| 基于阵列感应与自然电位联合反演地层水电阻率 |
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| 引用本文： | 李虎,范宜仁,胡云云,邓少贵,孙庆涛.基于阵列感应与自然电位联合反演地层水电阻率[J].地球物理学报,2013,56(2):688-695. |
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| 作者姓名： | 李虎 范宜仁 胡云云 邓少贵 孙庆涛 |
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| 作者单位： | 1. 中国石油大学(华东)地球科学与技术学院, 青岛 266580;
2. 中国石油大学(华东)CNPC测井重点实验室, 青岛 266580 |
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| 基金项目： | 国家自然科学基金项目(41174099);中石油国家重大专项(2011ZX05020-008);中国石油天然气集团公司科学研究与技术开发项目(2011D_4101)资助 |
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| 摘 要： | 原状地层水电阻率是重要的储层参数,也是进行精细储层评价的基础.基于泥浆侵入数值模拟与侵入过程中井周岩石物理特征分析,确定了薄膜电位的产生位置,针对储层高、低侵等不同侵入特征,提出了可适用于包括存在"低阻环"等不同侵入特征时储层电阻率分布的"五参数"地层模型,基于几何因子理论与有限元方法,建立了阵列感应与自然电位测井联合反演算法,实现了地层电阻率参数反演,重构了地层径向电阻率剖面,进而精确求取了地层水电阻率.通过对实际资料处理表明:反演算法稳定可靠,"五参数"模型能很好地表征储层电阻率分布形态,重构储层电阻率剖面,确定薄膜电位产生位置;基于阵列感应与自然电位的联合反演,能精确计算原状地层水电阻率,为储层评价与流体性质识别提供依据.
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| 关 键 词： | 阵列感应 自然电位 " 五参数" 模型 联合反演 地层水电阻率 |
| 收稿时间： | 2012-05-29 |
Joint inversion of HDIL and SP with a five-parameter model for estimation of connate water resistivity |
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| LI Hu
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FAN Yi-Ren
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HU Yun-Yun
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DENG Shao-Gui
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SUN Qing-Tao.Joint inversion of HDIL and SP with a five-parameter model for estimation of connate water resistivity[J].Chinese Journal of Geophysics,2013,56(2):688-695. |
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| Authors: | LI Hu FAN Yi-Ren HU Yun-Yun DENG Shao-Gui SUN Qing-Tao |
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| Institution: | 1. College of Geo-Resources and Information, China University of Petroleum, Qingdao 266580, China;
2. CNPC Key Laboratory for Well Logging, China University of Petroleum, Qingdao 266580, China |
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| Abstract: | Initial water saturation is an important reservoir parameter which is also the basis for reservoir fine evaluation. On the basis of numerical simulation of mud filtrate invasion and analysis of petrophysical characteristics around a borehole during drilling, the generation position of membrane potential is determined. In view of different invasion characteristics, a "five-parameter model" is proposed, which is applicable to different invasion characteristics including reservoir resistivity distribution with "low resistivity annulus". Furthermore, on the basis of geometrical factor theory and the finite element method, a combined inversion algorithm of array induction logging and spontaneous potential is established, and formation resistivity parameters are inverted. In addition, reservoir resistivity profile is reconstructed, thereby formation water resistivity is calculated accurately. The inversion results of field data show that the inversion algorithm is stable and reliable, and the joint inversion of array induction logging and spontaneous potential can well represent the resistivity distribution, reconstruct resistivity profiles and determine the generation position of membrane potential. The combined inversion algorithm based on array induction logging and spontaneous potential can accurately calculate the connate water resistivity and provide evidence for reservoir evaluation and fluid property identification. |
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| Keywords: | Array induction logging Spontaneous potential Five-parameter model Combined inversion Connate water resistivity |
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