度弗勞德數 (FrD) 和勞斯數 (p) 控制下的海底扇3種發育模式。類似于剛果現代扎伊爾扇體系148(圖8a),亞臨界海底扇 (FrDlt;1,plt;0.055 以內部不對稱的分支水道為特征,該模式中砂質沉積物主要富集在水道內部,粉砂一泥質沉積物發育在堤岸、朵體和外扇部位(圖8b,c);墨西哥灣第四紀東部斷陷盆地IV號海底扇屬臨界海底扇 (FrD=1,plt;0.101 模式(圖8d),該模式內部以自生的低彎度水道為特征,水道兩側發育明顯的堤岸沉積,沉積物以過路作用為主,砂質沉積物發育在水道、朵體和遠端堤岸,粉砂及泥質沉積物主要發育在遠端扇(圖8e,f;超臨界海底扇(FrD=1.17,p=0.22) 內部發育單一的自生低彎度主水道。流體厚度的增加和湍流動能的損失導致沉積物以旋回坎的形式在河道內部向上游遷移。水道內部的高剪切應力抑制細粒沉積物沉降,海底扇以砂質沉積物為主,整體呈長條狀,類似于現代斯瓦米什海底扇(圖 8g~i)[149]

3 討論與展望

(1)沉積模擬的局限性。沉積物理模擬基于相似性原理,需要滿足幾何相似、運動相似和動力相似原則。實驗模型通常按一定比例進行縮放,但某些參數(顆粒粒度、深海高壓等)難以完全模擬現實世界條件。重力流的運動和動力相似一般通過弗勞德(a,b)大褶皺小濁流沉積模式與小褶皺大濁流沉積模式(據文獻[130]修改); (c~e) 正斷層地貌下濁流演化過程、主要沉積區域及愛爾蘭西部裂谷盆地早白堊世海底斷裂帶均方根屬性圖(據文獻[65]修改)

圖7復雜地貌下重力流沉積過程及分布特征Fig.7Sedimentatary process and gravity-flow deposition in complex landforms

數、雷諾數和希爾茲數等無量綱參數來約束。目前實驗中僅能保持單一參數(弗勞德數或希爾茲數)與真實值接近,而雷諾數高于紊流界限值即可。此外,重力流的自加速、卷吸等特性需要一定的時間和空間累積才能夠體現出來。數值模擬雖能實現與真實模型一致的時空尺度,但由于納維一斯托克斯公式的復雜性,計算精度和運算時長往往成反比,一個高精度模型計算時長高達上百萬核時[68]。同時,目前的重力流數值模擬對高濃度顆粒運動以及濁流的底床侵蝕作用模擬效果也不盡如人意[68]

(2)多學科交互。目前重力流研究正邁向定量化的重要階段,除了傳統的野外露頭、地下資料、海底監測,沉積物理模擬和數值模擬已成為重力流定量研究的重要手段。沉積物理模擬能夠有效刻畫重力流沉積過程和動力學特征,同時要求研究者兼具地質學和流體動力學知識背景,以便分析流體水動力現象并總結地質規律。盡管當前的重力流數值模擬軟件已相對成熟,但仍需用戶具備一定的編程能力,以根據地質背景開發新功能。因此,未來重力流沉積模擬需要地質學、水力學和計算機科學等多學科研究者加強合作,地質資料和過程模擬相結合,推動沉積學理論的發展。

(3)深水油氣開發。深水重力流沉積形成了廣泛分布的重力流砂巖,并蘊含著豐富的油氣資源。傳統的沉積地質研究通過露頭、巖心和地震等靜態資料對重力流形成機制、沉積特征和發育模式等方面有了宏觀的理解,但在定量研究重力流沉積過程和流體轉化方面尚顯不足。流體搬運過程的差異將直接導致沉積充填樣式、砂體展布及疊置樣式等沉積結構的不同。借助沉積模擬的手段可以加深重力流沉積過程和分布規律的理解,預測有利沉積體的分布規模和空間組合關系,為深水油氣勘探提供理論支持。

(4)海洋地質災害。海底滑坡是海底沉積物受多種誘發因素發生大范圍移動的地質現象[150],其發展演化過程包括滑動、滑塌、碎屑流、濁流四個階段[151]。隨著世界海洋能源開發不斷向深海推進,以海底滑坡為代表的海洋地質災害正對水下基礎設施產生重大威脅。自前關于海底滑坡的相關研究主要集中在海底滑坡形成機制、演化過程和對水下設施沖擊評估3個方面。借助沉積物理模擬手段,可以控制初始邊界條件,開展不同觸發機制條件下的海底滑坡模擬實驗,制定斜坡失穩評價標準;從海底滑坡發展規律人手,探究不同地形作用下滑坡沖出距離、堆積寬度、堆積厚度等,建立海底滑坡運動演化模型;最后通過數值模擬開展海底滑坡沖擊水下管線實驗,建立滑坡沖擊力預測公式,評估滑坡破壞性。

圖8基于形態動力學的海底扇發育模式(據文獻[69]修改) (a~c) 亞臨界海底扇沉積模式;(d\~f臨界海底扇沉積模式; 超臨界海底扇沉積模式 Fig.8 Model of submarine fan development based on morphological dynamics (modified from reference [69])

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Abstract:[Significance]Deep-water gravityflowdepositsare,in efect,records of extreme climatic events and tectonic activities (e.g.paleoseismic events).Accumulations of these sediments significantly affct thenumber and extent of worldwide reserves ofoiland gasresources.The event-driven nature of the deep-water gravity flow process,together with the unique nature of each deposition site,presents a significant challenge to direct observation in the field.At present,simulationof thedynamicsanddistributionpatterns ofdeep-water gravityflowdeposits is the primary approach.[Progress] This study reviews the advances in both physicaland numerical simulation of the processes and paternsof deep-water gravityflow deposits.Itbegins with asummaryof the principles and progress inmonitoring technology and laboratoryconstruction of physical simulation models,then examines the factors influencing such experiments:material composition and content,flow stateand energy diferences in the dynamics of the fluid flow. Analysis of the formation,transportation and depositional processesof deep-water gravity flow provides insights nto the complex dynamics involved,in terms both of its behavior aloneand when influenced byexternal factors (e.g., contour currnts).The studyalso reviews advances in the simulation of sedimentaryprocesses influenced bythe structureof the fluid,taking account of hydrodynamic parameters and complex topography.Numerical simulation is also crucial tounderstandingdeep-water gravityflow.This study providesacomprehensive review ofthe historicaldevelopment of numerical simulation techniques and presently available numerical simulation platforms.[Conclusions and Prospects]The limitedabilityof physical models to simulatethe intricate dynamicsand complex interactions between sediment particles and fluidflow in deep-water gravity flowdepositsare further discussed.The spatiotemporal scaleofalaboratorysetting hinders theabilitytoreproduce thebehaviorof deep-water gravityflowthat exists inrealworld conditions,and it isunlikelythat hydrodynamic parameters(variation in water velocity,sedimentconcentration etc.)are accurately predicted byphysical models.Numerical simulation ofers a promising alternative for studying deep-water gravityflowdeposits dueto the mathematicalabilitytowork atascaleconsistent with real-worldconditions.However,although computational fluid dynamics simulations provide valuable information about various depositional mechanisms that occur in deep-water environments,they have limited accuracy when applied to certain phenomena.In particular,the accurate capture of the behaviorof high particle concentrations in turbidity currnts and predictionof the amount of erosion theycause remain significant challenges due to the uncertainties assciated with factorssuch as grain size distribution and bedcomposition.Interdisciplinary colaboration is crucial in confronting these challenges and advancing the understanding of deep-water gravity flow sedimentation.Deper insights into the underlying mechanismsat playduring these processes willbest beobtainedifkey results from physical model simulationare integrated with outcomes from numerical simulation.This approach presents novel guidance for exploring oil and gas reserves in deep-water environments and preventing geological disasters.

Key words:deep-water gravityflow;turbidity current;physical simulation;numerical simulation;research progress

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