| REN Jinfeng,ZHANG Yingzhao,WANG Hua,WANG Yahui,GAN Huajun,HE Weijun,SUN Ming,SONG Guangzeng.Identification methods of coal-bearing source rocks for Yacheng Formation in the western deepwater area of South China Sea[J].Acta Oceanologica Sinica,2015,34(4):19-31 |
| 南海西部深水区崖城组煤系烃源岩的识别方法 |
| Identification methods of coal-bearing source rocks for Yacheng Formation in the western deepwater area of South China Sea |
| 投稿时间：2014-06-21 修订日期：2014-09-28 |
| DOI：10.1007/s13131-015-0647-2 |
| 中文关键词: 琼东南盆地 深水区 煤系烃源岩 地质与地球物理方法 |
| 英文关键词:Qiongdongnan Basin deepwater area coal-bearing source rocks geological and geophysical methods |
| 基金项目: |
| 作者 | 单位 | E-mail | | 任金锋 | 中国地质大学(武汉) 构造与油气资源教育部重点实验室, 武汉 430074
中国地质大学(武汉) 资源学院, 武汉 430074 | | | 张迎朝 | 中海石油(中国)有限公司湛江分公司, 湛江 524057 | | | 王华 | 中国地质大学(武汉) 构造与油气资源教育部重点实验室, 武汉 430074
中国地质大学(武汉) 资源学院, 武汉 430074 | wanghua@cug.edu.cn | | 王亚辉 | 中海石油(中国)有限公司湛江分公司, 湛江 524057 | | | 甘华军 | 中国地质大学(武汉) 资源学院, 武汉 430074 | | | 何卫军 | 中海石油(中国)有限公司湛江分公司, 湛江 524057 | | | 孙鸣 | 广州海洋地质调查局, 广州 510075 | | | 宋广增 | 中国地质大学(武汉) 资源学院, 武汉 430074 | |
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| 中文摘要: |
| 琼东南盆地古近系崖城组海陆过渡相煤系烃源岩已被证实是该盆地的主要气源岩,但由于崖城组煤层具有层数多、单层薄、横向变化快的特点,而难以被识别和预测,尤其是勘探程度较低的深水区.本文利用综合种地质与地球物理法对煤系烃源岩进行更加准确的预测.首先,煤层可通过“三高,三低,一扩”的测井响应特征识别,而炭质泥岩可通过“四高,一低”的特征识别.基于该测井逻辑判断,煤系地层可通过测井曲线的聚类分析进行垂向的自动识别.在井震标的的约束下,煤层组可通过地震数据的“负相位,高吸收因子,低波阻抗和低频”等综合特征进行横向识别.然而,地球物理方法识别的煤系烃源岩分布范围不一定符合成煤的地质规律,因此本文从构造、层序和沉积的角度研究了煤系发育的主控因素约束其分布范围:①古地形及构造沉降控制了海陆过渡相煤系烃源岩在凹陷中的平面发育部位;②相对海平面变化通过控制可容空间变化以及海岸线迁移,从而控制烃源岩的发育规模以及垂向分布——具体的说,可容纳空间的增长速率和泥炭堆积速率的关系是控制煤层形成的最根本因素,在其平衡位置,煤层发育最厚、延伸最大;③原地碎屑的供应和沉积场所与古物源的距离,是制约高丰度烃源岩发育的关键因素,即距离古隆起海岸较近的沉积环境中陆源有机质较为丰富,便可形成高丰度煤系烃源岩.通过上述地质与地球物理联合识别方法,提高了煤系烃源岩发育的预测精度和可信度,为南海西部深水区的早期勘探提供了重要的参考依据. |
| 英文摘要: |
| Owing to the fact that the coal-beds are with the characteristics of multi-beds, thin single-bed, rapid lateral changes and deep burial, coal-bearing source rocks are difficult to be identified and predicted, especially in the lower exploration deepwater area. In this paper, a new integrative process utilizing geology and geophysics is proposed for better predicting the distribution of coal-bearing source rocks. Coal-beds were identified by the logging responses of “three higher, three lower, and one expand” and carbargilite were recognized by the characteristics of “four higher and one lower”. Based on the above logical decision, coal-beds and carbargilite can be distinguished automatically by cluster analysis of logging curves in verticality. Within the constraints of wellseismic calibration, the coal-beds group also can be detected in horizontality by the integrated representation of “negative phase, higher Q, lower impedance and lower frequency” within the seismic data. However, the distribution of coal-bearing source rocks utilizing geophysical methodology may do not conform to the geological rules of coal accumulation. And then the main geological controlling factors of coal accumulation are comprehensively analyzed as follows: (1) Paleotopography and tectonic subsidence determine the planar range of terrestrial-marine transitional facies markedly; (2) The relative sea level changes affect the accommodation space and shoreline migration, and limit the vertical range of coal-beds. More specifically, the relationship between the accommodation creation rate and the peat accumulation rate is a fundamental control on coal accumulation. The thickest and most widespread coals form where those two factors reached a state of balance; (3) The supply of autochthonous clasts and the distance between deposition places and paleovegetation accumulated area are the critical factor to form abundant coal, which means that if deposition area is close to paleouplift, there would be sufficient organic matters to form abundant source rocks. The results show that the integrated methods can significantly improve prediction accuracy of coal-bearing source rocks, which is suitable for early exploration of western deepwater area of South China Sea. |
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