致密砂岩储层岩石物理模型的优化建立

doi:10.11867/j.issn.1001-8166.2018.04.0416

地球科学进展 ›› 2018, Vol. 33 ›› Issue (4): 416 -424. doi: 10.11867/j.issn.1001-8166.2018.04.0416

致密砂岩储层岩石物理模型的优化建立

贾凌云 ¹(

), 李琳 ¹, 王千遥 ², 马劲风 ¹, 王大兴 ³

1.西北大学地质学系,二氧化碳捕集与封存技术国家地方联合工程研究中心,陕西西安 710069
2.中煤科工集团西安研究院有限公司,陕西西安 710077
3.中国石油长庆油田公司勘探开发研究院,陕西西安 710018

收稿日期:2017-09-08 修回日期:2018-01-25 出版日期:2018-04-20
基金资助:
*国家高技术研究发展计划项目“二氧化碳地质封存关键技术”(编号:2012AA050103)资助.

Optimization of the Rock Physical Model in Tight Sandstone Reservoir

Lingyun Jia ¹( ), Lin Li ¹, Qianyao Wang ², Jinfeng Ma ¹, Daxing Wang ³

1.National & Local Joint Engineering Research Center of Carbon Capture and Storage Technology, Department of Geology of Northwest University, Xi’an 710069, China;
2.China Coal Technology Engineering Group Xi’an Research Institute, Xi’an 710077, China;
3.Research Institute of Exploration and Development, Changqing Oil Field Company, PetroChina, Xi’an 710018,China;

Received:2017-09-08 Revised:2018-01-25 Online:2018-04-20 Published:2018-05-24
About author:
First author:Jia Lingyun(1983-),female,Datong City,Shanxi Province,Ph. D student. Research areas include seismic data interpretation, inversion and others.E-mail:1027314266@qq.com
Supported by:
Project supported by the National High Technology Research and Development Program of China “Key technique for CO ₂ sequestration” (No.2012AA050103).

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Krief模型、Nur模型和Pride-Lee模型通常被用于计算砂岩储层干岩石模量,但对于致密砂岩储层却效果不佳。基于Krief模型和Nur模型,在满足纵波或横波预测值与实测值差值最小的条件下,通过Gassmann方程求出模型中的岩性指数m或临界孔隙度?_c,进而将模型中通常采用的经验参数表示成随采样点变化的值,提高了Krief模型和Nur模型估算纵横波速的精度,称为变参数Krief模型和变参数Nur模型。此外,对比不同约束条件下纵横波预测精度,可知在致密砂岩储层中3种模型的剪切模量公式的精度更高、适用性更好。Han提出的K_dry与u_dry关系式不受孔隙度、岩性等因素的影响,将该关系式与上述3种模型中任意一种剪切模量公式结合建立干岩石模型,应用到Gassmann方程中对鄂尔多斯盆地苏里格气藏盒8致密砂岩储层横波速度进行预测,提高了预测横波速度的精度,同时获得了3种模型中每个采样点对应的岩性指数m、临界孔隙度?_c和固结参数c的值,这些参数值可以反映出储层的岩性差异、孔隙结构、压实程度等特征,映射了储层的地质特征。

关键词: 致密砂岩储层, 体积模量, 岩石物理模型, K_dry与u_dry的关系

Krief model, Nur model and Pride-Lee model are usually used to calculate dry rock modulus of sandstone reservoirs, but they are not effective for tight sandstone reservoirs. Based on Krief model and Nur model, and minimizing the difference between predicted P-wave or S-wave velocities and measured velocities, we acquireed lithologic index m in Krief model and critical porosity ?_c in Nur model by Gassmann relationship. The empirical parameters used in the models are expressed as the values changing with depth, so the accuracy of Krief and Nur models to estimate the P-wave and S-wave velocities was improved, and these two models are called as the variable parameter Krief model and the variable parameter Nur model. In addition, comparing with prediction accuracy of P-wave and S-wave velocities under different constraints, we can see that the shear modulus formulas in the three models are more accurate and more suitable in the tight sandstone reservoir. Han’s relationship about K_dry and u_dry is not affected by porosity, lithology and other factors, and the paper established dry rock model by Han’s relationship and any one of the above three models. The new dry rock model was applied in the Gassmann relationship to predict S-wave velocity of H8 tight sandstone reservoir in Sulige Gas Filed, Ordos Basin, which improved the accuracy of predicting S-wave velocity. At the same time, lithology index m in Krief model, critical porosity ?_c in Nur model and consolidation parameters c in Pride-Lee model which are corresponding to each sample can be obtained. The values of these parameters can reflect lithology difference, pore structure, compaction degree and other characteristics, which indicate the geological characteristics of the reservoir.

Key words: Tight sandstone reservoir, Bulk modulus, Rock physical model, The relationship of K_dry and u_dry.

中图分类号:

P316

图1 预测纵波速度对比

Fig.1 Comparison of predicted P-wave velocity

图1 预测纵波速度对比

Fig.1 Comparison of predicted P-wave velocity

图2 预测横波速度对比

Fig.2 Comparison of predicted S-wave velocity

图2 预测横波速度对比

Fig.2 Comparison of predicted S-wave velocity

图3 岩性指数与孔隙度交汇

Fig.3 Cross plot of lithological index and porosity

图3 岩性指数与孔隙度交汇

Fig.3 Cross plot of lithological index and porosity

图4 临界孔隙度与孔隙度交汇

Fig.4 Cross plot of critical porosity and porosity

图4 临界孔隙度与孔隙度交汇

Fig.4 Cross plot of critical porosity and porosity

图5 固结参数与孔隙度交汇

Fig.5 Cross plot of consolidation parameters and porosity

图5 固结参数与孔隙度交汇

Fig.5 Cross plot of consolidation parameters and porosity

图6 预测横波速度对比

Fig.6 Comparison of predicted S-wave velocity

图6 预测横波速度对比

Fig.6 Comparison of predicted S-wave velocity

图7 预测纵波速度对比

Fig.7 Comparison of predicted P-wave velocity

图7 预测纵波速度对比

Fig.7 Comparison of predicted P-wave velocity

图8 预测横波速度对比

Fig.8 Comparison of predicted S-wave velocity

图8 预测横波速度对比

Fig.8 Comparison of predicted S-wave velocity

图9 岩性指数与孔隙度交汇

Fig.9 Cross plot of lithological index and porosity

图9 岩性指数与孔隙度交汇

Fig.9 Cross plot of lithological index and porosity

图10 临界孔隙度 ?_c与孔隙度交汇

Fig.10 Cross plot of critical porosity ?_c and porosity

图10 临界孔隙度 ?_c与孔隙度交汇

Fig.10 Cross plot of critical porosity ?_c and porosity

图11 固结参数与孔隙度交汇

Fig.11 Cross plot of consolidation parameters and porosity

图11 固结参数与孔隙度交汇

Fig.11 Cross plot of consolidation parameters and porosity

图12 苏46井盒8段纵横波速度预测对比

Fig.12 Comparison of prediction velocity methods of He 8 formation of well Su 46

图12 苏46井盒8段纵横波速度预测对比

Fig.12 Comparison of prediction velocity methods of He 8 formation of well Su 46

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[1]	汪鹏，钟广法. 南海ODP1144站深海沉积牵引体的岩石物理模型研究[J]. 地球科学进展, 2012, 27(3): 359-366.

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