Reservoir prediction of conglomerate bodies in the fourth member of Xujiahe Formation of Nanjiang area, northeastern Sichuan Basin: a probabilistic body lithofacies modeling-based reservoir prediction method combining forward and inverse modeling
-
摘要: 川东北山前带南江地区上三叠统须家河组发育大规模典型砂砾岩含气储层，勘探程度低、潜力巨大，其中须四段是重要的含气储层，构造与岩性复杂、地球物理参数敏感性较差、多解性强，储层表征难度大，有利储层分布特征与规律认识不清。鉴于此，针对勘探初期的砂砾岩储层预测方法进行攻关研究，将地震正演、反演与序贯高斯模拟的岩相建模方法相结合，形成了正反演结合的概率体岩相建模储层预测方法，即应用地震正演确定储层边界、地震反演初步预测储层空间分布、测井与反演协同建模精细预测岩相空间概率分布，最终实现储层精细预测。研究表明：基于正反演结合的概率体岩相建模储层预测方法，以岩相建模为桥梁，将测井数据与地震反演结果相结合，实现了储层厚度定量预测；结合地震正演精细刻画的储层边界，有效提高了储层的预测精度。应用该方法精细刻画了南江地区须四段砂砾岩体储层的分布，其中有利储层主要位于砂砾岩相辫状河道，地震上表现为中—弱振幅和微幅下切的特征，砂质含量越高、泥质和砾质含量越低，地震振幅越弱，储层越好；从北向南有利储层逐渐增厚，呈条带状分布，厚度主体介于15~30 m。该研究既为目标区后续井位部署提供了可靠地质依据，又为相似区块的储层预测提供技术方法借鉴。Abstract: The Upper Triassic Xujiahe Formation in the Nanjiang area of the piedmont belt in the northeast Sichuan Basin hosts large-scale, typical conglomerate gas-bearing reservoirs. These reservoirs remain underexplored and hold significant potential. Among them, the fourth member of the Xujiahe Formation is an important gas-bearing reservoir characterized by complex structural and lithological features, low sensitivity of geophysical parameters, and strong multi-solution, making reservoir characterization highly challenging. The distribution characteristics and patterns of favorable reservoirs remain unclear. To address this, a prediction method tailored for early-stage conglomerate reservoir exploration was developed by integrating seismic forward modeling, seismic inversion, and sequential Gaussian simulation-based lithofacies modeling. The probabilistic body lithofacies modeling-based reservoir prediction method applied seismic forward modeling to determine reservoir boundaries, seismic inversion for preliminary spatial reservoir distribution prediction, as well as well-logging and inversion collaborative modeling for refined prediction of the spatial probabilistic distribution of lithofacies, ultimately achieving precise reservoir prediction. The results showed that this prediction method used lithofacies modeling as a bridge to combine logging data with seismic inversion results, enabling quantitative prediction of reservoir thickness. The combination with seismic forward modeling further refined reservoir boundaries, significantly enhancing prediction accuracy. Applying this method to the Nanjiang area, the distribution of conglomerate reservoirs in the fourth member of the Xujiahe Formation was finely characterized. The favorable reservoirs are mainly located in the braided channels of the conglomerate facies, characterized by medium to weak amplitudes and slight amplitude downcutting on seismic profiles. Reservoir quality improves with increasing sandy content and decreasing mud and conglomerate content, resulting in weaker seismic amplitudes. The favorable reservoirs gradually thicken from north to south, exhibiting a banded distribution with thickness primarily between 15 and 30 m. This study provides a reliable geological basis for subsequent well location deployment in the target area and serves as a technical reference for reservoir prediction in similar blocks.
-
图 1 川东北地区山前带须家河组构造区划及沉积综合柱状图
a.四川盆地位置图；b.川东北地区位置及构造区划图；c.川东北须家河组沉积综合柱状图。
Figure 1. Structural division and composite sedimentary column of Xujiahe Formation in piedmont belt of northeastern Sichuan Basin
图 2 基于正反演结合的概率体岩相建模储层预测方法流程
Figure 2. Workflow of probabilistic body lithofacies modeling-based reservoir prediction method integrating forward and inverse modelling
图 3 川东北南江地区须家河组四段沉积综合柱状图
a.LB1井；b.JX1井。
Figure 3. Composite sedimentary column of the fourth member of Xujiahe Formation in Nanjiang area of northeastern Sichuan Basin
图 4 川东北南江地区LB1井须家河组四段储层替换实验
a.LB1井岩性综合柱状图；b.泥质含量增加，振幅变强；c.砾岩减少，砂质含量增加，振幅变弱；d.砾岩增加，砂质含量减少，振幅变强。
Figure 4. Reservoir replacement experiments for the fourth member of Xujiahe Formation in well LB1, Nanjiang area, northeastern Sichuan Basin
图 5 川东北南江地区须家河组四段二维地质模型正演分析
a.正演响应特征；b.正演模型；c.正演响应特征；d.正演模型。
Figure 5. Forward modeling analysis of 2D geological model for the fourth member of Xujiahe Formation in Nanjiang area, northeastern Sichuan Basin
图 6 川东北南江地区须家河组四段最大波峰振幅属性图
Figure 6. Maximum peak amplitude attribute map of the fourth member of Xujiahe Formation in Nanjiang area, northeastern Sichuan Basin
图 7 川东北南江地区须家河组四段岩石物理分析
Figure 7. Petrophysical analysis of the fourth member of Xujiahe Formation in Nanjiang area, northeastern Sichuan Basin
图 8 川东北南江地区波阻抗区分砂砾岩相和砾岩相的概率相关关系
Figure 8. Probabilistic correlation of impedance to distinguish sandy conglomerate facies and conglomerate facies in Nanjiang area, northeastern Sichuan Basin
图 9 川东北南江地区须家河组四段不同概率预测砂砾岩储层结果对比
a.JX1井储层柱状图；b.须四段40%概率模型；c.须四段60%概率模型；d.须四段80%概率模型；e.LB1井储层柱状图。
Figure 9. Comparison of conglomerate reservoir prediction results with different probabilities for the fourth member of Xujiahe Formation, Nanjiang area, northeastern Sichuan Basin
图 10 川东北南江地区须家河组四段储层三维分布模型
Figure 10. 3D reservoir distribution model of the fourth member of Xujiahe member in Nanjiang area, northeastern Sichuan Basin
图 11 川东北南江地区须家河组四段储层厚度预测
Figure 11. Reservoir thickness prediction of the fourth member of Xujiahe Formation in Nanjiang area, northeastern Sichuan Basin
表 1 川东北南江地区须家河组四段4种岩性组合的地震响应特征
Table 1. Seismic response characteristics of four lithological combinations in the fourth member of Xujiahe Formation of Nanjiang area, northeastern Sichuan Basin
-
[1] 高阳. 准噶尔盆地玛湖凹陷砂砾岩储层物性分类及控制因素[J]. 成都理工大学学报(自然科学版), 2022, 49(5): 542-551.GAO Yang. Physical property classification and controlling factors of glutenite reservoir in Mahu Sag, Junggar Basin, China[J]. Journal of Chengdu University of Technology (Science & Technology Edition), 2022, 49(5): 542-551. [2] 陈思芮, 王卫学, 曲希玉, 等. 东营凹陷北带沙四上亚段砂砾岩储层物性主控因素分析[J]. 吉林大学学报(地球科学版), 2022, 52(4): 1091-1106.CHEN Sirui, WANG Weixue, QU Xiyu, et al. Main controlling factors of physical properties of Giutenite reservoirs of Es4s Member in north zone of Dongying Depression[J]. Journal of Jilin University (Earth Science Edition), 2022, 52(4): 1091-1106. [3] 胡鑫, 邹红亮, 胡正舟, 等. 扇三角洲砂砾岩储层特征及主控因素: 以准噶尔盆地东道海子凹陷东斜坡二叠系上乌尔禾组为例[J]. 东北石油大学学报, 2021, 45(6): 15-26.HU Xin, ZOU Hongliang, HU Zhengzhou, et al. Reservoir characteristics and main controlling factors of glutenite reservoir in fan dalta glutenite: a case study of the Upper Urho Formation of Permian in the east slope of Dongdaohaizi Sag, Junggar Basin[J]. Journal of Northeast Petroleum University, 2021, 45(6): 15-26. [4] 王保全, 王志萍, 于喜通, 等. 基于高频层序格架的储层定量预测技术在砂体刻画中的应用[J]. 海洋地质前沿, 2022, 38(9): 78-85.WANG Baoquan, WANG Zhiping, YU Xitong, et al. Application of quantitative reservoir prediction technology based on high frequency sequence framework in sand body[J]. Marine Geology Frontiers, 2022, 38(9): 78-85. [5] 张德明, 刘志刚, 臧殿光, 等. 基于叠前同时反演的致密砂岩储层预测及含气性识别: 以苏里格S区块为例[J]. 物探与化探, 2022, 46(3): 645-652.ZHANG Deming, LIU Zhigang, ZANG Dianguang, et al. Prediction and identification of gas-bearing properties of tight sandstone reservoirs through simultaneous pre-stack inversion: a case study of block S in Sulige gas field[J]. Geophysical and Geochemical Exploration, 2022, 46(3): 645-652. [6] 黎祺, 陆嫣, 何贤科, 等. 基于地震波形分类的三角洲储层刻画与应用: 以西湖凹陷J气田为例[J]. 科学技术与工程, 2022, 22(17): 6847-6856.LI Qi, LU Yan, HE Xianke, et al. Depiction and application of delta reservoir based on seismic waveform classification: a case study of J Gas Field in Xihu Sag[J]. Science Technology and Engineering, 2022, 22(17): 6847-6856. [7] 李达, 隋波, 马光克, 等. 地震多属性分析技术在含气储层预测中的应用[J]. 海洋地质前沿, 2012, 28(6): 51-55.LI Da, SUI Bo, MA Guangke, et al. Application of seismic attributes analysis technology to gas reservoir prediction[J]. Marine Geology Frontiers, 2012, 28(6): 51-55. [8] 林恬, 陈天胜, 刘振峰, 等. 相控地质统计学在元坝区块须家河组的应用[J]. 重庆科技学院学报(自然科学版), 2022, 24(2): 9-15.LIN Tian, CHEN Tiansheng, LIU Zhenfeng, et al. Application of facies-controlled geostatistics in Xujiahe Formation in Yuanba area[J]. Journal of Chongqing University of Science and Technology (Natural Sciences Edition), 2022, 24(2): 9-15. [9] 商晓飞, 赵磊, 易杰, 等. 川西新场地区须家河组二段砂体沉积充填特征及定量地质建模[J]. 中国海上油气, 2022, 34(4): 144-155.SHANG Xiaofei, ZHAO Lei, YI Jie, et al. Sedimentary filling characteristics and quantitative geological modeling of sand bodies in Xu2 Member of Xujiahe Formation in Xinchang area, western Sichuan Basin[J]. China Offshore Oil and Gas, 2022, 34(4): 144-155. [10] 关旭, 金吉能, 杨威, 等. 川中地区须家河组岩性气藏特征与含气有利区预测: 以安岳—磨溪地区须家河组二段为例[J]. 天然气地球科学, 2022, 33(3): 358-368.GUAN Xu, JIN Jineng, YANG Wei, et al. Lithologic gas reservoir characteristics and prediction of gas-bearing favorable zone of the Xujiahe Formation in central Sichuan Basin: case study of the 2nd member of Xujiahe Formation in Anyue-Moxi areas[J]. Natural Gas Geoscience, 2022, 33(3): 358-368. [11] 漆麟, 蒋裕强, 朱讯. 川西北地区须家河组三段致密砂砾岩沉积特征及模式[J]. 四川地质学报, 2021, 41(3): 410-416.QI Lin, JIANG Yuqiang, ZHU Xun. Sedimentological characteristics and sedimentary model of massive in northwest Sichuan[J]. Acta Geologica Sichuan, 2021, 41(3): 410-416. [12] 黄仁春, 刘若冰, 刘明, 等. 川东北通江—马路背地区须家河组断缝体储层特征及成因[J]. 石油与天然气地质, 2021, 42(4): 873-883.HUANG Renchun, LIU Ruobing, LIU Ming, et al. Characteristics and genesis of fault-fracture reservoirs in the Xujiahe Formation, Tongjiang-Malubei area, northeastern Sichuan Basin[J]. Oil & Gas Geology, 2021, 42(4): 873-883. [13] 王威, 凡睿, 黎承银, 等. 川东北地区须家河组"断缝体"气藏有利勘探目标和预测技术[J]. 石油与天然气地质, 2021, 42(4): 992-1001.WANG Wei, FAN Rui, LI Chengyin, et al. Exploration and prediction of promising fault-fracture reservoirs in the Xujiahe Formation, northeastern Sichuan Basin[J]. Oil & Gas Geology, 2021, 42(4): 992-1001. [14] 黄滔, 李瑞雪, 邓虎成, 等. 四川盆地川西坳陷深部致密砂岩储层地应力场预测及分区评价: 以新场—丰谷地区须家河组二段为例[J]. 石油实验地质, 2024, 46(6): 1198-1214. doi: 10.11781/sysydz2024061198HUANG Tao, LI Ruixue, DENG Hucheng, et al. Prediction and zoning evaluation of in-situ stress field in deep tight sandstone reservoirs of Western Sichuan Depression, Sichuan Basin: a case study of the second member of Xujiahe Formation in Xinchang and Fenggu area[J]. Petroleum Geology & Experiment, 2024, 46(6): 1198-1214. doi: 10.11781/sysydz2024061198 [15] 黎承银, 李明阳. 川东北地区须家河组构造差异及其对天然气富集的影响[J]. 天然气技术与经济, 2021, 15(3): 35-41.LI Chengyin, LI Mingyang. Structural difference and its influence on gas accumulation: an example from Xujiahe Formation, northeastern Sichuan Basin[J]. Natural Gas Technology and Economy, 2021, 15(3): 35-41. [16] 周霞, 王威, 杜红权, 等. 川东北地区须家河组四段物源及沉积体系特征[J]. 新疆石油地质, 2015, 36(4): 443-449.ZHOU Xia, WANG Wei, DU Hongquan, et al. Provenance analysis and sedimentary system characteristics of the 4th member of Xujiahe Formation in northeastern Sichuan Basin[J]. Xinjiang Petroleum Geology, 2015, 36(4): 443-449. [17] 李莉妃, 任启强, 杨田, 等. 多级构型界面下致密砂岩储层构造裂缝发育特征: 以川西坳陷须家河组二段为例[J]. 石油实验地质, 2024, 46(4): 722-734. doi: 10.11781/sysydz202404722LI Lifei, REN Qiqiang, YANG Tian, et al. Development characteristics of structural fractures in tight sandstone reservoirs under multi-level configuration interfaces: a case study of second member of Xujiahe Formation in Western Sichuan Depression[J]. Petroleum Geology & Experiment, 2024, 46(4): 722-734. doi: 10.11781/sysydz202404722 [18] 李中超, 周勇水, 刘平, 等. 普光地区须家河组致密砂岩储层成岩作用及孔隙演化[J]. 断块油气田, 2023, 30(3): 353-362.LI Zhongchao, ZHOU Yongshui, LIU Ping, et al. Diagenesis and pore evolution of tight sandstone reservoirs of Xujiahe Formation in Puguang area[J]. Fault-Block Oil & Gas Field, 2023, 30(3): 353-362. [19] 潘磊, 杜红权, 李雷涛, 等. 川东北元坝地区上三叠统须家河组天然裂缝发育特征与主控因素[J]. 地学前缘, 2024, 31(5): 156-165.PAN Lei, DU Hongquan, LI Leitao, et al. Fracture development characteristics and main controlling factors of natural fracture in the Upper Triassic Xujiahe Formation in Yuanba area, northeastern Sichuan Basin[J]. Earth Science Frontiers, 2024, 31(5): 156-165. [20] 段正鑫, 刘一锋, 楼章华, 等. 川西坳陷三叠系须家河组油气富集与地层压力关系[J]. 石油实验地质, 2023, 45(1): 72-79. doi: 10.11781/sysydz202301072DUAN Zhengxin, LIU Yifeng, LOU Zhanghua, et al. Correlation between formation pressure and hydrocarbon enrichment in Triassic Xujiahe Formation, Western Sichuan Depression[J]. Petroleum Geology & Experiment, 2023, 45(1): 72-79. doi: 10.11781/sysydz202301072 [21] 陈友智, 臧殿光, 杨晓, 等. 四川盆地须家河组坡折带发育特征及油气地质意义[J]. 石油实验地质, 2024, 46(3): 491-498. doi: 10.11781/sysydz202403491CHEN Youzhi, ZANG Dianguang, YANG Xiao, et al. Development characteristics and oil-gas geological significance of slope break zone of Xujiahe Formation in Sichuan Basin[J]. Petroleum Geology & Experiment, 2024, 46(3): 491-498. doi: 10.11781/sysydz202403491 [22] 王斌. 准噶尔盆地玛湖地区深层砂砾岩甜点储层形成机理与地震预测方法研究[D]. 成都: 成都理工大学, 2020.WANG Bin. Study on formation mechanism and seismic prediction method of deep glutenite sweet spot reservoir in Mahu area, Junggar[D]. Chengdu: Journal of Chengdu University of Technology, 2020. [23] 杨兆臣, 彭明超, 陈朕, 等. 致密砂砾岩优势储层预测方法综合研究[J]. 当代化工, 2020, 49(9): 2024-2027.YANG Zhaochen, PENG Mingchao, CHEN Zhen, et al. Comprehensive study on prediction methods of favorable tight glutenite reservoirs[J]. Contemporary Chemical Industry, 2020, 49(9): 2024-2027. [24] 曾贤德. 基于完备总体经验模态分解的砂砾岩储层地震预测方法研究[D]. 青岛: 中国石油大学(华东), 2019.ZENG Xiande. Research on seismic prediction method of glutenite reservoir based on complete ensemble empirical mode decomposition[D]. Qingdao: China University of Petroleum (East China), 2019. [25] 杨迪. 基于正演模型的曹妃甸6-4油田东三段砂砾岩储层地震预测[D]. 北京: 中国石油大学, 2018.YANG Di. Reservoir prediction based on seismic forward modeling in the third member of Dongying Formation of CFD6-4 Oilfield[D]. Beijing: China University of Petroleum, 2018. [26] 王长江, 穆星. 陆相断陷盆地储层地震预测技术优化[J]. 上海地质, 2010, 31(S1): 222-226.WANG Changjiang, MU Xing. The technology optimizing for seismic reservoir prediction in the continental rift basin[J]. Shanghai Geology, 2010, 31(S1): 222-226. [27] 孙怡. 陡坡带砂砾岩体地球物理储层预测方法应用研究[D]. 北京: 中国石油大学, 2008.SUN Yi. Research on geophysical reservoir prediction method and application for glutinite bodies in steep slope[D]. Beijing: China University of Petroleum, 2008. [28] 王锦, 冯国奇, 王鑫. 东营凹陷湖盆陡坡带砂砾岩储层评价方法及应用: 以LA区块沙四上亚段为例[J]. 石油地质与工程, 2022, 36(3): 61-68.WANG Jin, FENG Guoqi, WANG Xin. Evaluation method and application of glutenite reservoir in steep slope zone of lacustrine basin in Dongying Depression: by taking E2s41 in LA block as an example[J]. Petroleum Geology and Engineering, 2022, 36(3): 61-68. [29] 钱艳苓. 叠前AVO反演技术在砂砾岩储层预测中的应用研究[D]. 北京: 中国地质大学, 2016.QIAN Yanling. Application of pre-stack AVO inversion technique in glutenite reservoir prediction[D]. Beijing: China University of Geosciences, 2016. [30] 彭传圣, 王永诗, 常国贞, 等. 罗家地区砂砾岩储集层地球物理预测技术[J]. 油气地质与采收率, 2001, 8(2): 36-38.PENG Chuansheng, WANG Yongshi, CHANG Guozhen, et al. Geophysical forecasting technology for glutenite reservoir in Luojia area[J]. Petroleum Geology and Recovery Efficiency, 2001, 8(2): 36-38. [31] 沈向存, 范伟峰, 姜忠正, 等. 地震正演在深水沉积地层研究中的应用[J]. 特种油气藏, 2024, 31(4): 36-43.SHEN Xiangcun, FAN Weifeng, JIANG Zhongzheng, et al. Application of seismic forward modeling in the study of deep-water sedimentary formation[J]. Special Oil & Gas Reservoirs, 2024, 31(4): 36-43. [32] 王静, 束青林, 杜玉山, 等. 页岩油储层裂缝正演模拟及叠前各向异性反演预测方法[J]. 断块油气田, 2024, 31(6): 1031-1038.WANG Jing, SHU Qinglin, DU Yushan, et al. Forward modeling and pre-stack anisotropy inversion prediction methods for fractures of shale oil reservoir[J]. Fault-Block Oil & Gas Field, 2024, 31(6): 1031-1038. [33] 周路, 李飞, 何登发, 等. 四川盆地北部地区三叠系构造及其演化特征分析[J]. 地质科学, 2013, 48(1): 71-92.ZHOU Lu, LI Fei, HE Dengfa, et al. Structure and evolution characteristics analysis of Triassic in northern Sichuan Basin[J]. Chinese Journal of Geology, 2013, 48(1): 71-92. [34] 刘静. 序贯指示条件模拟方法研究及应用[D]. 成都: 成都理工大学, 2008.LIU Jing. The research and application of sequential indicator conditional method[D]. Chengdu: Chengdu University of Technology, 2008. -
下载:
计量
- 文章访问数: 71
- HTML全文浏览量: 38
- PDF下载量: 15
- 被引次数: 0
苏公网安备32021102000780号