致密砂岩AVO属性的贝叶斯岩相划分方法——以川中地区侏罗系沙溪庙组沙一段为例

doi:10.12108/yxyqc.20240511

岩性油气藏 ›› 2024, Vol. 36 ›› Issue (5): 111–121.doi: 10.12108/yxyqc.20240511

致密砂岩AVO属性的贝叶斯岩相划分方法——以川中地区侏罗系沙溪庙组沙一段为例

陈康¹, 戴隽成¹, 魏玮¹, 刘伟方², 闫媛媛¹, 郗诚¹, 吕龑¹, 杨广广¹

1. 中国石油西南油气田公司勘探开发研究院, 成都 610041;
2. 极遨技术服务(北京)有限公司, 北京 100004

收稿日期:2024-02-01 修回日期:2024-04-10 出版日期:2024-09-01 发布日期:2024-09-04
第一作者:陈康（1988—），男，硕士，高级工程师，主要从事地震资料处理解释方面的研究工作。地址：（610041）四川省成都市高新区天府大道北段12号中国石油西南油气田公司勘探开发研究院。Email：chenkang01@petrochina.com.cn。
通信作者: 刘伟方（1969—），男，博士，高级工程师，主要从事地震综合解释方面的研究工作。Email：435236940@qq.com。
基金资助:
中国石油西南油气田公司科技重大专项“四川盆地中西部地区致密气勘探开发理论及关键技术研究”（编号：2022ZD01-01）资助。

Lithofacies classification of tight sandstone based on Bayesian Facies-AVO attributes：A case study of the first member of Jurassic Shaximiao Formation in central Sichuan Basin

CHEN Kang¹, DAI Juncheng¹, WEI Wei¹, LIU Weifang², YAN Yuanyuan¹, XI Cheng¹, LYU Yan¹, YANG Guangguang¹

1. Research Institute of Exploration and Development, PetroChina Southwest Oil & Gas Field Company, Chengdu 610041, China;
2. GeoSoftware Technology Services(Beijing)Co., Ltd., Beijing 100004, China

Received:2024-02-01 Revised:2024-04-10 Online:2024-09-01 Published:2024-09-04

摘要/Abstract

摘要： 地震勘探中“高速或低速致密砂岩储层”地震响应复杂、非均质性强、反演中的低频模型难以建立。在基于Bayesian分类的AVO（BF-AVO）截距、梯度属性及孔隙度等指标约束下，对川中地区侏罗系沙溪庙组致密砂岩的岩相进行了划分。研究结果表明：①AVO分析是以弹性波理论为基础，根据其振幅随偏移距的变化规律来反映地下岩性及其孔隙流体的性质，在应用过程中，根据不同岩性和流体的相关参数组合进行AVO正演，获得已知岩性和流体性质的AVO特征，与实际地震记录进行对比，建立岩性和油气识别的地震响应模型。②利用模型和实际数据建立的孔隙度与截距、梯度属性的交会分析，厘清三者的内在联系，确定岩相划分标准，并拟合出不同岩相的概率密度函数，划分出不同孔隙度区间的岩相，从而实现孔隙度的半定量预测。③川中侏罗系沙溪庙组沙一段致密砂岩的岩相预测过程中，基于Bayesian分类，以概率分布预测的岩相与实钻结果吻合度高，达93.75%，验证了该方法的可行性和有效性。

关键词: 致密砂岩, 岩相预测, 孔隙度, AVO属性, Bayesian分类, 沙溪庙组, 侏罗系, 四川盆地

Abstract: In seismic exploration，high-velocity or low-velocity tight sandstone reservoirs are often characterized by complex seismic response and strong heterogeneity，and it is difficult to establish a low-frequency model in inversion. With the constraints of AVO intercept and gradient attribute based on Bayesian classification and porosity， the lithofacies of the tight sandstone of Jurassic Shaximiao Formation in central Sichuan Basin was classified. The results show that：（1）Based on elastic wave theory，AVO analysis reflects the underground lithologies and pore fluid properties according to the variation of amplitude with offset. In the application process，AVO forward modeling was carried out based on the relevant parameter combination of different lithologies and fluids，AVO characteristics of known lithologies and fluid properties were obtained and compared with actual seismic records，and then a seismic response model for lithologies and oil and gas identification was established.（2）The crossplot analysis of porosity，intercept and gradient attributes established by model and actual data was used to clarify the internal relationship between the three，determine the classification criteria of lithofacies，fit the probability density function of different lithofacies，and divide the lithofacies of different porosity intervals，to realize the semi-quantitative prediction of porosity.（3）In the application of tight sandstone of the first member of Jurassic Shaximiao Formation in central Sichuan Basin，the lithofacies predicted by probability distribution based on Bayesian classification is up to 93.75% consistent with the actual drilling results，which verifies the feasibility and effectiveness of the method.

Key words: tight sandstone, lithofacies prediction, porosity, AVO attributes, Bayesian classification, Shaximiao Formation, Jurassic, Sichuan Basin

中图分类号:

TE122.1

陈康, 戴隽成, 魏玮, 刘伟方, 闫媛媛, 郗诚, 吕龑, 杨广广. 致密砂岩AVO属性的贝叶斯岩相划分方法——以川中地区侏罗系沙溪庙组沙一段为例[J]. 岩性油气藏, 2024, 36(5): 111–121.

CHEN Kang, DAI Juncheng, WEI Wei, LIU Weifang, YAN Yuanyuan, XI Cheng, LYU Yan, YANG Guangguang. Lithofacies classification of tight sandstone based on Bayesian Facies-AVO attributes：A case study of the first member of Jurassic Shaximiao Formation in central Sichuan Basin[J]. Lithologic Reservoirs, 2024, 36(5): 111–121.

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致密砂岩AVO属性的贝叶斯岩相划分方法——以川中地区侏罗系沙溪庙组沙一段为例

Lithofacies classification of tight sandstone based on Bayesian Facies-AVO attributes：A case study of the first member of Jurassic Shaximiao Formation in central Sichuan Basin

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