Heat flow and thermal evolution of a passive continental margin from shelf to slope – A case study on the Pearl River Mouth Basin, northern South China Sea

Heat flow and thermal evolution of a passive continental margin from shelf to slope – A case study on the Pearl River Mouth Basin, northern South China Sea

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Journal of Asian Earth Sciences xxx (xxxx) xxx–xxx

Contents lists available at ScienceDirect

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Heat flow and thermal evolution of a passive continental margin from shelf to slope – A case study on the Pearl River Mouth Basin, northern South China Sea ⁎



Yajun Lia,b, Zhenglong Jianga, , Shu Jiangc, , Hao Liua, Baogang Wangd a

School of Marine Sciences, China University of Geosciences, Beijing 100083, China School of Energy Resources, China University of Geosciences, Beijing 100083, China c Energy and Geoscience Institute, University of Utah, Salt Lake City, UT 84108, USA d Petroleum Industry Press, Beijing 100011, China b

A R T I C L E I N F O

A B S T R A C T

Keywords: Heat flow Thermal evolution Passive margin South China Sea Seafloor spreading Deepwater

The Pearl River Mouth Basin (PRMB), the largest basin in the northern continental margin of the South China Sea (SCS), has been one of the key areas to characterize geothermal field and thermal evolution of a passive continental margin. The thermal history of the Pearl River Mouth Basin is related to the seafloor spreading of the SCS in the late Early Oligocene. Heat flow measurements show that the PRMB is characterized by a high background heat flow with average heat flow of 71.8 ± 13.6 mW/m2. The present-day heat flow of the northern SCS increases from the northern shelf with the thick crust to the southern slope with the thinned crust. This study employs forward and inverse modeling to simulate the rift and post-rift processes exampled by four wells at different structural settings. Two thermal evolution models of the PRMB are established for continental shelf and continental slope. In the continental shelf, heat flow increased rapidly twice during the syn-rift stage, and then followed by continuous thermal subsidence with heat flow value decreased during the post-rift stage. While the heat flow in the slope continuously increased due to lithospheric thinning, mantle upwelling and resulting multiepisode seafloor spreading in SCS during the Neogene post-rift stage, which is different from the previously proposed decreasing heat model for the slope during the post-rift. Heat flow gradually reduced after the cessation of the sea floor spreading (10 Ma). The local multi-staged magmatic activities mainly contribute to the high level of maturity in the Liwan Sag located in the lower slope.

1. Introduction As there is limited amount of hydrocarbon left to produce in existing reserves, the hydrocarbon industry is now pursuing to explore frontier areas. The major unexplored area is the ocean. Explorations have been focused in the deepwater to ultra-deepwater passive margins, especially base of the slope or the continent-ocean boundary (COB) area (White et al., 2003). There are two models of continental margins. One is “hot” margin with upwelling mantle plume during the lithospheric thinning, e.g., the North Atlantic Ocean on the either side of the Iceland Plume (White and McKenzie, 1989; Nottvedt et al., 2000; Holbrook et al., 2001). These “hot” margins are characterized by kilometer-thick seaward-dipping near-seabed lava flows and large magnesium-rich igneous rocks with velocities of 7.2–7.6 km/s at the base of the thinning crust. The high-velocity magma was generated by large-scale decompression melting of asthenosphere during continental break-up. The other one is



“cold” magma-poor margin, e.g., west of the Iberian Peninsula (Louden et al., 1997; Fernàmdez et al., 1998; Louden and Chian, 1999; Whitmarsh et al., 2001; Minshull, 2002; Welford et al., 2010). The “cold” margin is characterized by tilted fault blocks, magma-poor, and abnormal velocity structure that is different from both the stretched continental crust and the oceanic crust. Several tens of kilometers wide high-velocity structure were found in “cold” margin, which may be caused by serpentinization of mantle rocks as a result of contact with sea water during continental break-up (Funck et al., 2003; Hopper et al., 2004; Leroy et al., 2012; Sutra et al., 2013). As one of the largest marginal sea in the west Pacific Ocean, the northern continental margin of the South China Sea (NMSCS) fits neither of these two models, which is kind of similar to a magma-poor margin but with volcanic rocks in the thick upper/middle crust (Lüdmann and Wong, 1999; Lüdmann et al., 2001; Clift and Lin, 2001a, 2001b; Yan et al., 2001; Wang et al., 2006; Galushkin, 2015; Kroeger et al., 2015). Thus the NMSCS is likely

Corresponding authors. E-mail addresses: jia[email protected] (Z. Jiang), [email protected] (S. Jiang).

https://doi.org/10.1016/j.jseaes.2017.12.011 Received 28 March 2017; Received in revised form 7 December 2017; Accepted 7 December 2017 1367-9120/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Li, Y., Journal of Asian Earth Sciences (2017), https://doi.org/10.1016/j.jseaes.2017.12.011

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to represent an intermediary model of “warm” margin. A series of Meso-Cenozoic sedimentary basins have been developed in the NMSCS, which contained abundant petroleum resources in the deepwater area. As the largest basin in the NMSCS, the Pearl River Mouth Basin (PRMB) has drawn broad attention for its thermal field and thermal evolution. Comparing to other China offshore basins in the west Pacific e.g. East China Sea basin and South Yellow Sea Basin, the PRMB is characterized as a “hot” basin due to its much higher heat flow at present (Yang et al., 2004). These results contradict previous study (McKenzie, 1978) suggesting that the thermal state of passive continental margin basin is relatively “cold” due to the cooling of the lithosphere. Moreover, many researches indicate that high heat flow exists in the COT of passive continental margin (Parsons and Sclater, 1977; Stein and Stein, 1992; Nyblade, 1997; Lucazeau et al., 2004, 2008, 2009; Goutorbe et al., 2007, 2008a, 2008b). Hence, reconstruction of thermal history is significant to understand the maturity of source rocks and the distribution of petroleum resources in the PRMB. Thermal modeling was used to understand the high heat flow in the PRMB (Guo and He, 2007; Zhang, 2009; Shan et al., 2009), its results show that paleo-heat flow value peaked at the Eocene rift stage (49.0–33.9 Ma), and later slowly decreased since 23 Ma. Present high thermal state has been suggested to be caused by the last tectonic activity at ∼10–5 Ma. Most of the existing researches were conducted based on the limited wells located in shallow water on the continental shelf (Shi et al., 2003), which represents the thermal evolution of rift stage. Although the present thermal field of the PRMB can be accounted for multiple episodes of stretching during the stage of rifting, the lithospheric thinning and deeper upwelling during the post-rift stage have been ignored in previous studies. This paper aims to reveal the thermal evolution model of the PRMB. Four wells, located in the shelf, shelf break, upper slope, and lower slope, respectively, are selected to analyze the heat flow and thermal history from shelf to slope areas with different burial history and their corresponding thermotectonic evolution models. On the basis of the strata compaction correction of different rocks, the study area is modeled forwardly based on the results of structural-thermal modeling that verified by measured vitrinite reflectance (Ro) data. The BasinMod 1-D software is used to reconstruct the burial history and thermal history of Cenozoic sedimentary stratum in different tectonic position.

2. Geological setting The PRMB is located in the NMSCS (Fig. 1a), which consists of four depression zones (the Zhu-I Depression, the Zhu-II Depression, the ZhuIII Depression and Chaoshan Depression) separated by three uplift zones (the North Uplift Zone, the Central Uplift Zone, and the Southern Uplift Zone). The Zhu-I Depression has a typical double-layer geologic structure of rift overlain by sag (Fig. 2 profile AA′), which is controlled by a series of major faults and characterized by half grabens or strongly asymmetric grabens (Sun et al., 2009). The Baiyun Sag (BYS) of the Zhu-II Depression is located by the shelf break, with a maximum Neogene-Paleogene sedimentary thickness of 12 km. The BYS is characterized by composite graben controlled by several boundary faults with 3––4 km of throw (Fig. 2 profile CC′). The Liwan Sag (LWS), neighboring the BYS in the north, is an ultra-deepwater sag with an approximate area of 3500 km2. Due to its location at the weak COB transfer zone, the LWS has the characteristic of rift-depression without typical basin-controlling faults. The geological evolution of the PRMB was driven by the plate tectonic interactions between the Philippine Sea plate, the Eurasian plate and the Indo-Australian plate, and was influenced by seafloor spreading of the South China Sea (SCS) in the late Early Oligocene (Briais et al., 1993; Taylor and Hayes, 1983a, 1983b; Gao et al., 2015). The PRMB experienced Cretaceous pre-rift stage, Paleogene rift stage, Early Neogene (Early to Middle Miocene) post-rift stage and Late Miocene-Quaternary Neotectonic stage. A series of grabens or rifts were formed in the brittle upper crust and thick organic-rich lacustrine source rocks developed during the Paleogene rift stage (Jiang et al., 2015; Li et al., 2016). Magmatism is weak and characterized by a limited magma intrusions during the rift stage. Local magmatic activities were discovered in the limited area of a few kilometers (Yan et al., 2006a, 2006b; Zhou et al., 2012, Sun and Zhou, 2013), which reshaped the present structural framework of the LWS at ∼32 Ma (Fig. 2 profile BB′). Seafloor spreading of the SCS began at a late period of rift stage (∼30.0 Ma), and the PRMB then experienced abnormal subsidence during the post-rift stage. Volcanism along previous faults are more active after cessation of seafloor spreading (∼15.5 Ma). Under the influence of NWW movement of the Philippine Sea Plate and SSE/SE SCS subduction at the Manila trench (Berry and Grady, 1981; Andrew et al., 1992; Northrup et al., 1995; Charlton, 2000; Lüdmann et al., 2001; Yan et al., 2006a, 2006b), Dongsha movement (9.8–5.5 Ma) resulted in the massive volcanic rocks formed along the lower slope of the NMSCS crust during the

Fig. 1. Study area and its geologic setting (a) and lithostratigraphic sequence (b) of the Pearl River Mouth Basin in the Northern Margin of South China Sea. Seismic lines and representative wells covering shelf and slope settings are shown on the base map. (E-N: Paleocene-Neocene; Q: Quaternary). (Geologic setting modified from Pang et al., 2007 and lithostratigraphic sequence modified from Huang et al., 2005).

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Fig. 2. Interpreted profiles on the northern continental margin of the South China sea (AA′ – Zhu-I Depression; BB′ – Liwan Sag; CC′ – Baiyun Sag). See Fig. 1 for the locations of profiles and the formation tops and ages for seismic reflections Tg to T1.

(BHT) data from drilling wells located in the shallow water with a depth of less than 300 m. According to existed researches (He et al., 2001; Yuan, 2007; Yuan et al., 2009; Li et al., 2010; Tang et al., 2014, 2016), the PRMB is a typical “hot” basin. There existed a linear relationship between temperature and depth (Fig. 4). The thermal gradient of the PRMB ranges from 24.7 °C/km to 60.8 °C/km, with an average value of 37.9 ± 7.4 °C/km. The geothermal gradient value of the shallow area in the PRMB is higher than that of the East China Sea Shelf (30.0 °C/km). For instance, the current geothermal gradient of the Huizhou Sag ranges from 30.0 °C/km to 36.0 °C/km and increases from north to south. In the deepwater area, the geothermal gradient (34.0–35.6 °C/km) is relatively low in the Panyu uplift and much higher (48.0–52.0 °C/km) in the BYS and adjacent areas. The geothermal gradient of ODP1148 located near the base of the slope increases to 83.0 °C/km (Wang et al., 2000). The overall geothermal pattern in the PRMB is that geothermal gradient gradually increases from shelf in the north to slope in the south (Fig. 2 profile CC′).

Neotectonic stage, which covered dozens of kilometers (Lüdmann and Wong, 1999; Lüdmann et al., 2001; Yan et al., 2006a, 2006b). From Paleocene to Oligocene, the Paleogene rift system includes the Paleocene Shenhu Formation (Fm), Lower Eocene Wenchang Fm, Upper Eocene Enping Fm, and Oligocene Zhuhai Fm (Fig. 1b). The Wenchang Fm consists of fluvial sandstone, shoreline-shallow lacustrine silty mudstone and deep lacustrine mudstone. The Enping Formation mainly comprises of fluvial sand-mudstone and lacustrine mudstone. The Zhuhai Formation is composed of littoral-neritic marine sand-mudstone. The Miocene formations of Zhujiang and Hanjiang were deposited during post-rift stage. The post-rift system consists mainly of littoral sand-mudstones, neritic mudstone, and marine mudstone. The Miocene Yuehai Fm, Pliocene Wanshan Fm, and Quaternary Fm were deposited in a marine environment during the Neotectonic phase. 3. Present thermal field 3.1. Geothermal gradient

3.2. Thermal conductivity

More geothermal data in the PRMB and nearby areas are available because of the Marine geological survey and oil and gas exploration. These data have been collected from survey and industry wells, IODP and deep-water heat flow probe (Fig. 3). Most bottom-hole temperature

The thermal conductivity of rock is dependent on temperature and pressure (Clark, 1966; Clauser and Huenges, 1995). Thus, the 3

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Fig. 3. Sources of Heat flow measurements in the Pearl River Mouth Basin. (Magnetic anomaly modified from Pang et al., 2007).

Table 1 Measured thermodynamic parameters of the Zhu-I Depression. Well

Depth (m)

Lithology

Geothermal gradient (°C/ km)

Conductivity (W/(m·K))

Heat flow (mW/ m2)

LF-1

2572 2577 2910 2914

Sandstone Mudstone Siltstone Mudstone

36.4

1.79 2.73 2.44 1.94

65.16 99.37 88.82 70.62

LF-2

1924 1875

Gritstone Sandy limestone Granular limestone

40.4

0.59 3.40

23.84 137.36

2.48

100.19

1832 HZ-1

4588–4604

Daciteporphyrite

33.3

2.65

88.25

HZ-2

3096 3109

Limestone Sandy limestone

39.6

3.19 3.15

126.32 124.74

HZ-3

3201 3077

Sandstone Silt mudstone Fine sandstone

31.9

2.68 1.88

85.49 59.97

1.44

45.94

Gritstone

29.8

0.39

11.62

2692 Fig. 4. The relationship between the BTH (bottom-hole temperature) and depth of the Pearl River Mouth Basin (modified from Shan, 2011).

XJ-1

laboratory measurements need to be corrected for temperature and pressure conditions below the sea floor using the correction equation by Hyndman et al. (1974):

Z + ρ·Z T (Z )−Tlab ⎞ + λP, T (Z ) = λlab ·⎛1 + w 1829·100 4·100 ⎠ ⎝

2333

(Table 1), which are much higher than the average heat flow in the rift basin (c. 50–65 mW/m2, according to Allen and Allen, 1990; Röhm et al., 2000). As the conductivity data of each stratum is not always accessible and heat flow calculated for one lithology does not work for the subsurface consisting of multiple lithologies, rock mixing principle (Beardsmore and Cull, 2001) is therefore adopted to estimate the conductivity of the mixed lithology. The thermal conductivity and heat flow are then calculated by using the equations below:

(1)

where λP,T(Z) is the in-situ thermal conductivity at depth Z (W/(m·K)), λlab is the measured thermal conductivity in the laboratory (W/(m·K)), Zw is water depth (m), ρ is mean sediment density (g/cm3), T(Z) is the in-situ temperature (°C), and Tlab is mean measurement temperature in the laboratory (°C). According to the previously measured thermal conductivity data (Rao and Li, 1991; Yuan et al., 2009; Shan, 2011), some heat flow values calculated from limestone are greater than 100 mW/m2

λMIX =

∑ di ∑

di λi

(2)

where λMIX is the average conductivity of the sediment column (W/ m·°C), di is the thickness of each lithology (m); λi is the conductivity of each lithology (W/m·°C). 4

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Fig. 5. Simulated Ro results in well HZ-1, showing the simulated Ro in the red line values are consistently higher than measured values indicated by blue triangle. The locations of well HZ-1 is shown in Fig. 1. (Formation names: EP = the Enping Fm; ZH = the Zhuhai Fm; ZJ = the Zhujiang Fm; HJ = the Hanjiang Fm; Yh = the Yuehai Fm; WS = the Wanshan Fm; Q = Quaternary.) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

(3)

Q= λMIX × (TB−T0)/ΔZ

conductivity data of different formation in the PRMB, which shows the average thermal conductivity of Paleogene, Miocene and PlioceneQuaternary are 2.65 W/(m·K), 2.30 W/(m·K) and 2.00 W/(m·K), respectively. For the same lithology, thermal conductivity increases with burial depth due to the compaction (Fig. 6). For example, the thermal conductivity of the Oligocene Zhuhai Fm sandstone is 2.31 ± 0.44 W/ (m·K), and the value of Eocene Enping Fm sandstone and Eocene Wenchang Fm sandstone increase to 2.72 ± 0.35 W/(m·K) and 3.32 ± 0.24 W/(m·K), respectively. The thermal conductivity of different rocks varies greatly. The average thermal conductivity value (2.75 ± 0.43 W/(m·K)) of basement rocks is higher than that of the other clastic rocks.

where Q is the heat flow (mW/m2), T0 is the temperature at the surface of the sediment column (°C). TB is the temperature at the base of the sediment column (°C) and ΔZ is the sedimentary thickness from the surface to the base of the stratigraphic column (m). When the calculated heat flow value (88.25 mW/m2) using the single measured thermal conductivity from well HZ-1 was used as input parameter for the thermal modeling, the simulated maturity (Ro%) values are consistently much higher than the measured Ro values (Fig. 5a). When the heat flow data calculated by the estimated thermal conductivity of well HZ-1 was inputted into the same geologic model again, the new ‘simulated’ Ro values fit the ‘measured’ Ro values reasonably well (Fig. 5b), which indicates the reliability of this method for heat flow calculation in the PRMB. Table 2 lists the thermal

3.3. Heat flow In order to understand the origin and evolution history of the SCS, a total of 635 calculated heat flow data, ranging from 8 to 192 mW/m2, have been collected from borehole and deepwater heat flow probe (Jessop et al.,1976; Watanable et al., 1977; Anderson et al., 1978; Taylor and Hayes, 1983a, 1983b; Ru and Pigott,1986; Nissen et al.,1995a, 1995b; Shyu et al., 1998; He et al., 2001; Shi et al., 2003). According to the Eqs. (2) and (3), the heat flow from more than 200 sites was calculated by the estimated conductivity of the mixed lithology in the PRMB. Most data concentrated in the Zhu-I, Zhu-III Depression and the Panyu low uplift, and relatively few data located in the deepwater area. The heat flow values (Table 3), ranging from 72 mW/m2 to 94 mW/m2, in the BYS are much higher than that in normal rift basin with heat flow values of 50–65 mW/m2 suggested by Allen and Allen (1990) and Röhm et al. (2000) (Fig. 7a). The heat flow increases from the shelf in the north to the COB in the south, this trend is opposite to that the Moho depth decreases from shelf to COB (Fig. 7b). Our observation is consistent with previous works suggesting the PRMB as a typical “hot basin” with average heat flow of 71.8 ± 13.6 mW/m2, ranging from 24.2 mW/m2 to 121.0 mW/m2 (Kido et al., 2001; Chen et al., 2009; Tang et al., 2014, 2016).

Table 2 Thermal conductivity data of different formaion in the Pearl River Mouth Basin (PRMB), revised from Shan (2011). Fm.a

Lithology

Depth (m)

Conductivity (W/ (m·K))

Mean value (W/ (m·K))

N1zj N1zj N1zj E3zh E3zh E3zh E3zh E3zh E2ep E2ep E2ep E2ep E2wc E2wc E1-2sh AnR AnR AnR AnR AnR

Sandstone Siltstone Limestone Sandstone Conglomerate Shale Mudstone Siltstone Sandstone Shale Mudstone Siltstone Sandstone Mudstone Diorite Limestone Sandstone Granodiorite Andesite Granite

1187.6–3764.2 1192.6–1253.1 1269.0–2108.8 1647.3–4381.0 2727.8–3990.8 4376.5–4507.1 2578.0–4502.4 2801.5–3313.1 2907.3–3911.0 3512.9–3514.5 2910.8–3909.2 2910.6–3510.4 3970.7–3984.3 3967.3–3985.4 4410.4–4417.1 3108.0–3250.1 2746.1–4284.8 3837.0–3850.4 2731.6–2733.0 3223.3–3224.8

1.98–3.60 1.90–2.02 1.01–2.94 1.54–3.14 2.05–2.89 2.02–3.10 1.79–3.07 2.47–2.85 1.97–3.38 1.47–4.43 2.08–3.19 2.15–2.81 2.83–3.66 2.31–3.84 2.33–2.98 2.76–3.16 2.28–3.69 3.37–3.56 2.54–2.55 3.20–3.46

2.70 2.02 2.09 2.31 2.48 2.51 2.45 2.63 2.72 2.84 2.62 2.35 2.32 3.18 2.60 3.01 3.07 3.47 2.54 3.30

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.33 0.10 0.48 0.44 0.22 0.32 0.35 0.14 0.35 1.22 0.30 0.24 0.24 0.46 0.20 0.18 0.52 0.10 0.00 0.11

a ZJ, ZH, EP, WC, SH and AnR represent Zhujiang, Zhuhai, Enping, Wenchang, Shenhu and Pre-Cenozoic Fm, respectively.

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Fig. 6. Thermal conductivity of the Paleogene sandstone and mudstone. (E3zh: the Oligocene Zhuhai Fm; E2ep: the Eocene Enping Fm; E2wc: the Eocene Wenchang Fm.)

4. Thermal history modelling

2011), the average heat generation values were calculated from 97 samples. The average heat generation of sandstone, mudstone, limestone and bed rock are 0.99 μW/m3, 1.74 μW/m3, 0.61 μW/m3, 1.99 μW/m3, respectively. As heat generation data of each stratum is not always accessible, equation (5) was used to calculate the heat generation of mixed lithology.

4.1. Method In this study, four representative wells from different structure locations covering shelf to slope are selected (Fig. 1a) to simulate the rift and post-rift process via forward and inverse modeling. The convective or non-vertical heat transport heat sources in the study area are not considered in this paper. The burial history reconstruction is based on geological information, tectono-stratigraphic history of the region, drilling and seismic data. A mathematical model of backstripping method was used to reconstruct burial history. According to the residual thicknesses of each stratum and porosity-depth relationships, the thickness of each stratum and paleo-burial depth at different geological time can be calculated. Hence, the major process is the modelling of the compaction of sediments. Exponential compaction correlation Method (Sclater and Christie, 1980) was selected to calculate the porosity at the different depths.

Φ = Φ0 exp−kZ

A=

(4)

0.2Φ3 , S02 (1 − Φ)2 20Φ5 S02 (1 − Φ)2

Φ ⩾ 10%

, Φ < 10%

(6)

where A is average heat generation of mix lithology (μW/m3), Ai is the heat generation of each lithology (μW/m3), Ci is the proportion of each lithology in a stratum (%). The heat generation of the upper crust, lower crust, and upper mantle is 2.56 μW/m3, 0.3 μW/m3, 0 μW/m3, respectively (Yang et al., 2014). Rock mixing principle (Beardsmore and Cull, 2001) is adopted to estimate the average conductivity of sedimentary formations. Burial depth, formation temperature and thermophysical attributes of rocks vary with depth and time during the process of tectonic evolution. These thermodynamical data obtained via forward modelling are used to calculate the paleo-heat flow. The calculated paleo-heat flow values are then inputted into the BasinMod 1-D modelling software to simulate the thermal history indicated by maturity. One-dimensional transient heat flow model is used to constrain the maturity modelling. Thermal history is simulated by using the LLNL EASY% Ro model (Burnham and Sweeney, 1988; Sweeney and Burnham, 1990). The measured Ro data are used to constrain the simulation results of thermal evolution. When the ‘simulated’ Ro values match the ‘measured’ Ro values well, a reasonable geologic model is then generated.

where Φ is porosity (%), Φ0 is Initial porosity (%), k is compaction factor (m−1), Z is depth (m). The pore pressure evolution plays an important role in the compaction calculations. The modified Kozeny-Carman permeability equation (Ungerer, et al., 1990) was employed in this paper to reconstruct the burial history of strata for different structure locations of the PRMB. Modified Kozeny-Carman equation is:

⎧K = ⎪ ⎨K = ⎪ ⎩

∑ Ai Ci

4.2. Modeling parameters

(5)

where K is permeability (m2), Φ is porosity (%), S0 is the specific surface area of the rock. Radiogenic heat generation was taken into account when paleo-heat flow was calculated during rifting and post-rift subsidence process. According to existed heat generation data (Rao and Li, 1991; Shan,

To provide a more complete database for addressing the thermal regime and related rifting process, we firstly studied the present-day temperature and vitrinite reflectance data. The thermal history was then reconstructed based on the tectonic subsidence and heat flow history.

Table 3 Heat flow data of the Baiyun Sag (BYS). Well

Geothermal gradient (°C/ km)

Heat conductivity (W/mK)

Heat flow (mW/ m2)

Well

Geothermal gradient (°C/ km)

Heat conductivity (W/mK)

Heat flow (mW/ m2)

PY-1 PY-3 PY-5 PY-7 PY-9 BY-1 BY-3

31.2 33.4 40.8 31.3 38.5 35.6 40.6

2.09 2.04 1.82 2.08 1.98 2.10 2.10

65.21 68.19 74.12 65.00 76.24 74.73 85.42

PY-2 PY-4 PY-6 PY-8 PY-10 BY-2 LW-1

32.6 34.7 38.0 38.0 38.0 48.0 56.4

2.07 2.12 2.03 1.83 1.99 1.75 1.64

67.37 73.60 77.27 69.31 75.41 84.00 92.57

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Fig. 7. The calculated present-day heat flow based on measurements (a) and the Moho depth (b) in the BYS (COB: continent-ocean boundary).

PRMB underwent five tectonic movements (at ∼49.0 Ma, ∼38.0 Ma, ∼33.9 Ma, ∼23.0 Ma, ∼10.0 Ma, respectively) since Paleocene, which formed five unconformities. Erosion event occurred during each tectonic movement (Fig. 1b). The most significant erosion events are related to the SCS opening process after the deposition of Eocene Enping Fm. The eroded thickness can be estimated by extrapolation method of stratum trend and numerical simulation method (Guo et al., 1998). Because of the limited number of measured Ro, erosion thickness is hard to calculate. As truncations usually occurs under the sequence boundary in the structural highs, the trend of seismic reflection configuration on the seismic section can be used to estimate the thickness of eroded sediments (Fig. 8a). Simulation curves of measured Ro and burial depth were also used for extrapolation to estimate the thickness of eroded sediments (Fig. 8b). Erosion of the Enping Fm in well BY-1 was estimated at 250 m.

Table 4 Age, tectonic events, and lithology of formations of the Baiyun Sag (BYS). Deposition age From/Ma

To/Ma

2.60

0

5.30 10.0

2.60 5.30

16.0 23.0

10.0 16.0

33.9 38.0

23.0 33.9

49.0

38.0

Teconic movement (Age/ Ma)

Dongsha (10.0 Ma) Baiyun (23.0 Ma) Nanhai (33.9 Ma) Zhu-Qiong II (38.0 Ma) Zhu-Qiong I (49.0 Ma)

Formation

Lithology

Quaternary

Nonconsolidated sand and clay Neritic sand-mudstone Marine mudstone

Wanshan Yuehai Hanjiang Zhujiang Zhuhai Enping Wenchang

Neritic mudstone Littoral-neritic sandmudstone Littoral sand-mudstones Fluvial-lacustrine coalbearing series Medium-deep lacustrine sand-mudstone

4.2.3. Palaeoenvironment and palaeobathymetry Palaeoenvironment and palaeobathymetry have been determined on the basis of lithology and palaeontological data. The palaeoenvironment inferred from the palaeontological data of well BY-2 indicates the evolution of the north slope of the SCS. The abundance, diversity, variability of foraminifer and percentage of planktonic foraminifer of well BY-2 have been analyzed. The changes of the palaeobathymetry and depositional environment at the site of well BY-2 are inferred from the biostratigraphic data (Table 5). During the last sedimentary period of the Late Oligocene Zhuhai Fm, the BYS was in a rift to thermal subsidence stage, and then the palaeobathymetry increased gradually. The BYS was in the inner

4.2.1. Formation tops and lithologies The formation tops and lithologies are obtained from drilling results and seismic data. From bottom to top, the PRMB develops the formations of Shenhu, Wenchang, Enping, Zhuhai, Zhujiang, Hanjiang, Yuehai, Wanshan, and the Quaternary (Fig. 1b). Detailed data are shown in Table 4.

4.2.2. Erosion events Several erosion events have been recognized in the PRMB. The

Fig. 8. Thickness of eroded Enping Formation in well BY-2. (The location of well is shown in Fig. 1a. The sequence boundaries are shown in Fig. 1b.)

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Table 5 Palaeobathymetry of well BY-2 inferred from foraminifer data. Age

Forminiferal zonation

Fm

Abundance

Diversity

Variability of planktonic foraminifer

Variability of benthonic foraminifer

Percentage of planktonic foraminifer (%)

Palaeoenvironment

Palaeobathymetry (m)

The Middle Miocene

N14 N13

Hanjiang Fm

< 5000 ↘

21–35 ↘

Heterolepa spp.; Uvigerina spp.; Pullenia bullodies; Bulimina costata; Quinqueloculina bicarinata

66.7–90.0% mostly:70–80%

Abysmal sea – Continental slope

1000

N12 N11

1000–6000 ↗

24–40 ↘, ↗

Heterolepa spp.; Uvigerina spp.; Pullenia bullodies; Bulimina costata; Textularia spp.

25.0–75.9%

Continental slope

700

N10 N9

< 25,000 →

25–40 ↗

Globorotalia menardii; Orbulina universa; * Glboquadrina sacculifer; Globoquadrina dehiscens* Globorotalia menardii; Orbulina universa*; Globoquadrina sacculifer; Globoquadrina dehiscens Orbulina universa; Globoquadrina sacculifer; Globoquadrina dehiscens

5.6–63.5%

Continental slope

300 ? (Data are not credible because of gravity flow sediments.)

N8b2

< 25,000 ↘

AVE: 30 ↘

Quinqueloculina lamarckiana; Hete-rolepa spp.; Uvigerina spp.; Pullenia bullodies Bulimina costata; Ammonia sp.; Globocassidulina subglobosa Heterolepa spp.; Uvigerina spp.; Pullenia bullodies; Globocassidulina subglobosa; Bulimina costata; Cassidulina transulucens Textularia spp.; Bigenerina sp.; Quinqueloculina lamarckiana; Pyrgo sarsi; Heterolepa spp.*; Uvigerina spp.; Bulimina costata; Pullenia bullodies; Globocassidulina subglobosa Textularia spp.; Heterolepa spp.; Pullenia bullodies; Uvigerina spp.; Bigenerina sp. Quinqueloculina lamarckiana; Pullenia bullodies; Globocassidulina subglobosa; Heterolepa spp.

61.4–65.7%

Shelf break

61.4–94.1% Mostly: > 80%

Abysmal sea – Continental slope

1000

20.5–82.1% Mostly: > 50%

Continental slope – Shelf break – Outer shelf

700 500 200

0–60% Mostly: 0–33%

Outer shelf – Shelf break

150

0–61.1% Mostly: 0–10%

Inner shelf

< 50

Early Miocene

Oligocene

N8b1 N8a N7 N6 N5b

Upper part of the Zhujiang Fm

< 16,000 ↘

20–46 AVE:35 ↗, ↘

Globoquadrina dehiscens*

N5a N4 N3

Lower part of the Zhujiang Fm

< 35,000 ↗

< 34 ↗

Globoquadrina dehiscens

N2

Zhuhai Fm

Rare →

< 30 ↘

Rare →

<2 ↗

N1

↗: increase; ↘: decrease; →: essentially constant; AVE: average value.

continental shelf, and the palaeobathymetry is less than 50 m during the Late Oligocene. Existed researches show that palaeoenvironment of the IODP1148 site was the bathyal environment with palaeobathymetry of more than 1000 m during the Late Oligocene (Shao et al., 2004; Zhao, 2005). The palaeobathymetry of the BYS increased with fluctuations, the palaeoenvironment evolved into continental slope in the early period of Early Miocene. In the late period of Early Miocene, the palaeobathymetry was deeper than 1000 m, and the BYS was in the palaeoenvironment of the continental slope and bathyal settings. The environment of the BYS continued continental slope and bathyal settings during the mid-Miocene to present. The palaeobathymetry evolution of modeling wells is obtained by this method.

Table 6 Calculated heat flow values before rifting stage of four drilling wells. Well

HZ-1 BY-1 BY-2 LW-1

Lithospheric thickness (km) Initial

After stretching

120 120 120 120

90 81 72 70

Rifting β

1.33 1.48 1.67 1.71

Age of rift stage (Ma) Begin

End

49 49 49 49

33.9 33.9 33.9 33.9

Heat flow before stretching (mW/ m2)

51.9 52.7 54.4 59.2

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Fig. 9. Paleo-heat flow and thermal history of well HZ-1 located in shelf setting. The location of well HZ-1 is shown in Fig. 1. (a. Burial history; b. Simulated temperature modeling matches with the bottom hole temperature (BHT); c. Simulated Ro modeling matches with the measured Ro data; d. The evolution of bottom temperature; e. The evolution of paleo-heat flow.) Formation names: EP = the Enping Formation; ZH = the Zhuhai Formation; ZJ = the Zhujiang Formation; HJ = the Hanjiang Formation; YH = the Yuehai Formation; WS = the Wanshan Formation; and Q = Quaternary.

calculated by the finite rifting model (Jarvis and McKenzie, 1980). Basin Mod 1D calculates this process by follow thermal decay equation.

4.2.4. Thermophysical condition BHT, Ro data, and calculated paleo-heat flow at the base of the sediment column were used to calibrate thermal models. The BHT and Ro data were collected from boreholes and corrected according to Yuan et al. (2009). Present day geothermal gradient of each well was calculated from BHT individually. Present heat flow was calculated from the geothermal gradient and average conductivity of the sedimentary formation. The paleo-surface temperature data from the beginning of the Late Miocene (23 Ma) to the present for all locations are considered as the paleo-temperature at the seafloor. It is calculated by the correlation of water depth and temperature at seafloor. The empirical equation (Xue et al., 1991) is shown as the following: 100 < Z < 800, T0 (t ) = −8.7946 × ln Z + 62.958;

Z> 800, T0 (t ) = 2.0 ∼ 4.2



F(t ) =

kT1 ⎧ ⎫ · 1 + π ∑ nbn (−1)n + 1 × exp [−n2π 2 (t −Δt ) k / a2] ⎬ z ⎨ n = 1 ⎩ ⎭

(8)

where F(t) is the heat flow at surface at time t, t is the time of rifting, k is thermal conductivity, kT1 is the heat flow prior to rifting (based on z present day heat flow), bn is coefficient, a is the thickness of lithosphere. Requirements for calculation of rifting heat flow in Basin Mod are rifting Bata factor (β), thickness lithosphere, start and end age of rift stage. The Bata factor defines as

(7)

β=

where Z is the water depth (m) and T0(t) is the temperature at seafloor (°C) at time point t. For the surface temperature history before rifting stage (56–23 Ma) or the water depth is lower than 100 m, the surface temperature is taken from a module that is included with the BasinMod 1D software that calculates paleosurface temperature through time at chosen latitudes. Paleo-temperature at the base of the sediment column is obtained from forward modeling. According to the previous thermal history reconstruction of the Baiyun Sag (Tang et al., 2017), the reconstructed average paleo-heat flow was 54.9 mW/m2 at 49 Ma by multi-stage finite stretching method. In this paper, the heat flow values before rifting stage of four wells were

initial lithospheric thickness lithospheric thickness after stretching

(9)

The initial lithospheric thickness was set as 120 km, the lithospheric thickness after stretching of four well were referenced by existed research (Shi et al., 2017). In order to simplify the rifting process, the start and end age of rift stage were set as 49 Ma and 33.9 Ma, respectively. The calculated heat flow values before rifting stage of four wells were shown in Table 6. According the calculation results and previous research (Tang et al., 2017), the average background heat flow value was set as 55 mW/m2. The heat flow at the base of the sediment column during rifting and post-rift subsidence process is calculated by using the Eq. (3).

9

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Fig. 10. Paleo-heat flow and thermal history of well BY-1 located in shelf break setting. The location of well BY-1 is shown in Fig. 1. (a. Burial history; b. Simulated temperature modeling matches with the BHT; c. Simulated Ro modeling matches with the measured Ro data; d. The evolution of bottom temperature; e. The evolution of paleo-heat flow). Formation names: WC-1 = the lower part of the Wenchang Fm; WC-2 = the upper part of the Wenchang Fm; EP-1 = the lower part of the Enping Fm; EP-2 = the upper part of the Enping Fm; ZH = the Zhuhai Fm; ZJ-1 = the lower part of the Zhujiang Fm; ZJ-2 = the upper part of the Zhujiang Fm; HJ = the Hanjiang Fm; YH = the Yuehai Fm; WS = the Wanshan Fm; and Q = Quaternary.

the Eocene Enping Fm. The thickness of the Eocene Wenchang and Enping Fm are obtained from drilling well and seismic data, which were used to establish the geologic model for studying thermal history. Under the constraint of calculated heat flow from the geologic model (Fig. 10a), the simulated temperature and %Ro fit the BHT and measured Ro data well (Fig. 10b and c). The heat flow value (Fig. 10e) increased from 50.7 mW/m2 and reduced transiently during the early rifting stage (49.0–38.0 Ma). After that, the heat flow value began to rise during the late rifting stage (38.0–33.9 Ma) and reached the peak of approximately 74.8 ± 3.8 mW/m2. A reduction trend of heat flow was followed and decreased to 68.9 ± 3.7 mW/m2 at 10 Ma. In the Late Miocene-Pliocene-Quarternary Neoteconics stage, heat flow progressively increased to present high value (75.0 ± 2.1 mW/m2). It is shown from the simulated results (Fig. 10a) that the Eocene Wengchang Fm (WC-1, WC-2) is currently in a main gas generation stage (Ro > 1.3%). The Eocene Enping Fm (EP-1, EP-2) is still in the mid-late mature stage (Ro = 0.70–1.3%), and the Oligocene Zhuhai Fm is in middle mature stage (Ro = 1.0–0.70%). The bottom of the Miocene Hanjiang Fm and the Miocene Zhujiang Fm are in the early mature stage (Ro < 0.7%).

4.3. 1-D modeling results 4.3.1. Well HZ-1 The well HZ-1 with a total depth of 4418.9 m, located in the Zhu-I Depression on the continental shelf, has drilled into the Eocene Enping Fm. The drilling data were used to establish the geologic model for studying thermal history (Fig. 9a). The simulated temperature matches BHT reasonably well (Fig. 9b). Under the constraint of calculated heat flow, measured Ro values were used to calibrate the validity of maturity history (Fig. 9c). The calculated heat flow (Fig. 9e) increased from 51.0 to 68.0 ± 3.4 mW/m2 and then decreased temporarily during the early rifting stage (49.0–38.0 Ma). Heat flow increased to approximately 68.1 ± 5.4 mW/m2 at ∼33.9 Ma during the late rifting stage. After that, heat flow value gradually decreased to 67.8 ± 3.2 mW/m2 at ∼10 Ma. In the late Miocene, heat flow increased again and reached the peak of approximately 71.1 ± 2.3 mW/m2, and then dropped from its peak to 67.9 ± 1.7 mW/m2. It is shown from the simulated results (Fig. 9a) that the Eocene Enping Fm is currently in a middle mature stage (Ro = 0.70–1.0%), and the Oligocene Zhuhai, Miocene Zhujiang Fm are in the early mature stage (Ro < 1.0%).

4.3.3. Well BY-2 The well BY-2 is much deeper than well BY-1, which is located in the upper slope. The oldest layer is the Oligocene Zhuhai Fm with a total drilling depth of 3843 m. The thickness of the Eocene Enping and

4.3.2. Well BY-1 The well BY-1 with a total depth of 5094 m, located in the south of the Panyu low uplift and close to the shelf break area, has drilled into 10

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Fig. 11. Paleo-heat flow and thermal history of well BY-2 located in upper slope setting. The location of well BY-2 is shown in Fig. 1. (a. Burial history; b. Simulated temperature modeling matches with the BHT; c. Simulated Ro modeling matches with the measured Ro data; d. The evolution of bottom temperature; e. The evolution of paleo-heat flow.) Formation names: WC-1 = the lower part of the Wenchang Fm; WC-2 = the upper part of the Wenchang Fm; EP-1 = the lower part of the Enping Fm; EP-2 = the upper part of the Enping Fm; ZH = the Zhuhai Fm; ZJ-1 = the lower part of the Zhujiang Fm; ZJ-2 = the upper part of the Zhujiang Fm; HJ = the Hanjiang Fm; Q-YH = the Yuehai, Wanshan Fm and Quaternary.

Wengchang Fm are estimated from seismic data. A better fit between measured and calculated geothermal data (Fig. 11b and c) is obtained from geologic model (Fig. 11a). The evolution of heat flow (Fig. 11e) is much different from well BY-1 that is close to the shelf break. The heat flow value increased continuously from 54.4 to 68.8 ± 1.7 mW/m2 during the Eocene syn-rift stage. After 33.9 Ma, a slight increase trend was followed. Heat flow values increased rapidly during the post-rift stage and reached the peak of approximately 86.0 ± 2.3 mW/m2 at ∼5.3 Ma, and a slight decrease of heat flow was followed during the next 5 Ma. From the simulation results (Fig. 11a), the Eocene Wenchang and Enping Fm are currently in the late mature and main gas generation stage (Ro = 1.0–2.0%), while the Oligocene Zhuhai Fm is in the main mature stage (Ro = 0.70–1.30%). The Miocene Zhujiang and Hanjiang Fm are mostly in the early mature stage (0.5% < Ro < 0.75%).

LWS, local multi-staged magmatic activities (Dome-like uplifts or diapirs) are likely to have contributed to the present maturity degree of well LW-1 (Pang et al., 2007; Sun and Zhou, 2013; Zhou et al., 2012). When the additional heat by the volcanic intrusion (Fig. 10d) was inputted into the thermal modelling, the simulated %Ro was consistent overall with the measured values (Fig. 12c). Through parameter adjustment of geological model, the reasonably evolution of paleo-heat flow of well LW-1 is obtained. The paleo-heat flow evolution (Fig. 12e) of well LW-1 is similar to that of well BY-2, but the values are much higher. Heat flow did not decrease during the period from 33.9 Ma to 23.0 Ma, and then kept increase to 93.3 ± 3.4 mW/m2 at 10.0 Ma. A sharp increase of heat flow was followed and reached the peak of approximately 99.9 ± 3.4 mW/m2 at 2.6 Ma, and later decrease to present heat flow of 92.6 ± 3.1 mW/m2. The maturity simulation results (Fig. 12a) show that the Eocene Wenchang and Enping Fm are in the late mature and main gas generation stage (Ro = 1.0–2.0%), and the Oligocene Zhuhai, Miocene Zhujiang and Hanjiang Fm are in the middle mature stage (Ro = 0.7–1.0%).

4.3.4. Well LW-1 The well LW-1 with a total depth of 4185.4 m is located in the lower slope with a water depth of 2450 m. It has drilled into the Eocene Wenchang Fm. The drilling data are used to build up the geologic model. The calculated heat flow before rift stage of well LW-1 is 59.2 mW m2, which is much higher than other three wells. A better fit between simulated temperature and BHT (Fig. 12b) was obtained from geologic model (Fig. 12a). Under the constraint of calculated heat flow with high background value, the measured Ro values are used to calibrate the validity of maturity history. Unfortunately, no matter how the parameters were adjusted, the simulated %Ro was much lower than measured values (Fig. 12c). Considering the well area is close to the

5. Discussion 5.1. Present-day geothermal field The present-day geothermal field is related to the tectonic evolution process. A normal rift basin is characterized by lower present-day heat flow with symmetric distribution (Zeyen et al., 1997; Behrendt, 1999). Lithosphere is extended and thinned in a pure-shear model (McKenzie, 11

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Fig. 12. Paleo-heat flow and thermal history of well LW-1 located in lower slope. The location of well LW-1 is shown in Fig. 1. (a. Burial history; b. Simulated temperature modeling matches with the BHT; c. Simulated Ro modeling matches with the measured Ro data; d. The evolution of bottom temperature; e. The evolution of paleo-heat flow.) Formation names: WC = the Wenchang Fm; EP = the Enping Fm; ZH = the Zhuhai Fm; ZJ-1 = the lower part of the Zhujiang Fm; ZJ-2 = the upper part of the Zhujiang Fm; HJ = the Hanjiang Fm; QYH = the Yuehai, Wanshan Fm and Quaternary.

Fig. 13. Thermal evolution models for shelf and slope of the Pearl River Mouth Basin.

increases from shelf in the north to the base of the slope in the south. The Zhu-I Depression on the shelf, went through post-rift thermal decay due to re-establishment of thermal equilibrium in mantle lithosphere and asthenosphere after rift stage. As lithosphere getting thinner and thinner in continental slope, the BYS and the LWS entered the stage of

1978) or simple-shear model (Wernicke, 1985) during the rift stage. Isostatic compensation causes upwelling of asthenosphere, which results in a hotter lithosphere and the increase of heat flow. After that, the temperature perturbation gradually decays because of isostatic compensation and cooling of hot lithosphere. Present heat flow in the PRMB 12

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Fig. 14. Evolution process of deep crust in the Baiyun Sag (crust model modified from Morley and Westaway, 2006).

in the lithospheric thinning and the rise of the Moho (Fig. 14c). As a result, heat flow value in the slope to COB area increased dramatically, reaching a peak (at ∼10.0 Ma) after spreading of the SCS ceased. Dongsha movement (9.8–4.4 Ma) re-activated the previous faults and resulted in volcanism along these faults in the Dongsha Uplift, the Chaoshan Depression, the Zhu-I Depression and the Panyu Low-uplift. The dramatic increase of heat flow during the Neotectonic stage in well BY-1, which located beside the Panyu Low-uplift close to two previous faults, is likely affected by this movement (Fig. 10e). The local multistaged magmatic activities (Fig. 1a) also contribute to the thermal complexities of the LWS (Zhou et al., 2012). Dome-like magma diapirs rose up around 36–32 Ma to heat its ambient rocks and elevated the maturity of source rocks in the LWS (Fig. 12a). It is worth mentioning that it needs 80 m.y. for the continental lithosphere to regain thermal equilibrium (McKenzie, 1978). The NMSCS did not have enough time to cool down. This is probably another reason for high heat flow in the PRMB.

continued warming due to the rise of the Moho and upward movement of hot magma during the initial drifting stages. When ocean ridge migrated away from the continental margin, the lithosphere began to cool down in the continental slope, which happened later than that in the continental shelf. That is why present-day heat flow values in the southern PRMB are much higher. 5.2. Thermal evolution model Based on 1-D modelling results, the paleo-heat flow evolution varies from north to south of the passive continental margin. Two new thermal evolution models for the continental shelf and continental slope of the PRMB are established (Fig. 13). Continental shelf model: Because of two-phase extension, heat flow increased rapidly twice during the syn-rift stage. Continuous thermal subsidence was followed because of lithosphere cooling, and heat flow decreased during the post-rift stage. Under the influence of the fault reactivation and magmatic activity caused by Dongsha movement (9.8–5.5 Ma), the heat flow increased transitorily and then dropped again during the Neotectonic stage (10.0–0 Ma). Continental slope model: Two periods of extension made the lithosphere become hotter and hotter and heat flow increases rapidly during the syn-rift stage. Under continued spreading of the SCS, lithospheric thinning and rapidly-upwelling of mantle made the Moho elevated during the early period of drifting. Heat conducts to the surface more easily with a thinner crust and a shallower Moho. Hence, heat flow kept increasing during the post-rift stage and reached a peak value at 10.0 Ma. Local active faulting and magmatism lead to the transient increase of heat flow during the Neotectonic stage.

6. Conclusion 1. The Pearl River Mouth Basin (PRMB) is characterized by a high background heat flow. The present-day heat flow increases from the north to south of the northern South China Sea (SCS) where the crustal thickness decreases from the continental shelf to slope. 2. Two new thermal evolution models for continental shelf and continental slope of the PRMB are established. In the continental shelf, heat flow increased rapidly twice during the syn-rift stage, and then followed by continuous thermal subsidence with heat flow value decreased during the post-rift stage. While the heat flow in the slope continuously increased due to lithospheric thinning and mantle upwelling during the Neogene post-rift stage, which is different from the previously proposed heat model for the slope that heat flow continuously decreases during the post-rift. With multiple episodes of seafloor spreading of the SCS, heat flow gradually reduced after the cessation of the sea floor spreading (10 Ma). Tectonic settings and magmatism in deep mantle control the differential evolution of the passive continental margin. 3. The thermal evolution of the PRMB is mainly controlled by tectonic activities such as magmatism, lithospheric thinning and upwelling

5.3. Tectonic activity controls thermal evolution Thermal evolution is affected by many factors in the COT, include highly thinned crust, high basement radiogenic heat production, postspreading magmatic intrusion or thermal anomaly related to small-scale convection in the upper mantle (Nissen et al., 1995a, 1995b; Zhang and Wang, 2000; Yan et al., 2006a, 2006b; Lucazeau et al., 2008a, 2008b). Ductile lower crust became thinner during the syn-rift stage, and the heat flow increased rapidly (Fig. 14a and b). Multiple extensions result 13

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of the Moho. Lithospheric thinning and upwelling of the Moho are main control factors of thermal evolution during the rift and drift stage, the Neogene post-drift magmatic activity dominated the fluctuation of heat flow during the Neotectonic stage. Moreover, local multiple episodes of magmatic activities and diapirism led to the high maturity of source rocks in the LWS since 32 Ma.

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