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低孔隙度储层碳氧比测井灵敏度提高方法 被引量:5

A method of improving sensitivity of carbon/oxygen well logging for low porosity formation
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摘要 碳氧比能谱测井技术在确定储层剩余油饱和度及评价水淹层方面得到了广泛应用。为提高碳氧比测井在低孔隙条件下对含油饱和度的响应灵敏度,采用高斯与线性组合模型,拟合实测伽马能谱特征峰获取特征系数,并结合碳、氧元素标准伽马能谱,形成一种碳氧比值计算新方法;通过处理已知组成的混合伽马能谱验证了新方法的准确性。采用蒙特卡罗数值模拟方法建立不同孔隙度及含油饱和度的地层模型,研究低孔隙度储层条件下常规能窗法及新方法计算的碳氧比值与含油饱和度响应关系。结果表明:碳氧比值计算新方法能够减小中子与其他元素作用产生伽马射线对碳氧比值的影响,明显提高低孔隙度条件下碳氧比测井对含油饱和度的响应灵敏度。研究成果为碳氧比测井数据处理方法改进及其在低孔隙度条件下的应用提供了重要技术支持。 Carbon/Oxygen ( C/O) spectral logging technique has been widely used to determine residual oil saturation and the evaluation of water flooded layer. In order to improve the sensitivity of the technique for low-porosity formation, Gaussian and linear models are applied to fit the peaks of measured spectra to obtain the characteristic coefficients. Standard spectra of carbon and oxygen are combined to establish a new carbon/oxygen value calculation method, and the robustness of the new method is cross-validated with known mixed gamma ray spectrum. Formation models for different porosities and saturations are built using Monte Carlo method. The responses of carbon/oxygen which are calculated by conventional energy window method, and the new method is applied to oil saturation under low porosity conditions. The results show the new method can reduce the effects of gamma rays contaminated by the interaction between neutrons and other elements on carbon/oxygen rati-o, and therefore can significantly improve the response sensitivity of carbon/oxygen well logging to oil saturation. The new method improves greatly carbon/oxygen well logging in low porosity conditions.
出处 《中国石油大学学报(自然科学版)》 EI CAS CSCD 北大核心 2016年第6期57-62,共6页 Journal of China University of Petroleum(Edition of Natural Science)
基金 国家自然科学基金项目(41374125) 国家重大油气专项(2011ZX0520-002) 山东省自然科学基金项目(ZR2012DM002) 中石油创新基金项目(2012D-5006-0302) 中央高校基本科研业务费专项(14CX06071A 14CX05011A) 研究生创新工程(YCX2015001)
关键词 核测井 碳氧比能谱测井 蒙特卡罗方法 地层模型 低孔储层 非线性拟合 标准谱 响应灵敏度 nuclear logging carbon/oxygen spectral logging Monte Carlo method formation model low porosity reservoir nonlinearity fitting standard spectra response sensitivity
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