利用地震属性、多元统计分析理论和ANFIS预测碳酸盐岩储层裂缝孔隙度
|
摘要
碳酸盐岩储层非均质性和各向异性强,利用某种单一技术难以准确定量地刻画出裂缝孔隙度空间分布情况。利用地震属性、多元统计分析理论和ANFIS(自适应性模糊神经网络)综合预测碳酸盐岩储层裂缝孔隙度。用成像测井资料准确识别裂缝孔隙发育位置,并计算出裂缝孔隙度的大小,用自适应性模糊神经网络建立井孔裂缝孔隙度和井旁地震属性数据体之间的函数关系模型,结合全区地震属性数据体对碳酸盐岩储层进行定量评价。利用该项技术预测塔中某工区碳酸盐岩储层裂缝孔隙度分布,预测结果与钻遇优质储层的井点吻合,说明该方法在该区有一定的实用性。
The carbonate reservoir is characterized by strong heterogeneity and anisotropy.It is difficult to determine fracture porosity space distribution in carbonate reservoir accurately and completely just using a single method.Introduced is a comprehensive method to predict the fracture porosity in carbonate reservoir such as seismic attributes,multi-analysis and Adaptive Neuro-Fuzzy Inference System(ANFIS).Imaging logging data is used to identify the positions of fracture porosity accurately,and calculate the pore size.The ANFIS is used to build a function relation model between the borehole fracture porosity and the seismic attributes data around the well.Then,the quantitative evaluation of the carbonate reservoir is made by combining the seismic attributes data of the whole work area.This method is used in predicting the fracture porosity distribution in a work area in the middle of Tarim basin.The result shows that the predicted fracture porosity developing zone is in good accordance with the high quality reservoirs drilled.It is proved that this method is adaptable in the area.
The carbonate reservoir is characterized by strong heterogeneity and anisotropy.It is difficult to determine fracture porosity space distribution in carbonate reservoir accurately and completely just using a single method.Introduced is a comprehensive method to predict the fracture porosity in carbonate reservoir such as seismic attributes,multi-analysis and Adaptive Neuro-Fuzzy Inference System(ANFIS).Imaging logging data is used to identify the positions of fracture porosity accurately,and calculate the pore size.The ANFIS is used to build a function relation model between the borehole fracture porosity and the seismic attributes data around the well.Then,the quantitative evaluation of the carbonate reservoir is made by combining the seismic attributes data of the whole work area.This method is used in predicting the fracture porosity distribution in a work area in the middle of Tarim basin.The result shows that the predicted fracture porosity developing zone is in good accordance with the high quality reservoirs drilled.It is proved that this method is adaptable in the area.
引文
[1]Jian F X,Chork C Y,Taggart I J,et al.A GeneticApproach to the Prediction of Petrophysical Properties[J].Journal of Petroleum Geology,1994,17(1):71-88.
[2]司马立强,等.测井地震结合储层参数推广反演技术及应用[J].测井技术,2001,25(1):12-15.
[3]贾文玉,田素月,孔耀庭,等.成像测井技术与应用[M].北京:石油工业出版社,2000:15-25.
[4]吴兴能,刘瑞林,等.电成像测井资料变换为孔隙度分布图像的研究[J].测井技术,2008,32(1):53-56.
[5]罗宁,赵志惠.测井新技术在广安地区的应用[J].测井技术,2007,31(3):249-252.
[6]李潮流,王树寅.利用FMI成像测井识别柴西第三系藻灰岩储层[J].测井技术,2006,30(6):523-526.
[7]Chen Q,Steve S.Seismic Attribute Technology forReservoir Forecasting and Monitoring[J].The Lead-ing Edge,1997,16(5):445-456.
[8]印兴耀,孔国英,张广智.基于核主成分分析的地震属性优化方法及应用[J].石油地球物理勘探,2008,43(2):179-183.
[9]刘伟方,等.利用地震属性预测碳酸盐岩储层[J].岩性油气藏,2007,19(1):101-104.
[10]Johnson R A,Wichern D W.实用多元统计分析[M].北京:清华大学出版社,2001:388-439.
[11]赵睿,等.模糊逻辑和神经网络及其在含油饱和度预测中的应用[J].测井技术,2007,31(4):327-330.
[12]Takagi T,Sugeno M.Fuzzy Identification and Its Ap-plication to Modeling and Control[J].ESMC,1985,15(1):116-132.
[2]司马立强,等.测井地震结合储层参数推广反演技术及应用[J].测井技术,2001,25(1):12-15.
[3]贾文玉,田素月,孔耀庭,等.成像测井技术与应用[M].北京:石油工业出版社,2000:15-25.
[4]吴兴能,刘瑞林,等.电成像测井资料变换为孔隙度分布图像的研究[J].测井技术,2008,32(1):53-56.
[5]罗宁,赵志惠.测井新技术在广安地区的应用[J].测井技术,2007,31(3):249-252.
[6]李潮流,王树寅.利用FMI成像测井识别柴西第三系藻灰岩储层[J].测井技术,2006,30(6):523-526.
[7]Chen Q,Steve S.Seismic Attribute Technology forReservoir Forecasting and Monitoring[J].The Lead-ing Edge,1997,16(5):445-456.
[8]印兴耀,孔国英,张广智.基于核主成分分析的地震属性优化方法及应用[J].石油地球物理勘探,2008,43(2):179-183.
[9]刘伟方,等.利用地震属性预测碳酸盐岩储层[J].岩性油气藏,2007,19(1):101-104.
[10]Johnson R A,Wichern D W.实用多元统计分析[M].北京:清华大学出版社,2001:388-439.
[11]赵睿,等.模糊逻辑和神经网络及其在含油饱和度预测中的应用[J].测井技术,2007,31(4):327-330.
[12]Takagi T,Sugeno M.Fuzzy Identification and Its Ap-plication to Modeling and Control[J].ESMC,1985,15(1):116-132.
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心