Chemical Kinetics Models of Organic Matter (Vitrinite and Bitumen) Reflectance: Retrospect and Advances
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摘要: 镜质体反射率(Ro)和沥青反射率(BRo)化学动力学模型是标定沉积盆地热历史和预测烃源岩热演化最常用的研究手段，近年来已经取得显著进展，但并没有引起国内科研工作者的足够重视. 在回顾化学动力学模型研究历程的基础上，报道了相关研究新进展. Vitrimat 1989模型和经典的Easy%Ro模型基于3个原理：(1)Ro与H/C和O/C有关；(2)镜质体热降解产物为残余镜质体和4种产物(H2O、CO2、CHn、CH4)的总和；(3)热降解反应遵循Arrhenius方程. Easy%Ro模型存在设计缺陷：(1)使用的频率因子(1×1013)过低；(2)优化活化能分布时缺少过成熟度(Ro > 2.0%)样品. 在实际运用(地质升温速率)中的不足包括：(1)当实测Ro < 0.9%时，Easy%Ro模型对Ro的计算值过高；(2)当实测Ro > 2.0%时，Easy%Ro模型对Ro的计算值过低. 详细介绍了Basin%Ro、Easy%RoDL、Easy%RoV和Easy%RoB等新一代化学动力学模型的数据基础、校准原理和潜在适用性. BasinRo%模型在中‒低熟阶段展现的“dog-leg”曲线特征可能不适用于Ro-深度剖面；Easy%RoDL模型具有较强的地质条件适用性；Easy%RoV模型更加适用于实验室加热速率条件；在地质升温速率下，为Ro开发的新一代化学动力学模型全部提高了当Ro > 2.0%时的计算值；Easy%RoB模型是基于BRo-VRo(等效镜质体反射率)函数关系和Vitrimat 2018(Type-Ⅱ)模型并为BRo设计的模型，具有较高的地质条件适用性. 基于PetroMod盆地模拟平台中的Calibration化学动力学模块和Kinetics生烃动力学模块，展示了新一代化学动力学模型在超深层烃源岩成熟度标定和预测、中‒低成熟度烃源岩Ro反演热历史及盆地动力学、结合生烃动力学参数建立生烃模型等应用案例. 指出未来应重视地质升温速率/实验室加热速率下新一代化学动力学模型的适应性问题研究；提高反射率测量准确性、正确识别反射率受抑制程度、与低温热年代学参数耦合反演，对提高利用化学动力学模型开展盆地热历史研究的准确性具有重要意义.Abstract: The chemical kinetics model of the reflectance of vitrinite and bitumen is the most used research method to calibrate the thermal history of basin and predict the thermal evolution of source rocks. In recent years, important research progress has been made, but it has not attracted much attention from domestic researchers. Based on reviewing the research process of the chemical kinetic model of organic matter, in this paper it reports the new progress of relevant research. The classical Vitrimat model and Easy%Ro model are based on three principles: (1) the vitrinite reflectance is related to H/C and O/C. (2) The thermal degradation product of vitrinite was the sum of residual vitrinite and four kinds of products (H2O, CO2, CHn, CH4). (3) Thermal degradation reaction follows Arrhenius equation. Easy%Ro model has design defects: (1) the frequency factor (1×1013) is too low; (2) lack of high maturity (Ro > 2.0%) samples when optimizing activation energy distribution. The shortcomings in practical application include: (1) when the measured Ro < 0.9%, the calculated value of Easy%Ro is too high; (2) when the measured Ro > 2.0%, the calculated value of the Easy%Ro model is too low. New models Basin%Ro, Easy%RoDL, Easy%RoV and Easy%RoB (bitumen) are designed to overcome the obvious shortcomings of the Easy%Ro kinetics model, but the data basis, calibration principles and potential applicability of each model are different. The "dog-leg" curve characteristic of BasinRo% model at medium-low maturity stage may not be applicable to vitrinite reflectance-depth profile; The Easy%RoDL model has strong applicability to geological conditions; Easy%RoV is more suitable for laboratory heating rate conditions. At the geological heating rate, the new chemical kinetics models developed for Ro have all improved the calculated values when Ro > 2.0 %. Easy%RoB is a kinetics model designed for BRo based on the function relation of BRo-VRo (equivalent Vitinite reflectance) and Vitrimat 2018 (Type-Ⅱ) model, which has high applicability to geological conditions. Calibration chemical kinetics module and Kinetics hydrocarbon generation kinetics module in PetroMod basin simulation platform were used to carry out three studies: (1) calibration and prediction of ultra-deep source rock maturity, (2) thermal history and basin dynamics derived from vitrinite reflectance of medium to low maturity source rocks, (3) establishment of hydrocarbon generation model combined with hydrocarbon generation kinetics parameters. In the future, attention should be paid to the study of the adaptability of the new chemical kinetics models under laboratory/geological conditions. Improving the accuracy of reflectance measurement, correctly identifying the degree of reflectance inhibition, and being coupled with low temperature thermochronology parameter inversion are of great significance for improving the accuracy of basin thermal history research using chemical kinetics models.
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图 1 1987‒1989年和1990年之后发表的油页岩、烃源岩、干酪根和煤的生烃动力学参数中频率因子的累积概率分布
据Peters et al.(2016).1987‒1989年由劳伦斯利弗莫尔国家实验室(Lawrence Livermore National Laboratory，LLNL)发表的20个动力学参数中(Burnham et al.，1987，1989)，A的累积概率分布为0.5时，A值接近1×1013，该值即为Easy%Ro模型中20组活化能的通用频率因子(表 2)(Sweeney and Burnham, 1990；Burnham，2021a)；1990年之后由多个研究机构和石油公司发表的160个动力学参数中(Peters et al.，2016)，A的累计概率分布为0.5时，A值处于1×1014~2×1014(Burnham，2021b)
Fig. 1. Cumulative probability of frequency factors in kinetic parameters of oil shales, source rocks, kerogen and coal published in 1987‒1989 and after 1990
图 2 3 ℃/Ma地质升温速率条件下不同化学动力学模型计算的反射率与温度的关系
Fig. 2. The relationship between reflectance and temperature calculated by different chemical kinetic models at 3 ℃/Ma geological heating rate
图 3 20 ℃/h(a)和20 ℃/min(b)实验室加热速率条件下不同化学动力学模型计算的反射率与温度的关系
Fig. 3. The relationship between reflectance and temperature calculated by different chemical kinetics models at 20 ℃/h (a) and 20 ℃/min (b) laboratory heating rates, respectively
图 4 渤海湾盆地渤中凹陷钻井的埋藏史、热流史和镜质体反射率‒深度剖面
图 4a中太古界(Ar)与新生界(E)之间用波浪线表示沉积间断；图 4b中热流演化参考Qiu et al.(2022)，现今热流利用钻井实测温度标定，已省略
Fig. 4. Burial history, heat flow history and vitrinite reflectance-depth profile of Bozhong sag in offshore Bohai Bay basin
图 5 利用浅层钻井温度和浅层镜质体反射率‒深度剖面标定的渤海湾盆地渤中凹陷超深层成熟度预测曲线和温度曲线
图 5b和5e中热流演化(蓝色线)参考Qiu et al.(2022)，现今热流利用钻井实测温度标定，已省略；图 5e中热流演化(红色线)利用Easy%Ro模型反演标定
Fig. 5. Prediction of ultra-deep maturity curve and temperature curve of Bozhong sag in offshore Bohai Bay basin using shallow drilling temperature and shallow vitrinite reflectance-depth profile calibration, respectively
图 6 渤海湾盆地海域大地热流等值线图和沙河街组三段底部成熟度等值线
Fig. 6. Heat flow contour map and maturity contour line of the third member of Shahejie Formation of offshore Bohai Bay basin
图 7 分别使用Easy%RoDL模型和Easy%Ro模型标定的南黄海盆地热流演化史
Fig. 7. Heat flow evolution history of the South Yellow Sea Basin calibrated by Easy%RoDL and Easy%Ro, respectively
图 8 中国东部裂谷盆地热流演化史
胡圣标等(2019)对珠江口盆地开展的构造‒热演化研究为基底热流，推测珠江口盆地可能具有稍高的地表热流史
Fig. 8. Thermal evolution history of rift basins in eastern China
图 9 3℃/Ma地质升温速率下生烃动力学参数与化学动力学参数交汇建立的生烃地质模型
Fig. 9. Hydrocarbon generation geological model established by the intersection of hydrocarbon generation kinetic parameters and organic matter chemical kinetic parameters under the condition of the geological heating rate at 3℃/Ma
表 1 Vitrimat 1989模型和Vitrimat 2018 (vitrinite)模型参数
Table 1. Model parameters of Vitrimat (1989) and Vitrimat 2018 (vitrinite), respectively
Vitrimat 1989/ Vitrimat 2018 (vitrinite) x y χ α 0.90 0.90 0.35 0.35 0.28 0.20 0.25 0.21 β γ n 0.70 0.74 0.01 0.02 1.70 1.80 A 1×1013/s 2×1015/s 1×1013/s 2×1015/s 2×1013/s 2×1015/s 1×1013/s 2×1015/s E H2O CO2 CHn CH4 38 5 40 10 42 15 10 5 44 20 10 15 10 46 20 15 25 15 5 48 15 15 25 15 10 50 10 15 15 15 20 5 7 52 5 15 10 15 30 15 12 2 54 10 5 15 20 30 14 5 56 10 15 10 20 13 8 58 5 15 12 10 60 10 11 12 62 5 9 15 64 7 12 66 5 10 68 4 8 70 3 6 72 2 5 74 1 4 76 3 注：Vitrimat 1989模型参数根据Burnham and Sweeney (1989)，Vitrimat 2018(vitrinite)模型参数根据Burnham(2019). 
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表 2 Easy%Ro、Basin%Ro、Easy%RoDL、Easy%RoV和Easy%RoB化学动力学模型参数
Table 2. Chemical kinetic parameters of Easy%Ro, Basin%Ro, Easy%RoDL, Easy%RoV, and Easy%RoB, respectively
模型 Easy%Ro Basin%Ro Easy%RoDL Easy%RoV Easy%RoB Ro exp(3.7F-1.6) 0.210 4exp(3.7F) exp(3.7F-1.5) 0.223exp(3.7F) 0.15exp(3.7F) A 1×1013/s 9.7×1012/s 2×1014/s 2×1015/s 2×1014/s E 反应量 34 0.03 0.018 5 36 0.03 0.014 3 38 0.04 0.056 9 0.02 40 0.04 0.047 8 0.03 0.030 42 0.05 0.049 7 0.04 0.040 0.010 44 0.05 0.034 4 0.05 0.045 0.020 46 0.06 0.034 4 0.04 0.045 0.020 48 0.04 0.032 2 0.04 0.045 0.030 50 0.04 0.028 2 0.03 0.040 0.070 52 0.07 0.006 2 0.04 0.045 0.080 54 0.06 0.115 5 0.07 0.050 0.150 56 0.06 0.104 1 0.10 0.055 0.130 58 0.06 0.102 3 0.09 0.060 0.110 60 0.05 0.076 0 0.07 0.070 0.080 62 0.05 0.059 3 0.06 0.080 0.070 64 0.04 0.051 2 0.05 0.070 0.060 66 0.03 0.047 7 0.05 0.060 0.060 68 0.02 0.008 6 0.04 0.050 0.050 70 0.02 0.024 6 0.04 0.040 0.035 72 0.01 0.009 6 0.03 0.030 0.025 74 0.03 0.030 76 0.03 0.025 总反应量 0.85 0.921 5 0.95 0.91 1.00 注：Easy%Ro模型参数根据Sweeney and Burnham(1990)；Basin%Ro模型参数根据 Nielsen et al.(2017) ；Easy%RoDL模型参数根据Schenk et al.(2017) ；Easy%RoV和Easy%RoB模型参数根据Burnham(2019). 根据Sweeney and Burnham(1990，见该文附录)最初的计算公式，1 Ma被近似定义为3.16×1013s，在Basin%Ro模型中(Nielsen et al., 2017 )，频率因子(A)=exp(60.985 6)/Ma，Ma为百万年，因此Basin%Ro模型中的频率因子(A)=e60.985 6/3.16/1013=9.7×1012，其中e为自然指数. 另外，在本文中将1 Ma全部近似定义为3.16×1013 s (Sweeney and Burnham, 1990, 见该文附录)，部分讨论请见表 3注释.
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表 3 从化学动力学参数录入盆地与含油气系统模拟平台的参数转换
Table 3. Parameter conversion from chemical kinetic parameters into petroleum system and basin simulation platform
模型 Easy%Ro Basin%Ro Easy%RoDL Easy%RoV Easy%RoB E 初始比值 34 0.035 3 0.020 1 36 0.035 3 0.015 5 38 0.047 1 0.061 7 0.0211 40 0.047 1 0.051 9 0.031 6 0.033 0 42 0.058 8 0.053 9 0.042 1 0.044 0 0.010 0 44 0.058 8 0.037 3 0.052 6 0.049 5 0.020 0 46 0.070 6 0.037 3 0.042 1 0.049 5 0.020 0 48 0.047 1 0.034 9 0.042 1 0.049 5 0.030 0 50 0.047 1 0.030 6 0.031 6 0.044 0 0.070 0 52 0.082 4 0.006 7 0.042 1 0.049 5 0.080 0 54 0.070 6 0.125 3 0.073 7 0.054 9 0.150 0 56 0.070 6 0.113 0 0.105 3 0.060 4 0.130 0 58 0.070 6 0.111 0 0.094 7 0.065 9 0.110 0 60 0.058 8 0.082 5 0.073 7 0.076 9 0.080 0 62 0.058 8 0.064 4 0.063 2 0.087 9 0.070 0 64 0.047 1 0.055 6 0.052 6 0.076 9 0.060 0 66 0.035 3 0.051 8 0.052 6 0.065 9 0.060 0 68 0.023 5 0.009 3 0.042 1 0.054 9 0.050 0 70 0.023 5 0.026 7 0.042 1 0.044 0 0.035 0 72 0.011 8 0.010 4 0.031 6 0.033 0 0.025 0 74 0.031 6 0.033 0 76 0.031 6 0.027 5 初始Ro 0.202 0.210 0.223 0.223 0.150 终止Ro 4.688 6.365 7.501 6.465 6.067 A(1×1025/Ma) 31.6 30.65 632 6320 632 注：在PetroMod软件中，1 Ma被严格定义为3.153 6×1013s，这与Sweeney and Burnham(1990，见该文附录)给出的3.16×1013s近似值误差仅约为0.2%，因此将1 Ma设置为3.153 6×1013s或3.16×1013s均可；PetroMod软件中默认频率因子的单位为1×1025/Ma，其中s为秒，Ma为百万年，因此频率因子(1×1025/ Ma)=频率因子(s-1)×3.16×1013s/Ma/1025；也可改变频率因子的默认单位为s-1，读者亦可根据表 2中的参数进行设置. 在读者根据表 2或表 3的数据建立不同化学动力学模型时，请注意较新版本PetroMod软件中初始比值(Initial ratio)单位为百分比(%).
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