用户名: 密码: 验证码:
少井条件下富生烃凹陷油气资源评价
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
富生烃凹陷对大型油气系统具有控制作用,可以说“没有富生烃凹陷就没有大油田”,因此,富生烃凹陷的油气资源评价一直倍受专家们的重视。富生烃凹陷的形成条件主要包括三方面:长期的非补偿环境(断陷)、丰富的有机质物源(富浮游藻类、富营养水系)和良好的有机质保存条件(贫氧环境),其基本地质特征为:高沉积速率、高生烃强度、异常高压、良好的生储盖组合。基于以上认识可知,富生烃凹陷的资源量应首选成因法来估算。因为成因法能够较好的体现富生烃凹陷中优质烃源岩的生烃、排烃作用、油气运聚效率等成因参数,具有明确地质意义。
     烃源岩TOC (Total Organic Carbon,总有机碳)含量是有机质丰度的重要表征参数,亦是含油气盆地中评价生烃条件和资源潜力的基础。尤其是在生烃凹陷的深凹陷区,一般烃源岩品质较好,但钻井很少,甚至没有,导致烃源岩样品的获取极为困难。此种情况下,欲通过实验直接测定有机碳含量,必然受到烃源岩样品数量和分布的限制,难于满足研究的需要,而且实测数据多分布于洼陷边缘地带,不能有效地揭示洼陷生烃中心的TOC含量及其展布特征,对资源评价有较大的影响。因此,有必要采用烃源岩TOC井-震联合预测技术,通过建立三维的烃源岩TOC数据体,定量预测不同深度和不同时间平面上的烃源岩TOC含量及变化特征,有效地弥补烃源岩取心少、实测样品分布不连续的不足,达到刻画成烃坳陷中烃源岩三维空间展布特征的效果,为烃源岩评价和资源量计算奠定良好的基础。
     烃源岩的产烃率特征也是油气资源评价的一个关键参数,烃源岩热压模拟实验可以有效的获得烃源岩的产烃率,尤其是地层孔隙热压生排烃模拟实验,能够较好的保留原始样品的原始孔隙结构,在实验过程中可以手动的控制温度和压力,赋予其与地质条件相近的地层流体压力和上覆静岩压力,使其更加符合当时的地质背景,得到的实验数据略高于常规高压釜热压生烃模拟实验,更加的准确,提高了资源评价的可信度。
     惠州凹陷位于珠江口盆地珠一坳陷,是已经证实的典型的富生烃凹陷,其主要烃源岩层序为古近系文昌组和恩平组。目前,惠州凹陷虽然有很多钻井,但是大部分钻井的目的层为上部珠海组和珠江组的砂岩储层,仅有很少一部分钻井钻遇古近系上部的恩平组烃源岩,而钻遇古近系下部文昌组烃源岩的钻井仅有几口,也只是钻遇的文昌组顶部地层。基于上述分析可知,对于烃源岩层序来说,惠州凹陷为典型的少井条件下的富生烃凹陷。
     本次研究以惠州凹陷古近系烃源岩为目的层段,采用烃源岩有机碳井-震预测技术和热压模拟实验的方法,确定富生烃凹陷油气资源评价的关键参数,使其更加符合地质背景,然后利用成因法中的有机碳法计算烃源岩的生烃量,并基于排聚系数的分析,计算惠州凹陷恩平组和上、下文昌组烃源岩的油气资源量,为该区的油气资源勘探奠定良好的基础。此外,通过建立烃源指数的地质模型,计算烃源指数,结合油气资源量,提出了富生烃凹陷快速评价的烃源指数分级评价标准。主要取得的成果认识如下:
     (1)惠州凹陷古近系烃源岩的实测地球化学特征显示,下文昌组属于中等烃源岩,上文昌组和恩平组为好烃源岩,且上文昌组烃源岩的品质要优于恩平组。
     惠州凹陷古近系下文昌组烃源岩处于低熟阶段,有机质类型主要为Ⅱ2型,有机碳含量显示为中等烃源岩,上文昌组烃源岩处于低-中熟阶段,有机质类型主要为Ⅱ1-Ⅱ2型,有机碳含量显示为好烃源岩;恩平组烃源岩处于低-中熟阶段,有机质类型主要为Ⅱ2型,有机碳含量显示为好烃源岩。综合分析可知,上文昌组烃源岩的品质最好,其次为恩平组,最后为下文昌组。但是下文昌组实测数据缺乏一定的代表性,因为惠州凹陷钻遇下文昌组的井很少,且钻遇地层均为下文昌组顶部,样品的获取受到极大限制,因此,下文昌组的烃源岩品质还有待于进一步证实。
     (2)惠州凹陷古近系烃源岩TOC测井预测曲线显示,文昌组的TOC明显高于恩平组,说明文昌组的烃源岩品质高于恩平组。
     烃源岩TOC含量与电阻率、声波时差、中子孔隙度、自然伽马呈正相关性,而与密度呈负相关性。基于这种响应关系分别建立了文昌组和恩平组2种烃源岩TOC测井预测模型,预测了8口典型钻井文昌组和恩平组的烃源岩TOC曲线。在有实测TOC数据的井段,TOC预测曲线与实测TOC数据的拟合效果较好,说明该方法具有可行性。综合分析多口钻井的TOC预测曲线可知,文昌组的TOC明显高于恩平组,说明文昌组的烃源岩品质高于恩平组。
     (3)采用了烃源岩有机碳井-震联合预测技术,以测井信息为桥梁,获得烃源岩的有机碳含量与三维地震属性之间的响应关系,建立一个三维的烃源岩TOC数据体,显示生烃凹陷中不同深度和不同时间平面上的烃源岩有机碳含量及三维空间展布特征。
     该技术首先利用五种测井参数来定量预测单井的烃源岩TOC曲线;之后以TOC曲线为目标曲线,运用STRATA软件中的EMERGE模块提取与对应深度的TOC值相关性较好的振幅包络、绝对振幅积分、平均频率、瞬时相位、波阻抗等多种地震属性,建立TOC与多种地震属性之间的拟合关系;再基于拟合关系和三维地震数据体建立TOC的三维数据体。通过TOC三维数据体的深度与时间切片,可以显示不同深度和不同时间平面上的TOC含量变化特征,弥补了烃源岩取心少、实测样品分布不连续的不足;并依此获得烃源岩的有效厚度和分布范围。该技术与之前的技术相比,具有较大的优势,首先是利用了振幅包络、绝对振幅积分、平均频率、瞬时相位、波阻抗等多种地震属性,其次是不只达到了TOC的定量预测,而且还可以预测烃源岩的有效厚度、分布范围。
     (4)通过对惠州凹陷烃源岩TOC的三维数据体的分析可知,下文昌组的烃源岩品质要优于上文昌组和恩平组,生烃潜力最大,且文昌组有效烃源岩的累积厚度和成熟度明显高于恩平组。
     惠州凹陷烃源岩TOC的三维数据体,刻画了TOC在三维空间内的展布特征,主要三级层序PSQ2、PSO3、PSQ4、PSQ6、PSQ9、PSQ10的烃源岩TOC分布图显示,文昌组的有机碳含量明显普遍高于恩平组,下文昌组的TOC含量大部分在2.5%~3.5%以上,上文昌组的TOC含量大部分在2%~3%左右,而恩平组的TOC含量则以1.5%-2.5%为主,说明下文昌组的烃源岩品质要优于上文昌组和恩平组,生烃潜力最大。此外,惠州凹陷主要三级层序PSQ2、PSQ3、PSQ4、PSQ6、PSQ9、PSQ10的烃源岩有效厚度和成熟度的分布图显示,上、下文昌组有效烃源岩的累积厚度和成熟度明显高于恩平组。
     (5)惠州凹陷恩平组和上、下文昌组的烃源岩产烃率特征显示,上文昌组的产烃率最高,生烃潜力最大,而恩平组和下文昌组次之。
     该结果与烃源岩的实测地球化学特征类似,同样是限于下文昌组烃源岩样品的数量,不能有效的反映下文昌组的产烃率特征,在计算生烃量时宜用上文昌组的产烃率代表上、下文昌组的产烃率。此外,最好选用地层孔隙热压生排烃模拟实验来获得产烃率特征,该实验能够较好的保留原始样品的原始孔隙结构,在实验过程中可以手动的控制温度和压力,赋予其与地质条件相近的地层流体压力和上覆静岩压力,使其更加符合当时的地质背景,得到的实验数据略高于常规高压釜热压生烃模拟实验,更加准确,提高了资源评价的可信度。
     (6)基于烃源岩有机碳井-震联合预测技术和热压模拟实验,采用成因法对少井条件下的富生烃凹陷进行油气资源评价。
     富生烃凹陷的油气资源量主要取决于烃源岩的品质,宜采用成因法来进行油气资源评价。对于少井条件下的富生烃凹陷来说,可以采用烃源岩有机碳井-震联合预测技术来预测烃源岩TOC的三维展布特征,弥补烃源岩取心少、实测样品分布不连续的不足。在用热压模拟实验获得烃源岩的产烃率特征时,应优先选用地层孔隙热压生排烃模拟实验,得到的数据更加准确,以提高资源评价的可信度。此外,这种基于成因法、烃源岩有机碳井-震联合预测技术、热压模拟实验对少井条件下富生烃凹陷进行油气资源评价的方法,还可应用于盆地的早期勘探,因为钻井比较少,利用该方法进行早期的油气资源评价可以为以后的勘探部署服务。
     (7)富生烃洼陷是构成富生烃凹陷的基础,其资源评价对整个富生烃凹陷的油气资源评价和勘探潜力分析具有重要的指导作用。
     富生烃凹陷通常具有多个生烃中心,发育多个富生烃洼陷,而富生烃凹陷主要是受生烃的控制,其油气资源量的大小与其发育的富生烃洼陷的资源量具有密切的关系,因此,富生烃洼陷的油气资源评价对整个富生烃凹陷的油气资源评价和勘探潜力分析具有重要的指导作用。以富生烃凹陷惠州凹陷为例,其油气资源总量约70.3404×108t,主要由多个富生烃洼陷的资源量构成,其中HZ26洼的资源量最大,占油气资源总量的14.179%。此外,与HZ26洼紧邻的两个下古近系构造转换带XJ30-HZ26和HZ26-HZ22,具备了近源供烃的优势,对惠州凹陷的油气勘探起到了指导作用。
     (8)建立了富生烃凹陷的烃源指数地质模型,确定了富生烃凹陷的烃源指数分级评价标准,可用于富生烃凹陷的快速评价。
     富生烃凹陷油气资源评价的基础可以说是烃源条件的综合评价,而常规的评价方法从数据采集到实验分析投入大、周期长,而且综合性不强。烃源指数能够通过多种烃源条件的综合分析,快速有效地评价富生烃凹陷。基于富生烃凹陷的面积、最大厚度、沉积相、有机质类型、最大深度、门限深度等基础性参数,建立了富生烃凹陷的烃源指数地质模型,并依此模型计算烃源指数,确定富生烃凹陷的烃源指数分级评价标准。通过该标准,可以粗略的评价烃源岩的优劣和资源量的大小,因其涉及的参数容易获取,尤其适于在勘探程度较低的地区推广应用。
A large petroleum system is controlled by the hydrocarbon-rich generation depression, which can be considered that "no hydrocarbon-rich generation depression, no large oil field". Therefore, the evaluation of the petroleum resources in the hydrocarbon-rich generation depression has always been much accounted by the experts. The forming conditions of the hydrocarbon-rich generation depression include three aspects:the long-term non-compensation environment (rift), the abundant organic matter provenance (rich in the phytoplankton and the nutrition water) and the favorable preservation conditions of the organic matter (oxygen-poor environment). Then the fundamental geological features are high deposition rate, high hydrocarbon generation intensity, anomaly overpressure, and favorable source-reservoir-cap assemblage. Based on the above understanding, the resources of the hydrocarbon-rich generation depression should be estimated by the genetic method. Because the genetic method can reflect efficiently the genetic parameters of the excellent source rocks of the hydrocarbon generation expulsion, migration and accumulation in the hydrocarbon-rich generation depression, which has the clear geological significances.
     The organic carbon content of the source rock is the characterization parameters of the abundance of organic matter, and is the base of the evaluation of hydrocarbon generation condition and resource potential in the petroliferous basin. Especially in the deep depression zone of the hydrocarbon generation depressions, the quality of the source rock is generally good with the less drilling or no drilling, which leads to the acquisition of the source rock samples difficultly. In such a case, the organic carbon content will be restricted by the number and distribution of the source rock samples, which is difficult to meet the needs of the research. The measured data distribute in the marginal zone of the depression generally, which can not reveal the organic carbon content and the distribution characteristics in the center of the hydrocarbon-rich generation depression effectively, affecting the resource evaluation greatly. Therefore, it is necessary to use the drilling-seismic prediction technology of the source rock TOC. Through the establishment of the TOC3D data volume, the TOC contents and the distribution characteristics are predicted quantitatively in the3D space in the different depths and different time planes, which makes up the deficiencies of the less coring and the discontinuous distribution of the measured sample, characterizes the distribution characteristics of the source rock in the3D space, and lays a good foundation for the evaluation of the source rock and the calculation of the resources.
     The characteristic of the hydrocarbon generation rate is also a very important parameter of the resource evaluation, which can be got from the thermo compression simulation experiment. The thermo compression simulation experiment with the formation pore can reserve the original pore structure of the original sample, and the temperature and pressure can be manually controlled giving the similar formation fluid pressure and the overlying rock pressure with the geological conditions, which are more consistent with the prevailing geological background. The experimental data is slightly higher than the data from the thermo compression simulation experiment with the conventional autoclave, but it is more accurate and improves the credibility of the resource evaluation.
     The Huizhou Depression is a proven typical hydrocarbon-rich generation depression located in the Zhu Yi Depression, Pearl River Mouth Basin. The mainly source rocks are the Paleogene Wenchang and Enping Formations. Although there are many wells in the Huizhou Depression, but the target layers of most of the wells are the above sandstone reservoirs. There are only a fraction of wells drilling the Enping Formation and a few wells drilling the top stratum of the Wenchang Formation. Based on the above analysis, the Huizhou Depression is the typical hydrocarbon-rich generation depression with sparse wells for the source sequence.
     Using the drilling-seismic prediction technology of the source rock organic carbon and the thermo compression simulation experiments, the key parameters of the petroleum resources evaluation for the target stratum of the Paleogene source rocks in the Huizhou Depression are optimized to consistent with the geological background in the research. Then the hydrocarbon generation amount of the source rock is calculated by the genetic method. The amount of the petroleum resources is calculated in the Huizhou Depression based on the migration and accumulation coefficient, which lays a good foundation for the exploration of the petroleum resources. In addition, through the establishment of the geological model of the hydrocarbon source index, combined with conventional petroleum resources, the grading evaluation criterion of the hydrocarbon source index for the fast evaluation of the hydrocarbon-rich generation depression is presented, which is convenient for the fast evaluation of the resource potential of the source rock in the hydrocarbon-rich generation depression. The mainly achievements as follows:
     (1) The measured geochemical characteristics of the Paleogene source rock in the Huizhou Depression show that the Lower Wenchang Formation is regarded as a medium source rock, the Upper Wenchang and Enping Formations are regarded as good source rocks, and the quality of the source rock of the Upper Wenchang Formation is superior to that of the Enping Formation.
     The Lower Wenchang Formation is regarded as a medium source rock by the TOC with the low maturity and the organic matter type Ⅱ2. The Upper Wenchang Formation is regarded as a good source rock by the TOC with the low-medium maturity and the organic matter type Ⅱ1~ Ⅱ2. The Enping Formation is regarded as a good source rock by the TOC with the low-medium maturity and the organic matter type Ⅱ2. It is analyzed comprehensively that the quality of the source rocks of the Upper Wenchang Formation is the best, then that of the Enping Formation, and that of the Lower Wenchang Formation in the last. But the measured data of the Lower Wenchang Formation is lack of the certain representativeness. Because there are less drillings in the Lower Wenchang Formation of the Huizhou Depression, and the drilled strata are the top of the Lower Wenchang Formation, which lead to the acquisition of the source rock samples difficultly. So the quality of the Lower Wenchang Formation need to be further confirmed.
     (2) The predicted logging curves of the TOC of the Paleogene source rock in the Huizhou Depression show that the TOC of the Wenchang Formation is significantly higher than that of the Enping Formation, which illustrates that the quality of the source rock of the Wenchang Formation is superior to that of the Enping Formation.
     There is a positive correlation between TOC and the resistivity, acoustic, neutron porosity, natural gamma, and there is a negative correlation between TOC and density. Two predicted logging models of the Wenchang and Enping Formations are established based on the the response relationships, and the TOC curves of the the Wenchang and Enping Formations for eight typical drillings are predicted. The predicted TOC curves fit well with the measured TOC data, which illustrates that this method is feasible. Based on the comprehensive analysis of the TOC curves, the TOC of the Wenchang Formation is higher than that of the Enping Formation, which illustrates that the quality of the source rock of the Wenchang Formation is superior to that of the Enping Formation.
     (3) The drilling-seismic prediction technology of the source rock TOC is adopted with the bridge of the logging information, which gives a response relationship between the TOC and3D seismic attributes. The TOC3D data volume established shows the TOC contents and the distribution characteristics in the3D space in the different depths and different time planes of the hydrocarbon generation depression.
     In this technology, the TOC curves is predicted quantitatively by five logging parameters firstly; then the fitting relationship between TOC and many seismic attributes such as amplitude envelope, absolute amplitude integral average frequency, instantaneous phase, wave impedance; the TOC3D data volume is established based on the fitting relationship and3D data volume at last. The TOC distribution characteristics can be showed by the depth and time slices of the TOC3D data volume, which makes up the deficiencies of the less coring and the discontinuous distribution of the measured sample, and can give the thickness and the distribution range of the source rock. Compared with the previous technology, this technology has greater advantages. Fistly, many seismic attributes are used; secondly, not only the TOC contents are predicted quantitatively, but also the thickness and the distribution range of the source rock are predicted.
     (4) Through the analysis of the TOC3D data volume of the Huizhou Depression, the quality of the source rock of the Lower Wenchang Formation is superior to that of the Upper and Enping Formations, and the hydrocarbon generation potential of the Lower Wenchang Formation is the largest. The thickness and maturity of the effective source rock of the Wenchang Formation are bigger than that of the Enping Formation.
     The TOC3D data volume of the Huizhou Depression shows the distribution characteristics of the TOC in the3D space. The TOC distribution maps of the third-order sequences of the PSQ2, PSQ3, PSQ4, PSQ6, PSQ9, PSQ10sequences show that the TOC contents of the Upper and Lower Wenchang Formations are obviously higher than that of the Enping Formation. The quality of the Lower Wenchang Formation with the TOC contents ranged mainly from2.5%to3.5%is superior to that of the Upper Wenchang Formation with the TOC contents ranged mainly from2%to3%and the Enping Formation with the TOC contents ranged mainly ranged from1.5%to2.5%, which illustrates that the Lower Wenchang Formation has a largest hydrocarbon generation potential. In addition, The thickness and maturity distribution maps of the third-order sequences of the PSQ2, PSQ3, PSQ4, PSQ6, PSQ9, PSQ10sequences show that the thickness and maturity of the Upper and Lower Wenchang Formations are obviously higher than that of the Enping Formation.
     (5) The characteristics of hydrocarbon generation rate of the Enping, Upper and Lower Wenchang Formations in the Huizhou Depression show that the hydrocarbon generation rate and the hydrocarbon generation potential of the Upper Wenchang Formation are the highest, followed by that of the Enping and Lower Wenchang Formation.
     The results are similar to the measured geochemical characteristics of source rocks limited to the number of the source rock samples of the Lower Wenchang Formation, which can not reflect the characteristics of the hydrocarbon generation rate of the Lower Wenchang Formation. So the characteristics of the hydrocarbon generation rate of the Upper Wenchang Formation should be used in the calculation of the amount of the hydrocarbon generation on behalf of that of the Upper and Lower Wenchang Formations. In addition, the best selection is the thermo compression simulation experiment with the formation pore. The experiment can reserve the original pore structure of the original sample, and the temperature and pressure can be manually controlled giving the similar formation fluid pressure and the overlying rock pressure with the geological conditions, which are more consistent with the prevailing geological background. The experimental data is slightly higher than the data from the thermo compression simulation experiment with the conventional autoclave, but it is more accurate and improves the credibility of the resource evaluation.
     (6) Based on the drilling-seismic prediction technology of the source rock TOC and the thermo compression simulation experiment, the genetic method is used in the hydrocarbon-rich generation depression with sparse wells.
     The amount of petroleum resources mainly depends on the quality of the source rocks, so the genetic method is appropriate to use in the evaluation of the petroleum resources. The drilling-seismic prediction technology of the source rock TOC can make up the deficiencies of the less coring and the discontinuous distribution of the measured sample in the hydrocarbon-rich generation depression with sparse wells. The thermo compression simulation experiment with the formation pore should be preferred, which is more accurate and improves the credibility of the resource evaluation. In addition, the method of the petroleum evaluation based on the genetic method, the drilling-seismic prediction technology of the source rock TOC and the thermo compression simulation experiment in the hydrocarbon-rich generation depression with sparse wells can also be applied in the early exploration of the basin. Because of sparse wells, the early evaluation of petroleum resources can serve for the future exploration by this method.
     (7) The hydrocarbon-rich generation sags are the base of the formation of the hydrocarbon-rich generation depression. The petroleum resources evaluation of the hydrocarbon-rich generation sags have an important guiding role in the petroleum resources evaluation and exploration potential analysis of the hydrocarbon-rich generation depression.
     There are generally many hydrocarbon generation centers in the hydrocarbon-rich generation depression developing many hydrocarbon-rich generation sags. The hydrocarbon-rich generation depression is mainly controlled by the hydrocarbon generation, and the amount of the petroleum resources has a close relationship with the petroleum resources of the hydrocarbon-rich generation sags. So the petroleum resources evaluation of the hydrocarbon-rich generation sags have an important role in the petroleum resources evaluation and exploration potential analysis of the hydrocarbon-rich generation depression. For the case of the hydrocarbon-rich generation depression of the Huizhou Depression, the amount of the total petroleum resources with the total petroleum resources are about70.3404×108t, which are formed by the petroleum resources of many hydrocarbon-rich generation sags. The resources of the HZ26Sag are the largest, representing14.179%of the total resources. In addition, Two lower Paleogene tectonic transfer zones of the XJ30-HZ26and HZ26-HZ22close the HZ26Sag have the good advantage of the nearly source for hydrocarbon, which has a guiding role in the petroleum exploration of the Huizhou Depression.
     (8) The geological model of the hydrocarbon source index is established, and the grading evaluation criterion of the hydrocarbon source index for the hydrocarbon-rich generation depression is established, which can be used to fast evaluate the hydrocarbon-rich generation depression.
     The comprehensive evaluation of the source rock conditions is the base of the petroleum evaluation of the hydrocarbon-rich generation depression. The conventional evaluation methods from data acquisition to the experimental analysis have large investment, long cycle and weak comprehensiveness. The hydrocarbon source index can fast evaluate the hydrocarbon-rich generation depression through the comprehensive analysis of several source rock conditions. Based on the area, maximum thickness, facies, organic matter type, maximum depth, threshold depth and other basic parameters of the hydrocarbon-rich generation depression, the geological model of the hydrocarbon source index is established, the hydrocarbon source indexes are calculated, and the grading evaluation criterion of the hydrocarbon source index for the hydrocarbon-rich generation depression is confirmed. The quality of the source rock and the petroleum resources can be evaluated roughly by this criterion. Because the involved parameters are easy to access, especially, the criterion suit to use in the low level exploration areas.
引文
[1]胡朝元.生油区控制油气田分布一一中国东部陆相盆地进行区域勘探的有效理论[J].石油学报,1982,3(2):9-13.
    [2]龚再升,等.中国近海大油气田[M].北京:石油工业出版社,1997.
    [3]袁选俊,谯汉生.渤海湾盆地富油气凹陷隐蔽油气藏勘探[J].石油与天然气地质,2002,23(2):130-133.
    [4]赵文智,邹才能,汪泽成,等.富油气凹陷“满凹含油”论——内涵与意义[J].石油勘探与开发,2004,31(2):5-13.
    [5]Perrodon A. Dynamics of Oil and Gas Accumulations:Bulletin Des Centres de Recherches Exploration [M]. Aquitaine:Production Elf, Memoir 5,1983.
    [6]李思田.大型油气系统形成的盆地动力学背景[J].地球科学——中国地质大学学报,2004,29(5):505-512.
    [7]卢双舫,付广,王朋岩.天然气富集主控因素的定量研究[M].北京:石油工业出版社,2002,14-30.
    [8]赵旭东.石油资源定量评价[M].北京:地质出版社,1988.
    [9]金之钧,B.M.施比伊曼,等.油气资源定量评价系统[J].地质论评,1996,42(增刊):247-258.
    [10]金之钧,张金川.油气资源评价方法的基本原则[J].石油学报,2002,23(1):19-23.
    [11]D.D.赖斯.油气评价方法与应用[M].翟光明等译.北京:石油工业出版社,1992.
    [12]Lee P J, Wang P C. Prediction of oil or gas pool sizes when discovery record is available [J]. Mathematical Geology,1985,17(2):95-113.
    [13]徐春华,徐佑德,邱连贵,等.油气资源评价的现状与发展趋势[J].海洋石油,2001,21(4):1-5.
    [14]武守诚.油气资源评价导论[M].北京:石油工业出版社,2005.
    [15]赵文智,胡素云,沈成喜,等.油气资源评价方法研究新进展[J].石油学报,2005,26(增刊):25-29.
    [16]国土资源部油气资源战略研究中心.全国石油天然气资源评价[M].北京:中国大地出版社,2010.
    [17]Lawrence J D, John H S. The evolution and use of discovery process models at the U.S. geological survey [J].APPG Bulletin,1993,77(3):467-478.
    [18]Lee P J, Wang P C C. Evaluation of petroleum resources from Pool size distributions [J]. AAPG Special Volumes,1986, SG21:33-42.
    [19]Tissot B P, Welte D H. Petroleum formation and occurrence [M]. New York:Springer Verlag, 1978.
    [20]周总瑛,白森舒,何宏.成因法与统计法油气资源评价对比分析[J].石油实验地质,2005,27(1):67-73.
    [21]石广仁.油气盆地数值模拟方法[M].第二版.北京:石油工业出版社,1999.
    [22]石广仁,李阿梅,张庆春.盆地模拟技术新进展(一)——国内外发展状况[J].石油勘探与开发,1997,24(3):38-40.
    [23]张庆春,石广仁,田在艺.盆地模拟技术的发展现状与未来展望[J].石油实验地质,2001,23(3):312-317.
    [24]Barker R A, Gehman H M, James W R, et al. Geologic field number and size assessments of oil and gas Plays [J]. AAPG Bulletin,1984,68(4):426-432.
    [25]Ulmishek G. Stratigraphic aspects of Petroleum resource assessment. Oil and Gas Assessment-Methods and Application [J]. AAPG Studiesin Geology,1986,21:59-68.
    [26]Magoon L B. The Petroleum system-a classification scheme for research, resource assessment, and exploration (abs) [J]. AAPG Bulletin,1987,71(5):587.
    [27]Weeks L G. Concerning estimates of potential petroleum reserves [J]. AAPG Bulletin,1950, 34(8):1947-1953.
    [28]Price L C. Basin richness and source rock disruption:a fundamental relationship [J]. Journal of Petroleum Geology,1994,17(1):5-38.
    [29]Hunt J M. Petroleum Geochemistry and Geology [M]. San Francisco, Freeman and Company Press,1979.
    [30]Barker C. Pyrolysis Techniques for Source Rock Evaluation [J]. AAPG Bulletin,1974,58(2): 267-294.
    [31]黄第藩.二十一世纪初油气地球化学面临的任务和展望[J].沉积学报,2001,19(1):1-6.
    [32]朱光有,金强.烃源岩的非均质性及其研究——以东营凹陷牛38井为例[J].石油学报,2002,23(5):34-39.
    [33]Beers R F. Radioactivity and organic content of some Paleozoic shales [J]. AAPG Bulletin, 1945,29(1):1-22.
    [34]Swanson V E. Oil yield and uranium content of blank shales [M]. USGS Professional Paper 356-A. Reston, Virginia:USGS,1960:1-44.
    [35]Fertl W H, Rieke H H. Gammaray spectral evaluation techniques identify fractured shale reservoirs and source rock characteristics [J]. Journal of Petroleum Technology,1980,31(11): 2053-2062.
    [36]Schmoker J W. Determination of organic matter content of Appalachian Devonian shale from Gammaray logs [J]. AAPG Bulletin,1981,65(7):1285-1298.
    [37]谭廷栋.测井识别生油岩方法[J].测井技术,1988,12(6):1-12.
    [38]Hertzog R, Colson L, Seeman O, et al. Geochemical logging with spectrometry tools [J]. SPE Formation Evaluation,1989,4(2):153-162.
    [39]Schmoker J W. Determination of organic content of Appalachian Devonian shales from formation density logs [J]. AAPG Bulletin,1979,63(9):1505-1537.
    [40]Schmoker J W, Hester T C. Organic carbon in Bakken formation-United States Portion of Willist on Basin [J]. AAPG Bulletin,1983,67(12):2165-2174.
    [41]Autric A. Resistivity, radioactivity and sonic transit time logs to evaluate the organic content of low permeability rocks [J]. The Log Analyst,1985,26(3):36-45.
    [42]Hussain F A. Source rock identification in the state of Kuwait using wireline logs [J]. SPE Formation Evaluation,1987,2:477-488.
    [43]Meyer B L, Nederlof M H. Identification of source rocks on wireline logs by density/resistivity and sonic transit time/resistivity crossplots [J]. AAPG Bulletin,1984, 68(2):121-129.
    [44]赵彦超.生油岩测井评价的理论和实践:以南阳、泌阳凹陷为例[J].地球科学:中国地质大学学报,1990,15(1):65-74.
    [45]Mendelson J D, Toksoz M N. Source rock characterization using multivariate analysis of log data. SPWLA 26th Annual Logging Symposium [C]. Texas:Society of Petrophysicists and Well-Log Analysts,1985.
    [46]Fertl W H, Chilingar G V.Total organic carbon content determined from well logs [J]. SPE Formation Evaluation,1988,3(2):407-419.
    [47]Kamel M H, Mabrouk W M. Estimation of shale volume using a combination of the three porosity logs [J]. Journal of Petroleum Science and Engineering,2003,40(3-4):145-157.
    [48]徐思煌,朱义清.烃源岩有机碳含量的测井响应特征与定量预测模型——以珠江口盆地文昌组烃源岩为例[J].石油实验地质,2010,32(3):290-295.
    [49]Passey Q R, Creaney S, Kulla J B, et al. A practical model for organic richness from porosity and resisitivty logs [J]. AAPG Bulletin,1990,74(12):1777-1794.
    [50]许晓宏,黄海平,卢松年.测井资料与烃源岩有机碳含量的定量关系研究[J].江汉石油学院学报,1998,20(3):8-12.
    [51]张志伟,张龙海.测井评价烃源岩的方法及其应用效果[J].石油勘探与开发,2000,27(3):85-87.
    [52]朱振宇,刘洪,李幼铭..△logR技术在烃源岩识别中的应用与分析[J].地球物理学进展,2003,18(4):647-649.
    [53]Kamali M R, Mirshady A A. Total organic carbon content determined from well logs using △logR and neuro fuzzy techniques [J]. Journal of Petroleum Science and Engineering,2004, 45(3-4):141-148.
    [54]霍秋立,曾花森,付丽,等△logR测井源岩评价方法的改进及其在松辽盆地的应用[J].吉林大学学报(地球科学版),2011,41(2):586-591.
    [55]Huang Z, Williamson M A, Fowler M G, et al. Predicted and measured petrophysical and geochemical characteristics of the Egret Member oil source rock, Jeanne d'Arc Basin, Offshore Eastern Canada [J]. Marine and Petroleum Geology,1994,11(3):295-306.
    [56]Huang Z, Williamson M A. Artificial neural network modelling as an aid to source rock characterization [J]. Marine and Petroleum Geology,1996,13(2):227-290.
    [57]Ali K I, Rezaee M R, Hossain R B. A committee neural network for prediction of normalized oil content from well log data:An example from South Pars Gas Field, Persian Gulf [J]. Journal of Petroleum Science and Engineering,2009,65(1-2):23-32.
    [58]Patterson C D, Quarlesa C A, Breyerb J A. Possible new well-logging tool using positron Doppler broadening to detect total organic carbon (TOC in hydrocarbon source rocks [J]. Radiation Physics and Chemistry,2003,68:523-526.
    [59]Dale G.S.著,范维尚译.用地震资料外推测井曲线[J].石油地球物理勘探,1982,5:14-26.
    [60]李在光,杨占龙,刘俊田等.多属性综合方法预测含油气性及其效果[J].天然气地球科学,2006,17(5):727-730.
    [61]吴光大,刘正楷,魏嘉等.柴达木盆地红柳泉地区地震资料岩性处理及储层横向预测[J].石油物探,1992,31(3):36-45.
    [62]罗寿兵,曾庆,涂涛等.四川盆地米仓山东端-大巴山西段前缘构造建模及地震资料构造解释[J].天然气勘探与开发,2007,30(1):16-19.
    [63]郑晓东,朱明,何敏等.珠江口盆地白云凹陷荔湾深水扇砂体分布预测[J].石油勘探与开发,2007,34(5):529-533.
    [64]于建国,韩文功,于正军等.济阳拗陷孔店组烃源岩的地震预测方法[J].石油地球物理勘探,2005,40(3):318-321.
    [65]米立军,刘震,张功成等.南海北部深水区白云凹陷古近系烃源岩的早期预测[J].沉积学报,2007,25(1):139-145.
    [66]张寒,朱光有.利用地震和测井信息预测和评价烃源岩-以渤海湾盆地富油凹陷为例[J].石油勘探与开发,2007,34(1):55-59.
    [67]王志宏,罗霞李景坤,等.松辽盆地北部深层有效烃源岩分布预测.天然气地球科学[J],2008,19(2):204-209.
    [68]刘震,常迈,赵阳等.低勘探程度盆地烃源岩早期预测方法研究[J].地学前缘,2007,14(4):159-167.
    [69]赵胜,刘磊.基于地震资料的烃源岩早期评价研究[J].石油天然气学报,2007,29(5):76-79.
    [70]曹强,叶加仁.南黄海北部盆地东北凹陷烃源岩的早期预测[J].地质科技情报,2008,27(4):75-79.
    [71]曹强,叶加仁,石万忠.地震属性法在南黄海北部盆地勘探新区烃源岩厚度预测中的应用[J].海洋地质与第四纪地质,2008,25(8):109-114.
    [72]顾礼敬,徐守余,苏劲,等.利用地震资料预测和评价烃源岩[J].天然气地球科学,2011,22(3):554-560.
    [73]潘仁芳,徐乾承.地震反演预测页岩有机质成熟度的研究[J].长江大学学报(自然科学版),2011,8(2):29-31.
    [74]L(?)seth, H., Wensaas, L., Gading, M. et al. Can hydrocarbon source rocks be identified on seismic data [J]. Geology,2011,39(12):1167-1170.
    [75]中国地质大学(武汉).南海东部海域已证实的富烃凹陷再评价及新领域勘探方向[R].广州:中海石油(中国)有限公司深圳分公司,2010.
    [76]Powell T G. An assessment of the hydrocarbon source potential of the Canadian Arcticisland [R]. Geological Survey of Canada Paper,1978,78:12.
    [77]Tissot B P. Recent advances in petroleum geochemistry applied to hydrocarbon exploration [J]. AAPG Bull,1984,68(5):545-563.
    [78]傅家谟,盛国英,刘德汉.煤成烃地球化学[M].北京:石油工业出版社,1990:182-327.
    [79]程克明.吐哈盆地油气生成[M].北京:石油工业出版社,1994:37-58.
    [80]黄第藩,秦匡宗,王铁冠,等.煤成油的形成和成烃机理[M].北京:石油工业出版社,1995:265-267.
    [81]高岗.油气生成模拟方法及其石油地质意义[J].天然气地球科学,2000,11(2):25-29.
    [82]刘德汉,张惠之,戴金星,等.煤岩显微组分的成烃实验研究与评价[J].科学通报,2000,45(4):346-352.
    [83]姜正龙,罗霞,李剑,等.不同地质条件下各种类型气源岩气态烃产率的求取[J].沉积学报,2004,22:84-90.
    [84]卢双舫,黄第藩.煤成烃的生成和运移的模拟实验研究[J].石油实验地质,1994,16(3):290-302.
    [85]梅廉夫,徐思煌.江汉盆地王场地区泥岩储层裂缝演化及其模拟[J].地球科学,1995,21(3):256-263.
    [86]金强.有效烃源岩的重要性及其研究[J].油气地质与采收率,2001,8(1):1-4.
    [87]Bertrand P, Lallier V E, Boussafir M. Enhancement of Accumulation and Anoxic Degradation of Organic Matter Controlled by Cyclic Productivity:a Model [J]. Organic Geochemistry,1993,22:511-520.
    [88]Derenne S, Largeau C, Brukner W A. Origin of Variations in Organic Matter Abundance and Composition in a Lithologically Homogeneous Maar-type Oil Shale Deposit [J]. Organic Geochemistry,2000,31:787-798.
    [89]Lewan M D,Winters J C, McDonald J H. Generation of oil-like pyrolyzates from organic-rich shales [J]. Science,1979,203:897-899.
    [90]姚伯初,万玲,刘振湖.南海海域新生代沉积盆地构造演化的动力学特征及其油气资源.地球科学——中国地质大学学报,2004,29(5):543-549.
    [91]Sun, Zhen, Zhou, Di, Sun, Longtao, et al. Dynamic analysis on rifting stage of Pearl River Mouth Basin through analogue modeling. Journal of Earth Science,2010,21(4):439-454.
    [92]施和生,朱俊章,姜正龙,等.珠江口盆地珠一坳陷油气资源再评价[J].中国海上油气,2009,21(1):9-14.
    [93]杜家元,施和生,丁琳,等.惠州凹陷油气成藏期次划分及其勘探意义.中国海上油气,2009,21(4):221-226.
    [94]Kata, B J. Factors controlling the development of the lacustrine petroleum source rocks-an update. In:Huc A Y (Eds.) Paleogeography, Paleoclimate and Source Rocks [J]. The American Assiociation of Petroleum Geologista, Tusa, Oklahoma, U. S. A.,1995,61-79.
    [95]Tappn H, Loeblich A R. Geobiologic implication of fossil phytoplankton evolution and time-space distribution. In:Kosanke R and Cross A T (Eds.) Symposium on Palynology of the Late Cretaceous and Early Tertiary [J]. Special Paper-Geological Society of America, 1971,127:247-340.
    [96]Tappn H, Loeblich A R. Evolution of the oceanic plankton [J]. Earth-Science Reviews, 1973,9:207-240.
    [97]宋之琛,黎文本,何承泉,等.中国白垩纪何第三纪孢粉植物群和有机盐分布[J].中国科学,1983,2:168-176.
    [98]叶得泉,钟筱春,姚益民,等.中国油气区第三系(Ⅰ)总论[M].北京:石油工业出版社,1993.
    [99]何承全.化石沟鞭藻类与石油的重要关系[J].古生物学报,1984,18(2):171-188.
    [100]Peniguel G, Couderc R, Seyve D. Microalgae-their impotance in stratigraphy and petroleum exploration [J]. Bull. Centres Rech. Explor.-Prod. Elf -aquitaine,1989,13(2): 455-482.
    [101]朱神照.微古生物化石丰度[J].石油学报,1992,13(2):83-91.
    [102]茅绍智等.河南早第三纪陆相沟鞭藻及其他浮藻类与油气勘探[M].武汉:中国地质大学出版社,1995.
    [103]Lewen M D. Stable carbon isotopes of amorphous kerogens from Phanerozoic sedimentary rocks [J].Geochica et Cosmochimicaacta,1986,50,1583-1591.
    [104]朱伟林.中国近海新生代含油气盆地古湖泊学与烃源条件[M].北京:地质出版社,2009.
    [105]贾铁飞,张卫国,俞立中,等.近800年来巢湖沉积物营养元素富集特点及其环境演变意义[J].地理科学,2009,29(6):893-899.
    [106]谢先军,凌文黎.中国东部中-新生代玄武质火山岩的主量元素地球化学特征[J].矿物岩石地球化学通报,2005,24(2):171-177.
    [107]Bachraty C, Legendre P and Desbruyeres D. Biogeographic relationships among deep-sea hydrothermal vent faunas at global scale [J]. Deep Sea Research Part I,2009,56: 1371-1378.
    [108]周怀阳,李江涛,彭晓彤.海底热液活动与生命起源[J].自然杂志,2009,31(4):207-212.
    [109]Talbot M R. The origins of lacustrine oil source rocks:evidence from the lakes of tropical Africa. In:Fleet A J, Kelts K and Talbot M R (Eds), Lacustrine Petroleum Source Rocks [J]. Geological Society Special Publication, London,1988,40:29-43.
    [110]汪品先,刘传联.含油盆地古湖泊学研究方法[M].北京:海洋出版社,1993.
    [111]胡见义,黄第藩,徐树宝,等.中国陆相石油地质理论基础[M].北京:石油工业出版社,1991.
    [112]李松峰,徐思煌,施和生,等.珠江口盆地惠州凹陷古近系烃源岩特征及资源预测[J].地球科学——中国地质大学学报,2013,38(1):112-120.
    [113]陈敬轶,王飞宇,刘晓.东海平湖油气田烃源岩特征与油气生成[J].地质科技情报,2010,29(6):80-83,100.
    [114]侯读杰,张林晔.实用油气地球化学图鉴[M].北京:石油工业出版社,2003.
    [115]洪有密.测井原理与综合解释[M].东营:石油大学出版社,1993.
    [116]Meissner F F. Petroleum geology of the Bakken formation Williston basin, North Dakota and Montana, in the economic geology of the Williston basin:Montana Geological Society [J]. Williston Basin Symposium,1978,207-227.
    [117]李慧莉,金之钧,何治亮,等.海相烃源岩二次生烃热模拟实验研究[J].科学通报,2007,52(11):1322-1328.
    [118]郑伦举,秦建中,何生,等.地层孔隙热压生排烃模拟实验初步研究[J].石油实验地质,2009,31(3):296-302,306.
    [119]傅家谟,刘德汉.碳酸盐岩有机质演化特征与油气评价[J].石油学报,1982,3(1):1-9.
    [120]Jones R W. Comparison of carbonate and shale source rocks//Palacas J G. Petroleum Geochemistry and Source Rock Potential of Carbonate Rocks [J]. AAPG Studies in Geology, 1984,18:163-180.
    [121]张厚福.石油地质学新进展[J].石油与天然气地质,1992,13(3):351-354.
    [122]程克明,王兆云,钟宁宁,等.碳酸盐岩油气生成理论与实践[M].北京:石油工业出版社,1996.
    [123]梁狄刚,张水昌,张宝民,等.从塔里木盆地看中国海相生油问题[J].地学前缘,2000,7(4):534-547.
    [124]卢双舫,薛海涛,钟宁宁.地史过程中烃源岩有机质丰度和生烃潜力变化的模拟计算[J].地质论评,2003,49(3):292-297.
    [125]秦建中,郑伦举,腾格尔.海相高演化烃源岩总有机碳恢复系数研究[J].地球科学——中国地质大学学报,2007,32(6):853-860.
    [126]邬立言,顾信章,盛志伟.生油岩热解快速定量评价[M].北京:科学出版社,1986.
    [127]郝石生,高岗,王飞宇.高过成熟海相烃源岩[M].北京:石油工业出版社,1996.
    [128]张辉,彭平安.烃源岩有机碳含量恢复探讨[J].地球化学,2011,40(1):56-62.
    [129]崔鹏.烃源岩有机质丰度恢复方法综述[J].断块油气田,2007,14(5):15-17.
    [130]Ungerer P, Pelet R. Extrapolation of kinetics of oil and gas formation from laboratory experiments to sedimentary basins [J]. Nature,1987,327:52-54.
    [131]秦建中.中国烃源岩[M].北京:科学出版社,2005.
    [132]向奎.塔里木盆地西南边缘压扭构造体系及其石油地质意义[J].古地理学报,2006,8(2):233-240.
    [133]张永刚,汤良杰,金文正,等.龙门山构造转换带对油气成藏的控制作用[J].中国石油大学学报(自然科学版),2009,33(5):30-35.
    [134]李友川,陶维祥,孙玉梅,等.珠江口盆地惠州凹陷及其邻区原油分类和布特征[J].石油学报,2009,30(6):830-834,842.
    [135]郝石生.我国有机地球化学的发展与瞻望[J].沉积学报,1997,15(2):1-5.
    [136]Sachse V F, Delvaux D, Littke R. Petrological and geochemical investigations of potential source rocks of the central Congo Basin, Democratic Republic of Congo [J]. AAPG Bulletin, 2012,96(2):245-275.
    [137]李贤庆,熊波,马安来,等.有机岩石学在油气勘探评价中的应用进展[J].江汉石油学院学报,2002,24(1):15-19.
    [138]Dembicki H Jr. Three common source rock evaluation errors made byt geologists during prospect or play appraisals [J]. AAPG Bulletin,2009,93(3):341-356.
    [139]曾溅辉,郑和荣,王宁.东营凹陷岩性油气藏成藏动力学特征[J].石油与天然气地质,1998,19(4):60-63.
    [140]朱光有,金强.东营凹陷两套优质烃源岩层地质地球化学特征研究[J].沉积学报,2003,21(3):506-512.
    [141]姜福杰,姜振学,庞雄奇.东营凹陷油气成藏体系的划分及定量评价[J].地球科学(中国地质大学学报),2008,33(5):651-660.
    [142]陈云林.论富油洼陷及其意义[J].勘探家,1999,4(2):8-11.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700