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天然气勘探与开发 >

2022 , Vol. 45 >Issue 4: 49 - 54

DOI: https://doi.org/10.12055/gaskk.issn.1673-3177.2022.04.006

气田开发

浅海重力流复杂连通气藏实施风险定量评价技术

  • 李佳 ,
  • 叶青 ,
  • 周伟 ,
  • 彭旋
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  • 中海石油（中国）有限公司海南分公司研究院
李佳,女,1990年生,工程师;主要从事天然气开发地质研究工作。地址：（570100）海南省海口市秀英区长滨3路8号。E-mail：lijia11@cnooc.com.cn

修回日期: 2022-10-09

  网络出版日期: 2023-02-06

基金资助

“十三五”国家科技重大专项“莺琼盆地高温高压天然气富集规律与勘探开发关键技术（三期）”（编号：2016ZX05024005）、中海石油（中国）有限公司重大科技专项“南海西部油田上产2000万方关键技术研究”（编号：CNOOC-KJ135ZDXM38ZJ）

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Quantitative assessment on development risks in complex and connected gas reservoirs driven by gravity flow in shallow seas

  • Li Jia ,
  • Ye Qing ,
  • Zhou Wei ,
  • Peng Xuan
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  • Research Institute, CNOOC Hainan Company, Haikou, Hainan 570312, China

Revised date: 2022-10-09

  Online published: 2023-02-06

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摘要

近年来南海西部莺歌海盆地天然气勘探持续在重力流沉积储层中获得新发现,但受限于重力流储层沉积类型特殊、沉积机制及过程复杂,导致开发实施效果一直不好,失利井比例远高于常规油气田,如何高效地定量评价该类储层实施风险一直是地质研究者的研究方向,针对以上问题,笔者在充分消化吸收前人研究成果及勘探实践的基础上,对沉积微相展布、砂体空间刻画以及砂体叠置连通关系的研究成果,结合相邻相似区块或本区已钻砂体的经验和概率统计,并通过参数分类与优选,建立了研究区的风险潜力评价方案与流程,将传统的实施风险分析中各要素通过区域规律结合统计学实现定量化表征,有效指导气田的高效开发。研究结果表明：①储层风险与含气性风险是影响实施的两个关键因素,依托地质基础研究的相关性分析及井点信息归一化处理,能够有效实现储层风险与含气性风险的定量评价;②结合区域动静资料,建立靶区地质油藏数据库,依托不同的数据分析方法,是实现了复杂沉积体储层的高精度表征有效手段之一。

关键词： 复杂连通气藏; 空间刻画; 叠置连通; 概率统计; 参数分类; 风险定量评估; 优化建议; 莺歌海盆地

本文引用格式

李佳 , 叶青 , 周伟 , 彭旋 . 浅海重力流复杂连通气藏实施风险定量评价技术[J]. 天然气勘探与开发, 2022 , 45(4) : 49 -54 . DOI: 10.12055/gaskk.issn.1673-3177.2022.04.006

Abstract

Recently in Yinggehai Basin, western South China Sea, new natural-gas exploration discoveries have continuously emerged from certain reservoirs driven by gravity flow. However, these reservoirs are mostly characterized by exclusive depositional type, and complex mechanism and process during their deposition, resulting in a poor development effect, and much higher proportion of failure wells than that in conventional oil and gasfields. How to efficiently and quantitatively evaluate development risks in such reservoirs has always been one subject. So, the distribution of sedimentary microfacies, and the sandbody’s spatial distribution and superimposed connectivity were investigated on the basis of previous achievements and exploration practices. Combined with experiences and probability statistics on sandbody drilled in adjacent similar blocks or in the study area, both plan and process to evaluate the risk potential were established for the study area through parameter classification and optimization in terms of reservoir and gas-bearing risks. Depending on regional laws and statistics, some elements for analyzing traditional development risks were quantitatively characterized. In addition, a quantitative geological knowledge base was established to obtain high-precision characterization in complex depositional reservoirs. In view of these, a quantitative analysis on risk potential was carried out for four development wells with high risks at the gasfield edge, and many suggestions were made for them. As a result, their success rate reached 75%. These results can further guide an efficient implementing both pre-drilling optimization and development for surrounding gasfields.

Key words： Complex and connected gas reservoir; Spatial characterization; Superimposed connectivity; Probability statistics; Parameter classification; Quantitative risk assessment; Optimal suggestion; Yinggehai Basin

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参考文献

[1] 谢玉洪, 黄保家. 南海莺歌海盆地东方13-1高温高压气田特征与成藏机理[J]. 中国科学, 2014, 44(8): 1731-1739.
Xie Yuhong & Huang Baojia. Characteristics and accumulation mechanisms of the Dongfang 13-1 high temperature and overpressured gas field in the Yinggehai Basin, the South China Sea[J]. Science China Earth Sciences, 2014, 44(8): 1731-1739.
[2] 孟元林, 肖丽华, 杜洪烈, 等. 莺琼盆地主要勘探目的层成岩作用数值模拟及优质储层预测[R]. 大庆: 东北石油大学, 2009.
Meng Yuanlin, Xiao Lihua, Du Honglie, et al.Numerical simulation of diagenesis and prediction of quality reservoir of main exploration targets in Yingqiong Basin[R]. Daqing: Northeast Petroleum University, 2009.
[3] 周伟, 王勇标, 王玉, 等. 莺歌海盆地东方区高温高压气藏气水分布特征及成因[J]. 天然气技术与经济, 2020, 14(5): 20-27.
Zhou Wei, Wang Yongbiao, Wang Yu, et al.Characteristics and geneses of gas-water distribution in high-temperature high-pressure gas reservoirs, Dongfang block, Yinggehai Basin[J]. Natural Gas Technology and Economy, 2020, 14(5): 20-27.
[4] 林承焰, 朱兆群, 刘魁元, 等. 济阳坳陷邵家地区沙四段油气成藏差异性及其定量评价[J]. 地学前缘, 2018, 25(4): 155-167.
Lin Chengyan, Zhu Zhaoqun, Liu Kuiyuan, et al.Quantitative evaluation of hydrocarbon accumulation disparity in the fourth member of the Shahejie Formation in the Shaojia area of the Jiyang depression[J]. Earth Science Frontiers, 2018, 25(4): 155-167.
[5] 覃利娟, 晁彩霞, 李雷, 等. 东方A气田海底扇非均质性储层精细刻画研究[J]. 重庆科技学院学报(自然科学版), 2019, 21(3): 15-19.
Qin Lijuan, Chao Caixia, Li Lei, et al.Precise description of submarine fan with heterogeneity reservoir in Dongfang A gas field[J]. Journal of Chongqing University of Science and Technology (Natural Sciences Edition), 2019, 21(3): 15-19.
[6] 李亚茹, 李华, 杨朝强, 等. 南海莺歌海盆地黄流组海底扇储层构型特征[J]. 古地理学报, 2022, 24(3): 556-567.
Li Yaru, Li Hua, Yang Zhaoqiang, et al.Reservoir architecture of the Huangliu Formation submarine fan in Yinggehai Basin, South China Sea[J]. Journal of Palaeogeography, 2022, 24(3): 556-567.
[7] 吴欣松, 吴胜和, 聂昌谋, 等. 对应分析方法在储集层评价中的应用[J]. 石油勘探与开发, 1999, 26(2): 90-92.
Wu Xinsong, Wu Shenghe, Nie Changmou, et al.Application of correspondence analysis in the evaluation of reservoir beds[J]. Petroleum Exploration and Development, 1999, 26(2): 90-92.
[8] 朱剑兵, 谭明友. 利用支持向量机法预测地震储层厚度的尝试[J]. 大庆石油地质与开发, 2009, 28(1): 34-36.
Zhu Jianbing & Tan Mingyou. Trial on predicting reservoir thickness with support vector machine[J]. Petroleum Geology and Oilfield Development in Daqing, 2009, 28(1): 34-36.
[9] 赵辉, 李阳, 高达, 等. 基于系统分析方法的油藏井间动态连通性研究[J]. 石油学报, 2010, 31(4): 633-636.
Zhao Hui, Li Yang, Gao Da, et al.Research on reservoir interwell dynamic connectivity using systematic analysis method[J]. Acta Petrolei Sinica, 2010, 31(4): 633-636.
[10] 罗晓容, 雷裕红, 张立宽, 等. 油气运移输导层研究及量化表征方法[J]. 石油学报, 2012, 33(3): 428-436.
Luo Xiaorong, Lei Yuhong, Zhang Likuan, et al.Characterization of carrier formation for hydrocarbon migration: Concepts and approaches[J]. Acta Petrolei Sinica, 2012, 33(3): 428-436.
[11] 李少华, 李强, 李君. 影响砂体连通体积因素的定量评价[J]. 天然气地球科学, 2014, 25(5): 643-648.
Li Shaohua, Li Qiang & Li Jun. Quantitative evaluation of the factors controlling the sand body connected volumes[J]. Natural Gas Geoscience, 2014, 25(5): 643-648.
[12] 张伙兰, 裴健翔, 张迎朝, 等. 莺歌海盆地东方区中深层黄流组超压储集层特征[J]. 石油勘探与开发, 2013, 40(3): 284-293.
Zhang Huolan, Pei Jianxiang, Zhang Yingzhao, et al.Overpressure reservoirs in the mid-deep Huangliu Formation of the Dongfang area, Yinggehai Basin, South China Sea[J]. Petroleum Exploration and Development, 2013, 40(3): 284-293.
[13] 易远元. 地震属性分析技术综述[J]. 科技资讯, 2006(10): 211-212.
Yi Yuanyuan.Technologies for analyzing seismic attribute[J]. Science & Technology Information, 2006(10): 211-212.
[14] 阳孝法, 张学伟, 林畅松. 地震地貌学研究新进展[J]. 特种油气藏, 2008, 15(6): 1-5.
Yang Xiaofa, Zhang Xuewei & Lin Changsong. New advances in seismic geomorphology[J]. Special Oil and Gas Reservoirs, 2008, 15(6): 1-5.
[15] 彭小东, 杨朝强, 彭旋, 等. 对水驱气藏采收率的新认识——以南海西部典型水驱气藏为例[J]. 天然气勘探与开发, 2021, 44(2): 36-43.
Peng Xiaodong, Yang Chaoqiang, Peng Xuan, et al.New understanding about recovery in water drive gas reservoirs: Examples from typical ones in western South China Sea[J]. Natural Gas Exploration and Development, 2021, 44(2): 36-43.
[16] 杨朝强, 周伟, 王玉, 等. 莺歌海盆地东方区黄流组一段小层划分及海底扇沉积演化主控因素[J]. 中国海上油气, 2022, 34(1): 55-65.
Yang Zhaoqiang, Zhou Wei, Wang Yu, et al.Subdivision of the first member of Huangliu Formation in Dongfang area of Yinggehai Basin and the main factors controlling the sedimentary evolution of submarine fan[J]. China Offshore Oil and Gas, 2022, 34(1): 55-65.
[17] 岳绍飞, 张辉, 覃利娟, 等. 莺歌海盆地东方区黄流组一段砂质碎屑流沉积模式[J]. 大庆石油地质与开发, 2020, 39(4): 9-18.
Yue Shaofei, Zhang Hui, Qin Lijuan, et al.Sandy debris-flow sedimentary mode in Member 1 of Huangliu Formation in Dongfang area of Yinggehai Basin[J]. Petroleum Geology & Oilfield Development in Daqing, 2020, 39(4): 9-18.
[18] 姜平, 李明军, 周伟, 等. 莺歌海盆地黄流组一段限定—非限定朵体构型及其演化[J]. 地球物理学进展, 2019, 34(6): 2451-2458.
Jiang Ping, Li Mingjun, Zhou Wei, et al.Confined to unconfined: Architecture and evolution of lobes in the member 1 of Huangliu formation, Yinggehai Basin[J]. Progress in Geophysics, 2019, 34(6): 2451-2458.
[19] 陈欢庆, 唐海洋, 吴桐, 等. 精细油藏描述中的大数据技术及其应用[J]. 油气地质与采收率, 2022, 29(1): 11-20.
Chen Huanqing, Tang Haiyang, Wu Tong, et al.Big data technology and its application in fine reservoir description[J]. Petroleum Geology and Recovery Efficiency, 2022, 29(1): 11-20.
[20] 刘合, 李艳春, 金辉, 等. 区块链在石油勘探开发数据共享中的应用[J]. 中国石油大学学报(自然科学版), 2022, 46(2): 1-11.
Liu He, Li Yanchun, Jin Hui, et al.Application of blockchain in petroleum exploration and development data sharing[J]. Journal of China University of Petroleum (Edition of Natural Science), 2022, 46(2): 1-11.
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