Geologic Exploration

Study on Sedimentary Microfacies Characterization Method in Sparse Well Block with Progressive Extension

  • Nan Jinhao ,
  • Sha Zonglun ,
  • Jia Hongbing ,
  • Liu Shaoran ,
  • Xiong Xiangdong ,
  • Lin Tong
Expand
  • PetroChina Daqing Oilfield Co., Ltd., Daqing, Heilongjiang 163712, China

Received date: 2022-02-14

  Revised date: 2022-09-07

  Online published: 2023-01-10

Abstract

In view of the low degree of well control in the sparse well block around the development area and the great gap between the accuracy of sediment characterization and the existing development area, the differences were analyzed in sandstone thickness and seismic impedance of different sedimentary microfacies, the statistics was made for the sandstone parameters of different sedimentary microfacies in the development area, and the sandstone database was established in correspondence to different microfacies; based on the control range of fan spreading on the plane predicted by seismic attributes, the development characteristics of sedimentary sand bodies in sparse well block characterized by seismic inversion were analyzed by microfacies knowledge base, and the microfacies types of sand bodies were determined; the quantitative characterization of sedimentary microfacies in sparse well block can be implemented by taking the extension range of sand bodies parallel and vertical to sediment origins as microfacies distribution range. The study shows that The development characteristics of sand bodies in different sedimentary microfacies can be effectively characterized by single sand body thickness, cumulative probability, inverse wave impedance and other parameters of braided river delta microfacies in the dense well pattern area of Block A, among which underwater distributary channel and channel mouth bar were obviously advantaged in sandstone parameters. The microfacies characterization method based on the microfacies knowledge base and seismic attribute prediction can effectively improve the accuracy of sedimentary microfacies characterization in the sparse well block, with a coincidence rate up to 91%. The favorable microfacies types in the sparse well block are mainly distributed in Well Blocks A5 and A02. The study results have been applied to the evaluation, deployment and scheme implementation of sparse well block with progressive extension around Block A, and achieved excellent results, with a cumulative production capacity of 2.35×104t and proved reserves of 200×104t. The study results provide strong support for stimulation and stable production of old oilfields.

Cite this article

Nan Jinhao , Sha Zonglun , Jia Hongbing , Liu Shaoran , Xiong Xiangdong , Lin Tong . Study on Sedimentary Microfacies Characterization Method in Sparse Well Block with Progressive Extension[J]. Special Oil & Gas Reservoirs, 2022 , 29(6) : 56 -64 . DOI: 10.3969/j.issn.1006-6535.2022.06.007

References

[1] 陈欢庆,张虎俊,隋宇豪.油田开发中后期精细油藏描述研究内容特征[J].中国石油勘探,2018,23(3):115-128.
CHEN Huanqing,ZHANG Hujun,SUI Yuhao.Research characteristics of fine reservoir description in middle and late oilfield development[J].China Petroleum Exploration,2018,23(3):115-128.
[2] 陈欢庆.中国石油精细油藏描述进展与展望[J].中国地质,2021,48(2):424-446.
CHEN Huanqing.Progress in the fine description of reservoirs in China and its prospect[J].Geology in China,2021,48(2):424-446.
[3] 胡光明,何幼斌,李积永,等.滨浅湖单一坝沉积微相精细刻画方法——以柴达木盆地扎11井区N21Ⅳ-10小层为例[J].断块油气田,2020,27(2):171-175.
HU Guangming,HE Youbin,LI Jiyong,et al.Detailed description of single bar sedimentary microfacies in shore and shallow lake:a case of N21Ⅳ-10 individual reservoir in Zha 11 Wellblock in Qaidam Basin[J].Fault-Block Oil & Gas Field,2020,27(2):171-175.
[4] 尹艳树,吴胜和,张昌民,等.用多种随机建模方法综合预测储层微相[J].石油学报,2006,27(2):68-71.
YIN Yanshu,WU Shenghe,ZHANG Changmin,et al.Integrative prediction of microfacies with multiple stochastic modeling methods[J].Acta Petrolei Sinica,2006,27(2):68-71.
[5] 陈婷婷,胡望水,李相明,等.从密井网区到探评井区沉积微相平面图的编制[J].断块油气田,2014,21(5):545-549.
CHEN Tingting,HU Wangshui,LI Xiangming,et al.Drawing of sedimentary microfacies plane map from dense pattern to exploration assessment well areas[J].Fault-Block Oil & Gas Field,2014,21(5):545-549.
[6] 刘超,赵春明,廖新武,等.海上油田大井距条件下曲流河储层内部构型精细解剖及应用分析[J].中国海上油气,2014,26(1):58-64.
LIU Chao,ZHAO Chunming,LIAO Xinwu,et al.The complex fluvial-facies oil reservoirspredominated by meandering river sediments arequite[J].China Offshore Oil and Gas,2014,26(1):58-64.
[7] WEI Feng,XUE Guoqing,XIONG Cong,et al.Facies-controlled reservoirs classification and comprehensive evaluation in sparse well areas combined with well-seismic—taking the Pearl River Formation of the WC-A Oilfield in the Pearl River Mouth Basin as an example[J].Journal of Oil and Gas Technology,2020,42(2):17-26.
[8] 王华,马时刚,文鑫,等.海上油田沉积微相精细刻画方法——以珠江口盆地E油田为例[J].大庆石油地质与开发,2022,41(2):122-130.
WANG Hua,MA Shigang,WEN Xin,et al.Fine characterization of sedimentary microfacies in offshore oilfield:take Oilfield E in Pearl River Mouth Basin as an example[J].Petroleum Geology & Oilfield Development in Daqing,2022,41(2):122-130.
[9] 蒙启安,吴海波,李军辉,等.陆相断陷湖盆斜坡区类型划分及油气富集规律——以海拉尔盆地乌尔逊-贝尔凹陷为例[J].大庆石油地质与开发,2019,38(5):59-68.
MENG Qi'an,WU Haibo,LI Junhui,et al.Type classification of the slope area in the continental faulted lake basin and the hydrocarbon enrichment characteristics:taking Wuerxun-Beier Sag in Hailar Basin as an example[J].Petroleum Geology & Oilfield Development in Daqing,2019,38(5):59-68.
[10] 吴海波,李军辉,刘赫.海拉尔盆地乌尔逊-贝尔凹陷层序构成样式及油气成藏模式[J].岩性油气藏,2015,27(5):155-160.
WU Haibo,LI Junhui,LIU He.Sequence architecture pattern and hydrocarbon accumulation model of Lower Cretaceous in Wuerxun-Beier Depression,Hailaer Basin[J].Lithologic Reservoirs,2015,27(5):155-160.
[11] 吴海波,李军辉,刘赫.乌尔逊-贝尔凹陷岩性-地层油藏形成条件及分布规律[J].中南大学学报(自然科学版),2015,46(6):2178-2187.
WU Haibo,LI Junhui,LIU He.Formation condition and distribution rule of lithologic and stratigraphic reservoirs in Wurxun-Beir Sag[J].Journal of Central South University(Science and Technology),2015,46(6):2178-2187.
[12] 王雅春,张晓玲,袁红旗,等.斜坡带南一段油富集的主控因素分析[J].山东科技大学学报(自然科学版),2012,31(3):1-10.
WANG Yachun,ZHANG Xiaoling,YUAN Hongqi,et al.Dominative factors of oil enrichment in the first sector of Nantun Group in Wudong Slope Zone[J].Journal of Shandong University of Science and Technology(Natural Science),2012,31(3):1-10.
[13] 蔡义峰,熊婷,姚卫江,等.地震多属性分析技术在薄层砂体预测中的应用[J].石油地球物理勘探,2017,52(增刊2):140-145.
CAI Yifeng,XIONG Ting,YAO Weijiang,et al.Thin sandstone prediction with seismic multi-attribute analysis[J].Oil Geophysical Prospecting,2017,52(S2):140-145.
[14] 高世臣,袁照威.地震属性在沉积相预测中的方法研究——序贯随机模式识别[J].地球物理学进展,2016,31(3):1066-1072.
GAO Shichen,YUAN Zhaowei.Seismic attributes in facies prediction—sequential stochastic pattern recognition methods[J].Progress in Geophysics,2016,31(3):1066-1072.
[15] 季敏,王尚旭,陈双全.地震属性优选在油田开发中的应用[J].石油地球物理勘探,2006,41(2):183-187.
JI Min,WANG Shangxu,CHEN Shuangquan.Application of optimum seismic attributes in development of oilfield[J].Oil Geophysical Prospecting,2006,41(2):183-187.
[16] 王彦仓,秦凤启,杜维良,等.地震属性优选、融合探讨[J].中国石油勘探,2013,18(6):69-73.
WANG Yancang,QIN Fengqi,DU Weiliang,et al.Discussions on optimization and fusion of seismic attributes[J].China Petroleum Exploration,2013,18(6):69-73.
[17] 何翠,郭少斌,唐瑾,等.精细构造解释及储层预测技术在轮南地区的应用[J].地球物理学进展,2016,31(3):1111-1116.
HE Cui,GUO Shaobin,TANG Jin,et al.Application of fine structure interpretation and reservoir prediction technology in Lunnan Area[J].Progress in Geophysics,2016,31(3):1111-1116.
[18] 甘利灯,张昕,王峣钧,等.从勘探领域变化看地震储层预测技术现状和发展趋势[J].石油地球物理勘探,2018,53(1):214-225.
GAN Lideng,ZHANG Xin,WANG Yaojun,et al.Current status and development trends of seismic reservoir prediction viewed from the exploration industry[J].Oil Geophysical Prospecting,2018,53(1):214-225.
[19] KUSHWAHA Prabodh Kumar,MAURYA Satya Prakash,RAI Piyush,et al.Estimation of subsurface rock properties from seismic inversion and geo-statistical methods over F3-Block,Netherland[J].Exploration Geophysics,2021,52(3):258-272.
[20] 撒利明,杨午阳,姚逢昌,等.地震反演技术回顾与展望[J].石油地球物理勘探,2015,50(1):184-202.
SA Liming,YANG Wuyang,YAO Fengchang,et al.Past,present,and future of geophysical inversion[J].Oil Geophysical Prospecting,2015,50(1):184-202.
[21] 沈洪涛,郭乃川,秦童,等.地质统计学反演技术在超薄储层预测中的应用[J].地球物理学进展,2017,32(1):248-253.
SHEN Hongtao,GUO Naichuan,QIN Tong,et al.Application of geostatistical inversion for super thin reservoir prediction[J].Progress in Geophysics,2017,32(1):248-253.
Outlines

/