Advanced Search
Volume 42 Issue 4
Aug.  2024
Turn off MathJax
Article Contents
Article Navigation >  Acta Sedimentologica Sinica  > 2024  >  42(4): 1422-1432

SU Lei, CHANG XiangChun, XU YouDe, LIU ZhongQuan, SHI BingBing. Evaluation of the Biodegradation of Mesozoic Crude Oils in the Eastern Chepaizi Uplift[J]. Acta Sedimentologica Sinica, 2024, 42(4): 1422-1432. doi: 10.14027/j.issn.1000-0550.2022.140
Citation: SU Lei, CHANG XiangChun, XU YouDe, LIU ZhongQuan, SHI BingBing. Evaluation of the Biodegradation of Mesozoic Crude Oils in the Eastern Chepaizi Uplift[J]. Acta Sedimentologica Sinica, 2024, 42(4): 1422-1432. doi: 10.14027/j.issn.1000-0550.2022.140
shu

Evaluation of the Biodegradation of Mesozoic Crude Oils in the Eastern Chepaizi Uplift

doi: 10.14027/j.issn.1000-0550.2022.140
cstr: 32268.14.cjxb.62-1038.2022.140
  • 1.

    College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, China

  • 2.

    Institute of Petroleum Exploration and Development, Shengli Oilfield Company, SINOPEC, Dongying, Shandong 257015, China

Funds:

National Natural Science Foundation of China 42072172

  • Received Date: 2022-07-12
  • Accepted Date: 2022-11-25
  • Rev Recd Date: 2022-11-11
    • Available Online: 2022-11-25
  • Publish Date: 2024-08-10

  • Objective      Biodegraded crude oil is commonly found in poriferous basins globally. Biodegradation will have a profound impact on the physical properties and group components of crude oil, resulting in an increase in the oil density and viscosity, an enrichment in the non-hydrocarbon, asphaltene, sulfur metallic ion content and acid value. In recent years, the Mesozoic （Jurassic and Cretaceous） oil-bearing sandstone reservoirs in the east margin of the Chepaizi uplift have attracted much more attention due to the discovery of large quantities of crude oil, but their severe biodegradation restricts the exploration process. In order to clarify the biodegradation level of Mesozoic crude oil in the east margin of the Chepaizi uplift, the saturated hydrocarbon and the aromatic hydrocarbon fractions extracted from the reservoir samples from 10 wells in the Mesozoic east margin of Chepaezi uplift were analyzed by gas chromatography-mass spectrometry （GC-MS）, and molecular biomarkers strongly resistant to biodegradation were investigated.       Methods      Cluster analysis, a statistical method, is an effective tool to classify studied samples into different groups by their similarity distances which were calculated from the different variables investigated. Allowing for the severe oil alteration, the following nine biomarker parameters related to tricyclic terpenes （TT）, tetracyclic terpenes （Tet） and triaromatic steranes （TAS） with strong biodegradation resistance were selected： （C19TT + C20TT）/ （C23TT + C24TT）, C19TT/C23TT, C23TT/C21TT, C22TT/C21TT, C24TT/C23TT, ETR, C24 Tet/C26TT, C27 TAS/C28TAS （20R）, C26TAS/C28TAS （20S）. Cluster analysis （HCA） was performed to classify the Mesozoic crude oil populations. On this basis, the biodegradation level of Mesozoic crude oil was qualitatively evaluated according to the PM （Peters and Moldowan） method and descriptive terms. Then, following the academic theory of Manco scale, eight compounds with different sensitivities to microbial degradation, which characterize progressive bioresistance, were selected. Variables was assigned for them to optimize the quantitative evaluation scale of Manco method. The parametric vectors of the eight compounds generally covered the whole degradation level （PM0 ~ PM10）, including （1） n-alkanes （m/z 85）； （2） naphthalene and alkyl naphthalene （m/z 128, 142, 156, 170, 184, 198）； （3） alkyl dibenzothiophene （m/z 198, 212, 226）； （4） C0-3 phenanthrene （m/z 178, 192, 206, 220）； （5） pentacyclic triterpenes （m/z 191, 177, 205）； （6） sterane （m/z 217, 218, 259）； （7） tricyclic terpenoids （m/z 191, 177）； and （8） triaromatic steroids （m/z 231, 245）. MN1 （Manco Number 1） and MN2 （Manco Number 2） were calculated by the formulas, and the correlation between them and crude oil properties was analyzed.       Results and Discussions      The result shows that the Mesozoic crude oil is a typical heavy oil with high density and high viscosity, especially the viscosity of crude oil shows an order of magnitude change, which essentially reflects the alteration effect of microbial degradation. The oil density showed roughly positive correlation with the viscosity and the NSO （resin + asphaltene） fraction content, and negative correlation with the burial depth. Progressive biodegradation of crude oils may be responsible. The results of cluster analysis shows that the Mesozoic crude oil in the eastern Chepaizi uplift can be divided into four oil populations, i.e., I, II, III and IV. According to the difference of crude oil degradation level, different crude oil groups can be subdivided into different families. For example, group I crude oil is subdivided into family I1 crude oil （well P1, 781.5 m and 721.5 m） with a biodegradation level of PM7 （heavy） and family I2 crude oil （wells P607 and P624） with a biodegradation level of PM8 （very heavy）. Group II is subdivided into family II1 crude oil （well P1, 748.5 m and 751.2 m） with a biodegradation level of PM7 （heavy） and family II2 crude oil （wells P60 and P604） with a biodegradation level of PM9 （very heavy）. Group III is subdivided into family III1 crude oil （wells P629, P68, and P606） with a biodegradation level of PM9 （very heavy） and family III2 crude oil （well P646） with a biodegradation level of PM9+ （severe）. Group IV includes well P1（756.8 m, 757 m, 761.6 m, and 766.5 m） and well P609, and the biodegradation level of group IV is PM8 （very heavy）. Qualitative evaluation result by the PM method shows that the degradation level of Mesozoic crude oil can reach PM7-PM9+. The MN1 value obtained by the optimized Manco method ranges from 19 693 to 215 623； the MN2 value obtained by the optimized Manco method ranges from 768 to 954. For a single oil population, the values of MN1 and MN2 increased with the biodegradation level. In addition, the Manco number shows a good positive correlation with oil density, viscosity, non-hydrocarbon and asphaltene content, and a good negative correlation with total hydrocarbon content. The exception is the oil from well P646, which has a higher level of biodegradation than well P606 but shows a lower viscosity. Factually, there is not a simple relationship between the oil viscosity and the Manco number. Processes other than biodegradation, i.e., secondary oil charge, water washing, mixing of multiple maturity oil charges, and loss of light ends from heavy oils could produce variations in oil viscosity and density. The two episodes of oil charging, early biodegraded oils mixed with the later remigration of preexisting oils due to the structural adjustment, yet the same oil origin in the Chepaizi uplift maybe responsible for this case. In addition, differences in preservation conditions due to changes in burial depth can be one of the factors affecting biodegradation.       Conclusions      The optimized Manco method successfully distinguishes the oil-bearing reservoir samples with biodegradation level in PM7-PM9+, which is consistent with the PM result, that is, the biodegradation level of family Ⅰ1, family Ⅱ1, family Ⅰ2, group Ⅳ, family Ⅱ2, family Ⅲ1, family Ⅲ2 successively increases. In addition, the optimized Manco method provides a more detailed classification than the PM method, because it can clearly distinguish crude oil with the same PM level but different crude oil physical properties. This way, the differences in the biodegradation of oil-bearing reservoir samples can be clearly shown. The combination of qualitative evaluation by the PM method and quantitative evaluation by the optimized Manco method can reveal the difference in crude oil physical properties, which plays a guiding role for oil and gas exploration in this area.

  • [1] Head I M, Jones D M, Larter S R. Biological activity in the deep subsurface and the origin of heavy oil[J]. Nature, 2003, 426(6964): 344-352.
    [2] Meredith W, Kelland S J, Jones D M. Influence of biodegradation on crude oil acidity and carboxylic acid composition[J]. Organic Geochemistry, 2000, 31(11): 1059-1073.
    [3] Peters K E, Moldowan J M. The biomarker guide: Interpreting molecular fossils in petroleum and ancient sediments[M]. Englewood Cliffs, NJ: Prentice Hall, 1993: 363.
    [4] Volkman J K, Alexander R, Kagi R I, et al. Biodegradation of aromatic hydrocarbons in crude oils from the Barrow sub-basin of western Australia[J]. Organic Geochemistry, 1984, 6: 619-632.
    [5] Wenger L M, Isaksen G H. Control of hydrocarbon seepage intensity on level of biodegradation in sea bottom sediments[J]. Organic Geochemistry, 2002, 33(12): 1277-1292.
    [6] Larter S, Huang H P, Adams J, et al. A practical biodegradation scale for use in reservoir geochemical studies of biodegraded oils[J]. Organic Geochemistry, 2012, 45: 66-76.
    [7] Chang X C, Shi B B, Liu Z Q, et al. Investigation on the biodegradation levels of super heavy oils by parameter-striping method and refined Manco scale: A case study from the Chepaizi uplift of Junggar Basin[J]. Petroleum Science, 2021, 18(2): 380-397.
    [8] 胡秋媛,董大伟,赵利,等. 准噶尔盆地车排子凸起构造演化特征及其成因[J]. 石油与天然气地质,2016,37（4）：556-564.

    Hu Qiuyuan, Dong Dawei, Zhao Li, et al. Tectonic evolutionary characteristics and their causes of Chepaizi uplift in Junggar Basin[J]. Oil & Gas Geology, 2016, 37(4): 556-564.
    [9] Chang X C, Wang Y, Shi B B, et al. Charging of Carboniferous volcanic reservoirs in the eastern Chepaizi uplift, Junggar Basin (northwestern China) constrained by oil geochemistry and fluid inclusion[J]. AAPG Bulletin, 2019, 103(7): 1625-1652.
    [10] Shi B B, Chang X C, Xu Y D, et al. Charging history and fluid evolution for the Carboniferous volcanic reservoirs in the western Chepaizi uplift of Junggar Basin as determined by fluid inclusions and basin modelling[J]. Geological Journal, 2020, 55(4): 2591-2614.
    [11] Xu Y D, Chang X C, Shi B B, et al. Geochemistry of severely biodegraded oils in the Carboniferous volcanic reservoir of the Chepaizi uplift, Junggar Basin, NW China[J]. Energy Exploration & Exploitation, 2018, 36(6): 1461-1481.
    [12] 李阳. 准噶尔盆地车排子凸起东翼石炭系稠油地球化学与稠化机理研究[D]. 青岛：山东科技大学,2018.

    Li Yang. Geochemistry and genetic mechanism of heavy oil in the eastern Chepaizi uplift, Junggar Basin[D]. Qingdao: Shandong University of Science and Technology, 2018.
    [13] 张枝焕,向奎,秦黎明,等. 准噶尔盆地四棵树凹陷烃源岩地球化学特征及其对车排子凸起油气聚集的贡献[J]. 中国地质,2012,39（2）：326-337.

    Zhang Zhihuan, Xiang Kui, Qin Liming, et al. Geochemical characteristics of source rocks and their contribution to petroleum accumulation of Chepaizi area in Sikeshu Depression, Junggar Basin[J]. Geology in China, 2012, 39(2): 326-337.
    [14] Shi B B, Chang X C, Xu Y D, et al. Origin and migration pathway of biodegraded oils pooled in multiple-reservoirs of the Chepaizi uplift, Junggar Basin, NW China: Insights from geochemical characterization and chemometrics methodst[J]. Marine and Petroleum Geology, 2020, 122: 104655.
    [15] 沈扬,贾东,宋国奇,等. 源外地区油气成藏特征、主控因素及地质评价：以准噶尔盆地西缘车排子凸起春光油田为例[J]. 地质论评,2010,56（1）：51-59.

    Shen Yang, Jia Dong, Song Guoqi, et al. Reservoir-forming characters, key control factors and geological evaluation in the area outside oil source: Take the Chunguang oilfield in Chepaizi uplift in western Junggar Basin as an example[J]. Geological Review, 2010, 56(1): 51-59.
    [16] 牛靖靖. 准西车排子地区中生界油气成藏主控因素分析[D]. 青岛：中国石油大学（华东）,2015.

    Niu Jingjing. Analysis on main controling factors of Mesozoic hydrocarbon accumulation in Chepaizi area of west Junggar Basin[D]. Qingdao: China University of Petroleum (East China), 2015.
    [17] Peters K E, Walters C C, Moldowan J M. The biomarker guide: Biomarkers and isotopes in petroleum exploration and earth history[M]. 2nd ed. New York: Cambridge University Press, 2005: 222-223.
    [18] Wang G L, Wang T G, Simoneit B R T, et al. Investigation of hydrocarbon biodegradation from a downhole profile in Bohai Bay Basin: Implications for the origin of 25-norhopanes[J]. Organic Geochemistry, 2013, 55: 72-84.
    [19] Chang X C, Wang G L, Guo H H, et al. A case study of crude oil alteration in a clastic reservoir by waterflooding[J]. Journal of Petroleum Science and Engineering, 2016, 146: 380-391.
    [20] Larter S, Wilhelms A, Head I, et al. The controls on the composition of biodegraded oils in the deep subsurface: Part 1: Biodegradation rates in petroleum reservoirs[J]. Organic Geochemistry, 2003, 34(4): 601-613.
    [21] López L, Mónaco S L, Volkman J K. Evidence for mixed and biodegraded crude oils in the Socororo field, eastern Venezuela Basin[J]. Organic Geochemistry, 2015, 82: 12-21.
    [22] 常象春,孙婷婷,王悦,等. 水驱原油组分蚀变的地球化学响应及控制因素[J]. 地球科学与环境学报,2017,39（6）：807-825.

    Chang Xiangchun, Sun Tingting, Wang Yue, et al. Geochemical alteration of waterflooded oils and the controlling factors[J]. Journal of Earth Sciences and Environment, 2017, 39(6): 807-825.
    [23] López L. Study of the biodegradation levels of oils from the Orinoco Oil Belt (Junin area) using different biodegradation scales[J]. Organic Geochemistry, 2014, 66: 60-69.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(5)  / Tables(3)

Get Citation
PDF
XML

Article Metrics

Article views(80) PDF downloads(15) Cited by()

Proportional views
Related
Publishing history
  • Received:  2022-07-12
  • Revised:  2022-11-11
  • Accepted:  2022-11-25
  • Published:  2024-08-10

Evaluation of the Biodegradation of Mesozoic Crude Oils in the Eastern Chepaizi Uplift

doi: 10.14027/j.issn.1000-0550.2022.140
  • 1. College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, China
  • 2. Institute of Petroleum Exploration and Development, Shengli Oilfield Company, SINOPEC, Dongying, Shandong 257015, China
Funds:

National Natural Science Foundation of China 42072172

  • Received Date: 2022-07-12
  • Accepted Date: 2022-11-25
  • Rev Recd Date: 2022-11-11
  • Available Online: 2022-11-25
  • Publish Date: 2024-08-10

Abstract: 

Objective      Biodegraded crude oil is commonly found in poriferous basins globally. Biodegradation will have a profound impact on the physical properties and group components of crude oil, resulting in an increase in the oil density and viscosity, an enrichment in the non-hydrocarbon, asphaltene, sulfur metallic ion content and acid value. In recent years, the Mesozoic （Jurassic and Cretaceous） oil-bearing sandstone reservoirs in the east margin of the Chepaizi uplift have attracted much more attention due to the discovery of large quantities of crude oil, but their severe biodegradation restricts the exploration process. In order to clarify the biodegradation level of Mesozoic crude oil in the east margin of the Chepaizi uplift, the saturated hydrocarbon and the aromatic hydrocarbon fractions extracted from the reservoir samples from 10 wells in the Mesozoic east margin of Chepaezi uplift were analyzed by gas chromatography-mass spectrometry （GC-MS）, and molecular biomarkers strongly resistant to biodegradation were investigated.       Methods      Cluster analysis, a statistical method, is an effective tool to classify studied samples into different groups by their similarity distances which were calculated from the different variables investigated. Allowing for the severe oil alteration, the following nine biomarker parameters related to tricyclic terpenes （TT）, tetracyclic terpenes （Tet） and triaromatic steranes （TAS） with strong biodegradation resistance were selected： （C19TT + C20TT）/ （C23TT + C24TT）, C19TT/C23TT, C23TT/C21TT, C22TT/C21TT, C24TT/C23TT, ETR, C24 Tet/C26TT, C27 TAS/C28TAS （20R）, C26TAS/C28TAS （20S）. Cluster analysis （HCA） was performed to classify the Mesozoic crude oil populations. On this basis, the biodegradation level of Mesozoic crude oil was qualitatively evaluated according to the PM （Peters and Moldowan） method and descriptive terms. Then, following the academic theory of Manco scale, eight compounds with different sensitivities to microbial degradation, which characterize progressive bioresistance, were selected. Variables was assigned for them to optimize the quantitative evaluation scale of Manco method. The parametric vectors of the eight compounds generally covered the whole degradation level （PM0 ~ PM10）, including （1） n-alkanes （m/z 85）； （2） naphthalene and alkyl naphthalene （m/z 128, 142, 156, 170, 184, 198）； （3） alkyl dibenzothiophene （m/z 198, 212, 226）； （4） C0-3 phenanthrene （m/z 178, 192, 206, 220）； （5） pentacyclic triterpenes （m/z 191, 177, 205）； （6） sterane （m/z 217, 218, 259）； （7） tricyclic terpenoids （m/z 191, 177）； and （8） triaromatic steroids （m/z 231, 245）. MN1 （Manco Number 1） and MN2 （Manco Number 2） were calculated by the formulas, and the correlation between them and crude oil properties was analyzed.       Results and Discussions      The result shows that the Mesozoic crude oil is a typical heavy oil with high density and high viscosity, especially the viscosity of crude oil shows an order of magnitude change, which essentially reflects the alteration effect of microbial degradation. The oil density showed roughly positive correlation with the viscosity and the NSO （resin + asphaltene） fraction content, and negative correlation with the burial depth. Progressive biodegradation of crude oils may be responsible. The results of cluster analysis shows that the Mesozoic crude oil in the eastern Chepaizi uplift can be divided into four oil populations, i.e., I, II, III and IV. According to the difference of crude oil degradation level, different crude oil groups can be subdivided into different families. For example, group I crude oil is subdivided into family I1 crude oil （well P1, 781.5 m and 721.5 m） with a biodegradation level of PM7 （heavy） and family I2 crude oil （wells P607 and P624） with a biodegradation level of PM8 （very heavy）. Group II is subdivided into family II1 crude oil （well P1, 748.5 m and 751.2 m） with a biodegradation level of PM7 （heavy） and family II2 crude oil （wells P60 and P604） with a biodegradation level of PM9 （very heavy）. Group III is subdivided into family III1 crude oil （wells P629, P68, and P606） with a biodegradation level of PM9 （very heavy） and family III2 crude oil （well P646） with a biodegradation level of PM9+ （severe）. Group IV includes well P1（756.8 m, 757 m, 761.6 m, and 766.5 m） and well P609, and the biodegradation level of group IV is PM8 （very heavy）. Qualitative evaluation result by the PM method shows that the degradation level of Mesozoic crude oil can reach PM7-PM9+. The MN1 value obtained by the optimized Manco method ranges from 19 693 to 215 623； the MN2 value obtained by the optimized Manco method ranges from 768 to 954. For a single oil population, the values of MN1 and MN2 increased with the biodegradation level. In addition, the Manco number shows a good positive correlation with oil density, viscosity, non-hydrocarbon and asphaltene content, and a good negative correlation with total hydrocarbon content. The exception is the oil from well P646, which has a higher level of biodegradation than well P606 but shows a lower viscosity. Factually, there is not a simple relationship between the oil viscosity and the Manco number. Processes other than biodegradation, i.e., secondary oil charge, water washing, mixing of multiple maturity oil charges, and loss of light ends from heavy oils could produce variations in oil viscosity and density. The two episodes of oil charging, early biodegraded oils mixed with the later remigration of preexisting oils due to the structural adjustment, yet the same oil origin in the Chepaizi uplift maybe responsible for this case. In addition, differences in preservation conditions due to changes in burial depth can be one of the factors affecting biodegradation.       Conclusions      The optimized Manco method successfully distinguishes the oil-bearing reservoir samples with biodegradation level in PM7-PM9+, which is consistent with the PM result, that is, the biodegradation level of family Ⅰ1, family Ⅱ1, family Ⅰ2, group Ⅳ, family Ⅱ2, family Ⅲ1, family Ⅲ2 successively increases. In addition, the optimized Manco method provides a more detailed classification than the PM method, because it can clearly distinguish crude oil with the same PM level but different crude oil physical properties. This way, the differences in the biodegradation of oil-bearing reservoir samples can be clearly shown. The combination of qualitative evaluation by the PM method and quantitative evaluation by the optimized Manco method can reveal the difference in crude oil physical properties, which plays a guiding role for oil and gas exploration in this area.

SU Lei, CHANG XiangChun, XU YouDe, LIU ZhongQuan, SHI BingBing. Evaluation of the Biodegradation of Mesozoic Crude Oils in the Eastern Chepaizi Uplift[J]. Acta Sedimentologica Sinica, 2024, 42(4): 1422-1432. doi: 10.14027/j.issn.1000-0550.2022.140
Citation: SU Lei, CHANG XiangChun, XU YouDe, LIU ZhongQuan, SHI BingBing. Evaluation of the Biodegradation of Mesozoic Crude Oils in the Eastern Chepaizi Uplift[J]. Acta Sedimentologica Sinica, 2024, 42(4): 1422-1432. doi: 10.14027/j.issn.1000-0550.2022.140
shu

    HTML

0.   引言

  • 全球范围内原油的生物降解现象较为普遍,大量研究表明生物降解对原油物理性质及组分都有影响。经过生物降解作用,原油黏度增加,非烃、沥青质、硫和金属离子含量增加,酸值上升[1⁃5]。原油生物降解的评价方法主要有PM法和Manco法。PM法是Peters et al.[3]基于化合物类型对微生物侵蚀的抵抗能力建立的定性评价生物降解的方法,可将生物降解等级分为10个级别（PM1~PM10）,Wenger et al.[5]根据降解程度又补充说明了描述性的术语在PM法中的赋值规则：轻微（PM1~PM3）；中等（PM4~PM5）；严重（PM6~PM7）；很严重（PM8~PM9）；强烈（PM10）。Manco法是Larter et al.[6]提出的一种定量评价生物降解的方法,Manco法选取了8种抗生物降解能力逐渐增强的化合物（烷基甲苯、萘+甲基萘、C2萘、C3萘、C4萘、C0-2菲、甲基二苯并噻吩和甾烷）,并按照8种化合物的降解程度划分为5个等级,即完全未降解（Manco赋值为0）,只发生轻微降解（Manco赋值为1）,化合物不完全降解（Manco赋值为3）和介于这二者之间的（Manco赋值为2）,完全降解（通常化合物被全部消耗,Manco赋值为4）。通过Manco法获取的MN1和MN2值可以清晰地区别介于PM4~PM8的原油,提高了生物降解程度评价的精度。但Manco法只适用于区别介于PM4~PM8的原油,不适用于生物降解程度在PM8以上的原油。但Larter et al.[6]也提出了可以通过优化Manco法中的赋值参数,构建适用于更高生物降解程度的原油评价。

    准噶尔盆地是我国西部油气资源最为丰富的含油气盆地之一,车排子凸起石炭系是主要的产油层。近年来在车排子凸起中生界也发现良好的油气显示,但此处的油气来源仍存在争议,生物降解作用造成的油源对比困难是其缘由之一,因而研究车排子凸起中生界原油生物降解情况对深化油气勘探评价具有重要意义。Chang et al.[7]研究发现车排子凸起石炭系原油的生物降解程度可达PM9+,由于车排子凸起的中生界原油与石炭系原油具有相似的地球化学特征,考虑到中生界原油也存在严重降解的可能性,本文利用PM法和优化的Manco法对准噶尔盆地车排子凸起中生界原油生物降解程度进行定性和定量的综合评价。

1.   地质背景

  • 车排子凸起位于准噶尔盆地的西部隆起南段,面积约1.08×104 km2[8],是一个继承性古隆起,形成于海西晚期构造运动早期[9⁃11]。西面和北面邻近扎伊尔山,南面为四棵树凹陷,向东以红车断裂带与沙湾凹陷相接,整体上呈三角形（图1a[12]）。准噶尔盆地车排子凸起自晚石炭世已开始发育,依次经历了强挤压—弱挤压—较弱挤压—弱伸展的演化过程,其构造演化可划分为初始发育（C3~P）、持续隆升（T~J）、稳定埋深（K~E）和局部伸展掀斜（N~Q）4个阶段[8]。车排子凸起基底为石炭系,自下而上发育侏罗系、白垩系、古近系、新近系和第四系,缺失二叠系和三叠系。各时代地层厚度总体较薄,向西北向尖灭[13]。车排子凸起断层发育,保存了多期构造运动叠加的构造格局,且油气源条件优越,成为盆地内重要的油气聚集区[8]。车排子凸起拥有3套含油储层、6套烃源岩（石炭系、中—下二叠系、上三叠统、中—下侏罗系、白垩系、古近系）、多期油气充注、原油物性多变[14]。近年来,在车排子凸起白垩系、侏罗系、古近系和新近系获得高产工业油气流,显示良好的油气勘探前景[15]。

    Figure 1.  Structural units and well location in the Chepaizi uplift

2.   样品与实验

  • 本次研究共采集车排子凸起东翼中生界10口井的含油储层岩石样品,其中包括侏罗系P1井；白垩系P1井、P60井、P68井、P604井、P606井、P607井、P609井、P624井、P629井、P646井（图1b）。

    将适量储层岩石样品（10 g）磨成100目的粉末,用正己烷和二氯甲烷进行萃取获得抽提物,使用常规硅胶和氧化铝柱进行柱层析,用正己烷和二氯甲烷得到脂肪族和芳香族组分。使用安捷伦7890A GC/5977 MSD仪器对脂肪族和芳香族组分进行了气相色谱—质谱法（GC-MS）分析。脂肪族组分的GC温度操作条件为：从100 ℃(1 min)升至220 ℃,速率为4 ℃/min,然后以2℃/min的速率升至300 ℃(保温5 min)；芳香族组分的GC温度操作条件为：从80 ℃(1 min)升至300 ℃(保温15 min),速率为3 ℃/min。MS（质谱）条件如下：电子碰撞(EI)电离模式,70 eV电子能量,300 mA发射电流,50~550 amu/s扫描范围。

3.   结果与讨论

    3.1.   原油物性

  • 本实验选取的侏罗系和白垩系的样品都集中在车排子凸起东翼。侏罗系原油的密度在0.945~0.988 g·cm-3,黏度在592~5 879 mPa·s[16]；白垩系原油的密度在0.945 0~0.980 2 g·cm-3,黏度在592~37 192 mPa·s（表1）。侏罗系原油和白垩系原油均为重质稠油,原油族组成中非烃和沥青质含量介于28.57%~75.48%,占绝对优势（图2）。

    井号深度/m层位饱和烃/%芳烃/%非烃+沥青质/%饱/芳总烃/%密度/g·cm-3黏度/mPa·s
    P1721.5K35.6527.7936.561.2863.440.945 0592
    P1748.5K57.299.7232.995.8967.010.946 02 301
    P1751.2K41.738.6549.624.8350.380.946 02 301
    P1756.8J35.3114.8949.802.3750.200.945 0592
    P1757.0J37.8111.5150.683.2949.320.945 0592
    P1761.6J16.358.1775.482.0024.520.988 05 879
    P1766.5J25.2115.2959.501.6540.500.988 05 879
    P1781.5J42.8628.5728.571.5071.430.945 0592
    P604682.9K27.0216.4356.551.6443.45
    P606960.5K27.3217.5655.121.5644.880.956 82 354
    P607349.1K29.8418.3351.831.6348.170.975 029 664
    P646256.5K22.8910.4466.672.1933.330.962 91 830
    P60579.9K40.9618.0840.962.2759.040.963 58 978
    P68930.1K42.3418.9238.742.2461.26
    P609310.1K33.9424.0941.971.4158.030.980 237 192
    P624278.0K37.3321.2041.471.7658.53
    P629385.0K12.9626.1360.910.5039.09

    Table 1.  Physical property parameters of crude oil[16]

    Figure 2.  Ternary diagram of oil bulk compositions

    • 3.2.   原油族群划分

  • 来源于同一烃源层或同一油源区的原油定义为同一原油族群（Oil Population）。聚类分析（HCA）是将研究对象分为相对同质的群组的统计分析技术,可以根据不同变量计算出的相似距离将研究样本分为不同的组。选取与三环萜烷（TT）、四环萜烷（Tet）、三芳甾烷（TAS）相关的9个抗生物降解极强的生物标志物参数：（C19TT+C20TT）/（C23TT+C24TT）,C19TT/C23TT,C23TT/C21TT,C22TT/C21TT,C24TT/C23TT,ETR,C24Tet/C26TT,C27TAS/C28TAS（20R）,C26TAS/C28TAS（20S）,采用聚类分析对车排子凸起东翼中生界原油样品进行划分（表2）。在聚类谱系图中（图3）,根据不同变量计算出的相似距离,可以分为Ⅰ、Ⅱ、Ⅲ、Ⅳ四类族群。

    井号层系深度/mL1L2L3L4L5L6L7L8L9族群
    P1K721.50.430.172.080.420.330.870.301.150.56Ⅰ
    P1J781.50.440.151.050.280.530.890.361.420.27Ⅰ
    P607K349.10.470.151.100.430.340.870.351.120.11Ⅰ
    P624K278.00.970.350.750.170.330.880.411.320.14Ⅰ
    P1K748.50.530.181.040.260.500.860.330.360.67Ⅱ
    P1K751.20.720.180.840.230.500.900.290.681.55Ⅱ
    P60K579.90.210.061.170.300.500.770.300.361.66Ⅱ
    P604K682.90.430.201.870.730.520.870.251.132.35Ⅱ
    P68K930.11.580.470.600.220.550.800.412.500.75Ⅲ
    P606K960.51.490.430.740.180.370.800.441.021.21Ⅲ
    P629K385.01.010.572.190.740.350.830.351.390.89Ⅲ
    P646K256.50.880.502.360.750.300.820.190.980.96Ⅲ
    P1J756.80.220.122.810.620.270.810.330.330.81Ⅳ
    P1J757.00.270.155.961.140.290.800.300.621.38Ⅳ
    P1J761.60.120.108.801.210.300.790.340.910.52Ⅳ
    P1J766.50.420.184.100.840.280.800.330.860.54Ⅳ
    P609K310.10.540.170.880.260.370.780.331.170.21Ⅳ
    注：L1=（C19TT+C20TT）/（C23TT+C24TT）；L2= C19TT/C23TT；L3= C23TT/C21TT；L4= C22TT/C21TT；L5= C24TT/C23TT；L6= ETR；L7= C24Tet/C26TT；L8= C27TAS/C28TAS（20R）；L9= C26TAS/C28TAS（20S）。

    Table 2.  Geochemical parameters of crude oil and population identification

    Figure 3.  Dendrogram of cluster analysis of the crude oil populations

    • 3.3.   PM法定性评价生物降解

  • 车排子凸起东翼中生界储层样品的饱和烃总离子流图（TIC）具有高度相似特征,谱图基线呈现明显的“鼓包”,反映色谱分析未分辨的复杂混合物,主要是环烷烃及异构烷烃成分,称之为UCM峰（Unresolved Complex Mixture）,通常作为原油遭受生物降解作用的标志。通过对饱和烃总离子流谱图、反映萜烷系列化合物的m/z 191谱图、反映甾烷系列化合物的m/z 217谱图和反映芳香甾烷系列化合物的m/z 231谱图的分析,发现车排子凸起原油呈现不同的生物降解特征,依据Peters和Moldowan在1993年提出的PM法[3]和Wenger et al.[5]在2002年补充说明的描述性的术语在PM法中的赋值规则,对车排子凸起原油生物降解程度进行评价。

    Ⅰ类原油可细分为Ⅰ1类原油：P1（781.5 m）、P1（721.5 m）和Ⅰ2类原油：P607（349.1 m）、P624（278 m）。Ⅰ1类原油饱和烃的TIC图上可见显著的UCM鼓包,仅可检测到少量的正构烷烃化合物（图4a）。m/z 191谱图中,藿烷以C30H为主峰,三环萜烷呈现C23TT优势,三环萜烷未发生降解,说明降解程度未达PM8[17]（图4a）。m/z 217谱图中,甾烷发生实质性消耗,说明生物降解程度已达PM7[3]（图4a）。m/z 231谱图中,萘和菲基本上完全消除,三芳甾烷未发生降解（图4a）,原油生物降解程度定为PM7。Ⅰ2类原油饱和烃的TIC图上可见显著的UCM鼓包,仅可检测到少量的正构烷烃化合物（图4b）,m/z 191谱图中,25-NH（25-降藿烷）消失,藿烷严重消耗,说明生物降解程度可达PM8[3]。更耐生物降解的三环萜烷初步消耗,三环萜烷呈现C21TT优势,表明生物降解等级已达PM8[17]（图4b）。m/z 217谱图中,甾烷基本上完全消除,孕甾烷和升孕甾烷丰度远高于甾烷（图4b）。m/z 231谱图中,三芳甾烷未发生降解（图4b）,原油生物降解程度定为PM8。

    Figure 4.  Evaluation of biodegradation level of representative samples from the Chepaizi uplift

    Ⅱ类原油可细分为Ⅱ1类原油：P1（748.5 m）、P1（751.2 m）和Ⅱ2类原油：P60（579.9 m）和P604（682.9 m）。Ⅱ1类原油饱和烃的TIC图上可见显著的UCM鼓包,仅可检测到少量的正构烷烃化合物（图4c）。m/z 191谱图中,藿烷以C30H为主峰。三环萜烷呈现C23TT优势,三环萜烷未发生降解,说明降解程度未达PM8[17]（图4c）。m/z 217谱图中,甾烷发生实质性消耗,说明生物降解程度已达PM7[3]（图4c）。m/z 231谱图中,萘和菲基本上完全消除,三芳甾烷未发生降解（图4c）,原油生物降解程度定为PM7。Ⅱ2类原油饱和烃的TIC图上难以检测到可分辨的生物标志物（图4d）。m/z 191谱图中,藿烷系列已完全消除,三环萜烷系列发生实质性的消耗但丰度仍高于藿烷系列（图4d）。m/z 217谱图中,重排甾烷发生实质性消耗,说明生物降解程度达PM9[3]（图4d）。芳烃的m/z 231谱图中,三芳甾烷未发生降解（图4d）,原油生物降解程度定为PM9。

    Ⅲ类原油可细分为Ⅲ1类原油：P629（385 m）、P68（930.1 m）、P606（960.5 m）和Ⅲ2类原油：P646（256.5 m）。Ⅲ1类原油饱和烃的TIC图上难以检测到可分辨的生物标志物（图4e）。m/z 191谱图中,藿烷系列已完全消除,三环萜烷系列发生实质性的消耗但丰度仍高于藿烷系列（图4e）。m/z 217谱图中,重排甾烷发生实质性消耗,说明生物降解程度达PM9[3]（图4e）。m/z 231谱图中,三芳甾烷未发生降解（图4e）,原油生物降解程度定为PM9。Ⅲ2类原油饱和烃的TIC图上难以检测到可分辨的生物标志物（图4f）。m/z 191谱图中,三环萜烷基本上完全消除,与已完全消耗的藿烷系列丰度相当（图4f）。m/z 217谱图中,重排甾烷基本上完全消除,孕甾烷和升孕甾烷发生实质性降解（图4f）,孕甾烷和升孕甾烷要比规则甾烷和重排甾烷的抗生物降解能力更强[18],说明生物降解程度大于PM9[3]。m/z 231谱图中,三芳甾烷初步消耗（图4f）,芳香化的甾族烃是抵抗生物降解能力最强的化合物,在生物降解等级达PM10之外的几乎所有原油中仍然能保存不变[17],原油生物降解程度定为PM9+。

    Ⅳ类原油包括P1（756.8 m）、P1（757 m）、P1（761.6 m）、P1（766.5 m）和P609（310.1 m）。饱和烃的TIC图上难以检测到可分辨的生物标志物（图4g）。m/z 191谱图中,25-NH消失,藿烷严重消耗（图4g）,说明生物降解程度可达PM8[3]。更耐生物降解的三环萜烷初步消耗（图4g）,表明着生物降解等级已达PM8[17]。m/z 217谱图中,甾烷基本上完全消除,孕甾烷和升孕甾烷丰度远高于甾烷（图4g）。芳烃的m/z 231谱图中,三芳甾烷未发生降解（图4g）,原油生物降解程度定为PM8。

    • 3.4.   基于优化Manco法的降解程度定量评价

  • 基于Manco法的学术思想,选取了8种对微生物降解作用的敏感性不同且呈现递减关系的化合物,来优化Manco法的赋值参数,对原油生物降解程度进行定量分析。8种化合物的参数向量覆盖全降解区间（PM0~PM10）,具体为：（1）正构烷烃（m/z 85）；（2）萘和烷基萘（m/z 128、142、156、170、184、198）；（3）烷基二苯并噻吩（m/z 198、212、226）；（4）C0-3菲（m/z 178、192、206、220）；（5）五环三萜类（m/z 191、177、205）；（6）甾烷（m/z 217、218、259）；（7）三环萜类（m/z 191、177）；（8）三芳甾类（m/z 231、245）。对所有样品进行分析评价,定性划分出8种化合物的降解程度,通过以下公式计算MN1（Manco Number 1）和MN2（Manco Number 2）[6]。

    MN1=Σmi5i (1)
    MN2=[n+log5(MN1)×(Smax-1)]/n (2)

    式中：m是指八个向量元素（0~4）中每个元素的Manco分数,i表示类号（0~7）,n是复合类的数量。Smax是MN2的最大值,被指定为1 000,以避免与当前存在的尺度混淆,并在使用整数值时确保在不同的生物降解水平下有足够的分辨率。结果如表3。

    族群井号深度/m层位PMNAN+MNMDBTP+MPH+25-NHSTTTASMN1MN2
    Ⅰ1P1721.5K73322212035 943815
    Ⅰ1P1781.5J73444111019 998769
    Ⅰ2P624278.0K82232213051 587843
    Ⅰ2P607349.1K834443331136 873919
    Ⅱ1P1748.5K73322111019 693768
    Ⅱ2P60579.9K944343221118 099907
    Ⅲ1P606960.5K942344121115 589906
    Ⅲ1P629385.0K934344331137 473919
    Ⅲ2P646256.5K9+34444332215 623954
    ⅣP1757.0J84234311021 214774
    ⅣP1761.6J83434311021 223774
    ⅣP1766.5J83434312036 848817
    注：NA.正构烷烃；N+MN.萘+烷基萘；MDBT.烷基二苯并噻吩；P+MP.菲+烷基菲；H+25-NH.藿烷+25-降藿烷；S.甾烷；TT.三环萜烷；TAS.三芳甾烷。

    Table 3.  MN1 and MN2 values calculated by improved Manco method

    由表3可知,优化的Manco法求得的MN1值介于19 693~215 623,MN2值介于768~954,在同一原油族群内,MN1值和MN2值随着生物降解程度增大而增大。Ⅰ类原油的MN2值介于769~919,Ⅱ类原油的MN2值介于768~907,Ⅲ类原油的MN2值介于906~954,Ⅳ类原油的MN2值介于774~817。在同一原油族群内,Manco数与原油密度（图5a）、黏度（图5b）、非烃和沥青质含量（图5c）均呈现良好的正相关性,Manco数与总烃呈现良好的负相关性（图5d）。研究表明,生物降解过程降低了饱和烃和芳香烃的含量,并丰富了非烃和沥青质的含量,从而导致原油密度的增加[19⁃22]。比较例外的是,Ⅲ类原油中生物降解程度更高的P646井样品,其黏度却低于P606井样品。事实上,原油黏度和Manco数之间并不是简单的线性关系[6]。生物降解以外的过程,即二次充注、水洗、混合多种成熟度充注以及重油中轻馏分的损失均可能导致油的黏度和API比重发生变化[23]。造成这种情况的原因可能是存在两期来源相同的石油充注,早期生物降解石油与后期石油混杂[9⁃10]。此外,埋藏深度变化导致的保存条件差异通常也是影响生物降解的因素之一。

    Figure 5.  Correlation of MN2 with (a) oil density; (b) oil viscosity; (c) non⁃hydrocarbon and asphaltene content; and (d) total hydrocarbon

    可见,PM法及优化的Manco法得出了较为一致的结论,成功厘定了生物降解程度在PM7-PM9+的样品：Ⅰ1类、Ⅱ1类、Ⅰ2类、Ⅳ类、Ⅱ2类、Ⅲ1类、Ⅲ2类原油的生物降解程度依次增强。

    • 3.5.   地球化学意义

  • PM法和优化Manco法具有一致性,但相比PM法,优化Manco法对原油生物降解的划分分辨率更高,可以区分PM等级相同但原油黏度不同的超稠油的生物降解程度,以了解相关样品之间生物降解过程程度的相对差异。与Larter et al.[6]创建的Manco等级（通常与PM等级4~8相关）相比,优化Manco法能够评价生物降解PM等级0~10的储层样品,是涵盖全区间的生物降解评价方法,适用于发生严重生物降解的原油生物降解程度评价。但本次优化的Manco法也存一些不足,如Ⅳ类原油中P1井（757 m）和P1井（761.6 m）的样品原油物性参数不同,但求得的MN2值相近,优化过程尚需进一步探索。

    车排子凸起中生界稠油生物降解程度极高,稠油的黏度显示出数量级的变化,通过PM法定性评价和优化Manco法定量评价相结合,可以很好地揭示原油密度和黏度的变化,生物降解等级评价对深化油气藏的认识和勘探策略调整都有帮助。

4.   结论

  • （1） 车排子凸起中生界侏罗系和白垩系原油均为重质稠油,非烃和沥青质含量较高。通过聚类分析,可以将车排子凸起东部的原油分为Ⅰ、Ⅱ、Ⅲ、Ⅳ四类油族。按照原油降解程度的差异,不同原油族群还可以细分为不同组群。如Ⅰ类原油可划分为Ⅰ1类原油和Ⅰ2类原油；Ⅱ类原油可划分为Ⅱ1类原油和Ⅱ2类原油；Ⅲ类原油可划分为Ⅲ1类原油和Ⅲ2类原油。

    （2） PM法定性评价表明中生界原油降级程度可达PM7~PM9+。Ⅰ1类原油生物降解程度为PM7,Ⅰ2类原油生物降解程度为PM8；Ⅱ1类原油生物降解程度为PM7,Ⅱ2类原油生物降解程度为PM9；Ⅲ1类原油生物降解程度为PM9,Ⅲ2类原油生物降解程度定PM9+；Ⅳ类原油生物降解程度为PM8。PM分析结果表明Ⅰ1类、Ⅱ1类、Ⅰ2类、Ⅳ类、Ⅱ2类、Ⅲ1类、Ⅲ2类原油的生物降解程度依次增强。

    （3） 基于优化的Manco法求得的MN1值取值范围在19 693~215 623,MN2值取值范围在768~954,Ⅰ类原油的MN2值介于769~919,Ⅱ类原油的MN2值介于768~907,Ⅲ类原油的MN2值介于906~954,Ⅳ类原油的MN2值介于774~817。在同一原油族群内,Manco数与原油密度、黏度、非烃和沥青质含量均呈现良好的正相关性。优化的Manco法成功厘定了生物降解程度在PM7~PM9+的储层样品,与PM等级评价具有一致性且有着更高的分辨率,它可以区分具有相同PM等级但原油黏度不同的样品,还可以进一步了解样品之间生物降解过程的相对差异。将PM法定性评价和优化Manco法定量评价相结合,可以很好地揭示原油物性的变化,对稠油区的油气勘探具有重要的指导作用。

Reference (23)

Catalog

    Links

    Journal Online

    Contact Us

    • Website Copyright © 2011 Editorial Office of Acta Sedimentologica Sinica
    • Address: 8 Tianshui Middle Road, Lanzhou
    • Post code: 730000   Tel:（0931）8264231
    • 陇ICP备2021001824号-28
    • 甘公网安备 62010202000673号
    Wechat

    Email alert

    RSS

    Supported by: Beijing Renhe Information Technology Co. Ltd  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return