| 惠州凹陷新近系K系列海平面变化定量分析及大数据应用展望 |
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| 引用本文： | 李景哲,周永章,张金亮,王树功,丁琳.惠州凹陷新近系K系列海平面变化定量分析及大数据应用展望[J].岩石学报,2018,34(2):372-382. |
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| 作者姓名： | 李景哲 周永章 张金亮 王树功 丁琳 |
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| 作者单位： | 中山大学地球环境与地球资源研究中心, 广州 510275;广东省地质过程与矿产资源探查重点实验室, 广州 510275;北京师范大学地理科学学部, 北京 100875,中山大学地球环境与地球资源研究中心, 广州 510275;广东省地质过程与矿产资源探查重点实验室, 广州 510275;中山大学地球科学与工程学院, 广州 51027,北京师范大学地理科学学部, 北京 100875,中山大学地球环境与地球资源研究中心, 广州 510275;广东省地质过程与矿产资源探查重点实验室, 广州 510275;中山大学地球科学与工程学院, 广州 51027,中海石油(中国)有限公司深圳分公司, 深圳 518067 |
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| 基金项目： | 本文受国家重点研发计划项目（2016YFC0600506）、国家自然科学基金项目（41273040）及高校基本科研业务费中山大学科研助手资助计划联合资助. |
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| 摘 要： | 本文以珠江口盆地惠州凹陷南部为例,对地质历史时期的相对海平面变化进行了定量分析和估算,得到了研究区的相对海平面变化曲线。通过对比分析,INPEFA方法得出的曲线更能代表相对海平面变化。研究区K系列沉积时期,海平面总体是上升的,但上升的速率在不同的位置不尽相同。总体而言,四级层序海侵体系域(TST)的上升速率要稍高于与其相邻的同级别高位体系域(HST)的速率。海平面主要以交替的快速上升(海侵)和缓慢上升(海退)为特点。Fischer方法得出的曲线在本地区不直接反映相对海平面(可容纳空间)变化,但可以指示富砂层段的位置。本文进一步分析认为,可以利用地层的层序结构、分形特性以及离散的地层年龄等数据,依据贝叶斯-拉普拉斯(Bayes-Laplace)原理构建数据驱动的迭代模型,进而从粗略到精细,实现相对海平面在时间域的高精度刻画,为小尺度古环境研究和精细油藏描述提供支撑。
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| 关 键 词： | 地质大数据 贝叶斯-拉普拉斯原理 相对海平面 惠州凹陷南部 INPEFA Fischer图解 智能地质模型 |
| 收稿时间： | 2017/5/23 0:00:00 |
| 修稿时间： | 2017/9/21 0:00:00 |
Eustatic fluctuations of the Neogene K successions of Huizhou Sag: High resolution quantitative analysis and application of Bayes-Laplace principle with big data |
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| LI JingZhe,ZHOU YongZhang,ZHANG JinLiang,WANG ShuGong and DING Lin.Eustatic fluctuations of the Neogene K successions of Huizhou Sag: High resolution quantitative analysis and application of Bayes-Laplace principle with big data[J].Acta Petrologica Sinica,2018,34(2):372-382. |
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| Authors: | LI JingZhe ZHOU YongZhang ZHANG JinLiang WANG ShuGong and DING Lin |
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| Institution: | Center for Earth Environment & Resources, Sun Yat-sen University, Guangzhou 510275, China;Guangdong Provincial Key Laboratory of Mineral Resources and Geological Processes, Guangzhou 510275, China;Department of Geographic Sciences, Beijing Normal University, Beijing 100875, China,Center for Earth Environment & Resources, Sun Yat-sen University, Guangzhou 510275, China;Guangdong Provincial Key Laboratory of Mineral Resources and Geological Processes, Guangzhou 510275, China;School of Earth Sciences & Engineering, Sun Yat-sen University, Guangzhou 51027,Department of Geographic Sciences, Beijing Normal University, Beijing 100875, China,Center for Earth Environment & Resources, Sun Yat-sen University, Guangzhou 510275, China;Guangdong Provincial Key Laboratory of Mineral Resources and Geological Processes, Guangzhou 510275, China;School of Earth Sciences & Engineering, Sun Yat-sen University, Guangzhou 51027 and CNOOC Shenzhen Branch, Shenzhen 518067, China |
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| Abstract: | Taking K successions of the Zhujiang Formation in the southern part of Huizhou Sag as an example, this paper studied the changes of the relative sea levels. On the basis of sequence division, by Fischer plots and maximum entropy spectral analysis methods (INPEFA curve method), the relative sea level changes during the formation of the K successions have been quantitatively estimated and a relative sea level changing curve was acquired. By comparison, it is concluded that the curve based on the INPEFA method is more reliable than that based on the Fischer plot in revealing the relative sea level changes. During the formation of the K successions, the relative sea level kept rising in an overall view, while the rate of rising varied from time to time. In general, the rising rates of Transgressive Systems Tracts (TSTs) are higher than those of Highstand Systems Tracts (HSTs). The relative sea level is characterized by alternatively fast rising (transgression) and slow rising (regression). The curve based on the Fischer plot, in contrast, does not reveal the relative sea level (accommodation) change, while it can indicate the advantageous positions of sand-rich zones. On the basis of the relative sea level curve in depth domain, this paper furtherly proposed a Bayes-Laplace based approach to acquire the relative sea level in geological time domain. This paper aims at proposing an approach for analyzing relative sea level in a high resolution scale, which is supposed to support the small scaled paleoenvironment study and fine reservoir characterization. |
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| Keywords: | Relative sea level Sequence stratigraphy INPEFA Fischer Diagram geological big data Predictable model in time domain Bayes-Laplace principle Intelligent geological model |
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