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国土资源遥感  2020, Vol. 32 Issue (1): 209-215    DOI: 10.6046/gtzyyg.2020.01.28
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基于InSAR形变的辽河油田曙光采油厂储层参数反演
杨崇1,刘国祥1,2(),于冰3,张波1,张瑞1,2,王晓文1
1. 西南交通大学地球科学与环境工程学院,成都 610031
2. 高速铁路运营安全空间信息技术国家地方联合工程实验室,成都 610031
3. 西南石油大学土木工程与建筑学院,成都 610500
Inversion of reservoir parameters in Shuguang Oil Production Plant of the Liaohe Oilfield based on InSAR deformation
Chong YANG1,Guoxiang LIU1,2(),Bing YU3,Bo ZHANG1,Rui ZHANG1,2,Xiaowen WANG1
1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
2. State-Province Joint Engineering Laboratory of Spatial Information Technology of High-Speed Railway Safety, Chengdu 610031, China
3. School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China
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摘要 

对油田储层参数及开采量进行反演,可以及时掌握油田的储层状态及开采量变化,有效监控储层的健康和安全。目前国内对于油田储层参数反演的研究较少。以辽河油田最大的采油厂——曙光采油厂为研究对象,采用2007年1月—2010年9月的21景L波段ALOS/PALSAR数据,使用StaMPS (stanford method for persistent scatterers)技术提取该区域的形变结果,并以此为观测量,分别使用Mogi模型和椭球模型对储层参数进行反演和分析,并与经典的Okada模型的反演结果进行对比。结果表明: ①曙光采油厂沉降显著,监测周期内最大沉降速率高达-189.6 mm/a,最大累积沉降量约为750 mm,沉降面积约为28 km 2; ②与Okada模型和Mogi模型相比,椭球模型反演的储层深度精度最高,且模拟的形变结果与观测形变结果最吻合,说明椭球模型的反演结果更可靠,更适用于该油田储层参数的反演。本研究可为InSAR油田沉降监测及储层参数反演提供科学参考。

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杨崇
刘国祥
于冰
张波
张瑞
王晓文
关键词 油田沉降StaMPS技术Mogi模型椭球模型储层参数反演    
Abstract

The inversion of reservoir parameters and production for the oil field can grasp reservoir status and production changes in time and effectively monitor reservoir health and safety. At present, the study of reservoir parameter inversion is very insufficient in China. The authors chose Shuguang Oil Production Plant, the largest oil production plant in the Liaohe Oilfield, as the research object. Using 21 L-band ALOS/PALSAR data obtained from January 2007 to September 2010, the authors employed StaMPS to extract deformation results. Based on these deformation results, the authors used Mogi model and Finite Prolate Spheroidal model to invert and analyze reservoir parameters respectively, with the inversion results compared with those of Okada model. The results are as follows: ① The subsidence of Shuguang Oil Production Plant is remarkable. The maximum subsidence rate is -189.6 mm/year, the maximum cumulative subsidence is about 750 mm, and the subsidence area is about 28 km 2. ② Compared with Okada model and Mogi model, Finite Prolate Spheroidal model has the highest accuracy of reservoir depth inversion, and the simulated deformation results are in the best agreement with the observed deformation results, which shows that the inversion results of Finite Prolate Spheroidal model are more reliable and more suitable for the inversion of reservoir parameters in this oilfield. This study can provide scientific reference for InSAR subsidence monitoring and reservoir parameter inversion in the oilfield.

Key wordsoilfield subsidence    StaMPS    Mogi model    Finite Prolate Spheroidal model    inversion of reservoir parameters
收稿日期: 2019-03-01      出版日期: 2020-03-14
ZTFLH:  TP79  
基金资助:国家自然科学基金青年科学基金项目“基于卫星升降轨时序DInSAR的塔里木油田沉降监测及储层状态参数反演”(编号: 41801399);测绘遥感信息工程国家重点实验室资助课题“基于星载SAR干涉的克拉玛依油田时序二维形变监测及储层参数反演”(编号: 18E01);油气藏地质及开发工程国家重点实验室(西南石油大学)资助项目“多卫星平台MT-DInSAR克拉玛依油田沉降监测及储层地质力学参数动态反演”(编号: PLN201815);国家重点研发计划项目“星载新体制SAR综合环境监测技术”(编号: 2017YFB0502700);国家自然科学基金面上项目“基于卫星升降轨X/C/L波段SAR影像监测贡嘎山冰川分布及其动态演变”(编号: 41771402);国家自然科学基金青年科学基金项目“基于GBInSAR与GNSS的特大型滑坡监测与反演方法”(编号: 41601503);四川省科技支撑计划应用基础面上项目“基于卫星—地基SAR遥感的四川省山区滑坡隐患调查与高危滑坡监测预警”(编号: 2018JY0564);“星载多平台升降轨时序差分雷达干涉滑坡三维形变监测及预测”(编号: 2018JY0138)
通讯作者: 刘国祥     E-mail: rsgxliu@swjtu.edu.cn
作者简介: 杨 崇(1993-),男,硕士,主要从事InSAR及油田储层参数反演研究。Email: swjtu_yc@163.com。
引用本文:   
杨崇,刘国祥,于冰,张波,张瑞,王晓文. 基于InSAR形变的辽河油田曙光采油厂储层参数反演[J]. 国土资源遥感, 2020, 32(1): 209-215.
Chong YANG,Guoxiang LIU,Bing YU,Bo ZHANG,Rui ZHANG,Xiaowen WANG. Inversion of reservoir parameters in Shuguang Oil Production Plant of the Liaohe Oilfield based on InSAR deformation. Remote Sensing for Land & Resources, 2020, 32(1): 209-215.
链接本文:  
http://www.gtzyyg.com/CN/10.6046/gtzyyg.2020.01.28      或      http://www.gtzyyg.com/CN/Y2020/V32/I1/209
Fig.1  研究区域范围
序号 成像时间 格式 序号 成像时间 格式
1 2007-01-31 FBS 12 2009-02-05 FBS
2 2007-06-18 FBD 13 2009-05-08 FBS
3 2007-08-03 FBD 14 2009-08-08 FBD
4 2007-09-18 FBD 15 2009-09-23 FBD
5 2007-11-03 FBS 16 2009-12-24 FBS
6 2007-12-19 FBS 17 2010-02-08 FBS
7 2008-02-03 FBS 18 2010-03-26 FBS
8 2008-03-20 FBS 19 2010-05-11 FBD
9 2008-05-05 FBD 20 2010-06-26 FBD
10 2008-06-20 FBD 21 2010-09-26 FBD
11 2008-12-21 FBS
Tab.1  PALSAR影像参数
Fig.2  StaMPS数据处理流程
Fig.3  干涉时空基线分布
Fig.4  研究区沉降速率
Fig.5  时间序列累积沉降
Fig.6  观测形变、模拟形变和残差结果对比
Fig.7  残差分布直方图
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