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EP-A油田岩石分类及储层流动单元研究 被引量:2

Research on Rock Classification and Reservoir Flow Units for EP-A Oilfield
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摘要 储层流动单元划分对认识油藏的非均质性、注水开发效果和剩余油分布规律研究提供了有效手段。EP-A油田处于开发初期,存在两个问题有待解决:一是没有明确的孔渗关系,如果使用单一的孔渗关系计算渗透率,储层非均质性会被忽略,开发过程中历史拟合和开发指标预测也会受到影响;二是如何将岩石分类结果运用在三维地质模型中。本次研究运用岩心观察和实验数据进行岩石类型精细划分,共分为三类,每一类岩石类型给予相应的孔渗关系,并运用相应的孔渗关系计算渗透率,解决了储层非均质性无法准确表征渗透率的难题。在取心井上建立岩石类型与电性特征的关系,采用神经网络方法运用到非取心井中,进而运用到三维地质模型中,通过流动带指数(FZI指数)进行流动单元划分,从而有利于动态历史拟合,使下一步调整井的开发指标预测更加合理,降低了潜在开发风险。 Reservoir flow unit division provides an effective means for understanding reservoir heterogeneity,waterflooding effect and remaining oil distribution rule.EP-A Oilfield is in the early development period.There are two problems to be solved.One is that there is no clear porosity-permeability relationship.If single porosi-ty-permeability relationship is used to calculate permeability,the reservoir heterogeneity will be neglected,and history matching and development index forecast will be affected in the development process.The other is that how to apply rock classification results to three-dimensional geological model.In this study,core observation and experimental data were applied to detailed classification on rock types.Three types were divided.Each rock type has corresponding porosity-permeability relationship,which is used to calculate the permeability.This method solved the difficulty of accurate permeability characterization by the reservoir heterogeneity.The relationship be-tween rock types and electrical characteristics was established for the cored wells.The neural network method was applied to non-cored wells,and then to the three-dimensional geological model.The flow units were di-vided by flow zone index( FZI), which is beneficial to dynamic history match and will make the develop-ment index forecast of the adjustment wells more reasonable and reduce the potential development risk.
作者 刘登丽 谢明英 涂志勇 施征南 Liu Dengli;Xie Mingying;Tu Zhiyong;Shi Zhengncin(CNOOC Shenzhen Company, Shenzhen Guangdong 518000)
出处 《中外能源》 CAS 2019年第5期40-46,共7页 Sino-Global Energy
关键词 岩石分类 神经网络 FZI 指数 流动单元 rock classification neural network FZI flow units
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  • 1袁彩萍,姚光庆,徐思煌,周锋德.油气储层流动单元研究综述[J].地质科技情报,2006,25(4):21-26. 被引量:55
  • 2董春梅,林承焰,赵海朋,袁新涛,车京虎.基于流动单元的测井储层参数解释模型[J].测井技术,2006,30(5):425-428. 被引量:18
  • 3Hearn C L, Ebanks Jr W J, Ranganath V. Geological factors influencing reservoir performance of the Hartzog Draw field,Wyoming[J]. JPT, Aug 1984,1335-1344.
  • 4Lucia F J. Rock-fabric/petrophysical classification of carbonate pore space for reservoir characterization[J]. AAPG, 1995, 79(9): 1275-1300.
  • 5Guangming Ti, Ogbe D O, Hatzignation D G. Use of flow units as a tool for reservoir description: A case study [A]. SPE 26919, 1993.
  • 6H Scott Hamlin, et al. Depositional controls on reservoir prope rties in a braid delta sandstone, Tirrawarra Oil Field, South Australia[J]. AAPG, 1996, 80(2) :139-156.
  • 7Amaefule J O, Altunbay M. Enhanced reservoir description: Using core and log data to identify hydraulic (flow) units and predict permeability in uncored intervals/well[A]. SPE 26436, 1993.
  • 8Canas J A, et al. Characterization of flow units in sandstone reservoirs: La Cira Field, Colombia, South America[A]. SPE 27732, 1994.
  • 9Maghsood Abbaszaden, Hikari Fujii, Fujio Fujimoto. Permeability prediction by hydraulic flow units--theory and applications[A]. SPE 30156, 1996.
  • 10Rincones J G, Delgado R, Ohen H, et al. Effective petrophysical fracture characterization using the flow unit concept- San Juan reservoir, Orocual Field, Venezuela[A]. SPE 63072, 2000.

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