Yingchun Zhang, W. Xu, Jingyun Zou, Z. Jing, L. Fang, Jun Liu
{"title":"乌干达阿尔伯特盆地北部复杂碎屑岩储层饱和高度函数与岩石类型耦合","authors":"Yingchun Zhang, W. Xu, Jingyun Zou, Z. Jing, L. Fang, Jun Liu","doi":"10.2118/195853-ms","DOIUrl":null,"url":null,"abstract":"\n In complex clastic reservoirs, deviation often exists in oil saturation derived from logging interpretation due to the borehole conditions and log quality. Especially in thin-sand reservoirs, oil saturation is generally lower than actual results because of boundary effect. An innovative approach of saturation height function coupled with rocktype is provided to improve the accuracy of saturation prediction in well logs and spatial distribution. The model results are compared with log derived results.\n The new approach is based on the routine and special core analysis of over 100 core samples from the complex clastic reservoir in the north of Albert Basin in Uganda. Discrete rocktypes (DRT) are determined by flow zone index and pore throat radius which indicate the fluid flows. After converting the capillary pressure (Pc) data to reservoir conditions, Lambda curve fitting (Sw = A * PcB + C) is used to fit each capillary pressure curve. Then, a robust relationship between the fitting coefficients (A, B, C) and rock properties (i.e. porosity and permeability) is expressed as a nonlinear function for each DRT. Combined with the height above free water level, a water saturation (Sw) model is constructed by SHF within DRT model.\n Using the porosity and permeability obtainedfrom routine core analysis, FZI and pore throat radius are calculated (e.g., by Winland function). Five different rocktypes (DRT1-5) are defined in the delta sand reservoir in the north of Albert Basin with distinct pore textures. The distinguishment is in accordance with the shape of capillary pressure curve, that is, the flow capability increases from DRT1 to DRT5. A strong correlation between Pc and Sw processed by Lambda curve is acquired for each core sample. Meanwhile, 3 coefficients A, B and C can be obtained in Lambda formula. By nonlinear regression, coherent relation between each factor and reservoir properties (porosity and permeability) for each DRT are obtained. Height above the free water level is estimated by geometrical modeling on the oil water contact. The Sw model is constructed by the new SHF function coupled with DRT model. It showed that the water saturation derived from SHF is highly consistent with log derived results and NMR results. Moreover, it provides more precise results in thinner sands and in spatial distribution.\n Based on the identified different rocktype, a new SHF derived from capillary pressure data is utilized to establish the relationship between saturation, the height above the free water level and rock properties. The approach can significantly improve the accuracy of saturation prediction of thin reservoir and reasonably depict the spatial distribution characteristics of saturation. Furthermore, the approach will provide a more precise result in hydrocarbon volume calculation and numerical simulation.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Saturation Height Function Coupled with Rocktype in Complex Clastic Reservoir in the North of Albert Basin, Uganda\",\"authors\":\"Yingchun Zhang, W. Xu, Jingyun Zou, Z. Jing, L. Fang, Jun Liu\",\"doi\":\"10.2118/195853-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n In complex clastic reservoirs, deviation often exists in oil saturation derived from logging interpretation due to the borehole conditions and log quality. Especially in thin-sand reservoirs, oil saturation is generally lower than actual results because of boundary effect. An innovative approach of saturation height function coupled with rocktype is provided to improve the accuracy of saturation prediction in well logs and spatial distribution. The model results are compared with log derived results.\\n The new approach is based on the routine and special core analysis of over 100 core samples from the complex clastic reservoir in the north of Albert Basin in Uganda. Discrete rocktypes (DRT) are determined by flow zone index and pore throat radius which indicate the fluid flows. After converting the capillary pressure (Pc) data to reservoir conditions, Lambda curve fitting (Sw = A * PcB + C) is used to fit each capillary pressure curve. Then, a robust relationship between the fitting coefficients (A, B, C) and rock properties (i.e. porosity and permeability) is expressed as a nonlinear function for each DRT. Combined with the height above free water level, a water saturation (Sw) model is constructed by SHF within DRT model.\\n Using the porosity and permeability obtainedfrom routine core analysis, FZI and pore throat radius are calculated (e.g., by Winland function). Five different rocktypes (DRT1-5) are defined in the delta sand reservoir in the north of Albert Basin with distinct pore textures. The distinguishment is in accordance with the shape of capillary pressure curve, that is, the flow capability increases from DRT1 to DRT5. A strong correlation between Pc and Sw processed by Lambda curve is acquired for each core sample. Meanwhile, 3 coefficients A, B and C can be obtained in Lambda formula. By nonlinear regression, coherent relation between each factor and reservoir properties (porosity and permeability) for each DRT are obtained. Height above the free water level is estimated by geometrical modeling on the oil water contact. The Sw model is constructed by the new SHF function coupled with DRT model. It showed that the water saturation derived from SHF is highly consistent with log derived results and NMR results. Moreover, it provides more precise results in thinner sands and in spatial distribution.\\n Based on the identified different rocktype, a new SHF derived from capillary pressure data is utilized to establish the relationship between saturation, the height above the free water level and rock properties. The approach can significantly improve the accuracy of saturation prediction of thin reservoir and reasonably depict the spatial distribution characteristics of saturation. 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引用次数: 0
摘要
在复杂碎屑岩储层中,由于井眼条件和测井质量的影响,测井解释含油饱和度往往存在偏差。特别是在薄砂油藏中,由于边界效应的影响,含油饱和度普遍低于实际结果。提出了一种结合岩石类型的饱和高度函数的创新方法,提高了测井曲线和空间分布的饱和度预测精度。将模型结果与对数推导结果进行了比较。新方法是基于对乌干达阿尔伯特盆地北部复杂碎屑储层100多个岩心样本的常规和特殊岩心分析。离散岩石类型(DRT)由指示流体流动的流区指数和孔喉半径决定。将毛管压力(Pc)数据转换为储层条件后,采用Lambda曲线拟合(Sw = A * PcB + C)拟合各毛管压力曲线。然后,拟合系数(a, B, C)与岩石性质(即孔隙度和渗透率)之间的鲁棒关系被表示为每个DRT的非线性函数。结合自由水位以上高度,利用DRT模型中的SHF构造了含水饱和度(Sw)模型。利用常规岩心分析得到的孔隙度和渗透率,计算FZI和孔喉半径(如采用Winland函数)。阿尔伯特盆地北部三角洲砂岩储层划分出5种不同的岩石类型(DRT1-5),孔隙结构各异。这种区别与毛管压力曲线的形状一致,即从DRT1到DRT5,流动能力增加。对每个岩心样品进行Lambda曲线处理,得到了Pc与Sw之间较强的相关性。同时在Lambda公式中可以得到3个系数A、B、C。通过非线性回归,得到各因素与各DRT储层物性(孔隙度和渗透率)之间的相干关系。通过油水接触面的几何建模来估计自由水位以上的高度。该模型由新的SHF函数与DRT模型耦合而成。结果表明,深水场计算的含水饱和度与测井结果和核磁共振结果高度一致。此外,在较薄的砂层和空间分布上,它提供了更精确的结果。在确定不同岩石类型的基础上,利用毛管压力数据推导出新的SHF,建立了饱和度、自由水位以上高度与岩石性质之间的关系。该方法可显著提高薄层储层饱和度预测的精度,合理刻画储层饱和度的空间分布特征。此外,该方法将为油气体积计算和数值模拟提供更精确的结果。
Saturation Height Function Coupled with Rocktype in Complex Clastic Reservoir in the North of Albert Basin, Uganda
In complex clastic reservoirs, deviation often exists in oil saturation derived from logging interpretation due to the borehole conditions and log quality. Especially in thin-sand reservoirs, oil saturation is generally lower than actual results because of boundary effect. An innovative approach of saturation height function coupled with rocktype is provided to improve the accuracy of saturation prediction in well logs and spatial distribution. The model results are compared with log derived results.
The new approach is based on the routine and special core analysis of over 100 core samples from the complex clastic reservoir in the north of Albert Basin in Uganda. Discrete rocktypes (DRT) are determined by flow zone index and pore throat radius which indicate the fluid flows. After converting the capillary pressure (Pc) data to reservoir conditions, Lambda curve fitting (Sw = A * PcB + C) is used to fit each capillary pressure curve. Then, a robust relationship between the fitting coefficients (A, B, C) and rock properties (i.e. porosity and permeability) is expressed as a nonlinear function for each DRT. Combined with the height above free water level, a water saturation (Sw) model is constructed by SHF within DRT model.
Using the porosity and permeability obtainedfrom routine core analysis, FZI and pore throat radius are calculated (e.g., by Winland function). Five different rocktypes (DRT1-5) are defined in the delta sand reservoir in the north of Albert Basin with distinct pore textures. The distinguishment is in accordance with the shape of capillary pressure curve, that is, the flow capability increases from DRT1 to DRT5. A strong correlation between Pc and Sw processed by Lambda curve is acquired for each core sample. Meanwhile, 3 coefficients A, B and C can be obtained in Lambda formula. By nonlinear regression, coherent relation between each factor and reservoir properties (porosity and permeability) for each DRT are obtained. Height above the free water level is estimated by geometrical modeling on the oil water contact. The Sw model is constructed by the new SHF function coupled with DRT model. It showed that the water saturation derived from SHF is highly consistent with log derived results and NMR results. Moreover, it provides more precise results in thinner sands and in spatial distribution.
Based on the identified different rocktype, a new SHF derived from capillary pressure data is utilized to establish the relationship between saturation, the height above the free water level and rock properties. The approach can significantly improve the accuracy of saturation prediction of thin reservoir and reasonably depict the spatial distribution characteristics of saturation. Furthermore, the approach will provide a more precise result in hydrocarbon volume calculation and numerical simulation.