Multiple-Point Geostatistical Modeling of Braided Channel Reservoir with Constraints by 3D Seismic Data: A Case Study of M Block in Venezuela
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摘要: 将地震信息引入多点统计地质建模之中，可以提高模型的井间预测功能.首先以委内瑞拉奥里诺科重油带一个辫状河沉积含油区块为例，结合该区辫状河储层的地质特点，利用井震信息结合的多点统计建模方法，研究了波阻抗的相标定、砂体概率生成曲线选定、训练图像分析、井震影响比等方面的技术细节及它们在辫状河储层多点统计建模中的作用.然后结合辫状河储层的沉积学特征，对研究区的心滩、河道、泛滥平原等微相空间分布的建模结果进行了分析.最后对于不同的储层建模结果进行了不确定性分析.研究表明：井震结合的多点统计建模方法，较好地降低了稀井网地区建模结果的不确定性；通过砂岩概率生成曲线，波阻抗数据转化为地震相的空间概率分布.这样就有效地建立起了地震数据与其地质意义的联系；相比仅用测井信息建模，井震结合建模结果对井间微相预测更具合理性，同时预测的河道、心滩的连续性也得到了更好的体现.Abstract: Integrating seismic information into multi-point statistical geological modeling can improve the cross well prediction function of the model. Taking a braided river sedimentary oil-bearing block in Orinoco heavy oil belt, Venezuela, as an example, combined with the geological characteristics of braided river reservoir in this area, and using the multi-point statistical modeling method integrated well with seismic data, is this paper it studies the facies calibration of seismic wave impedance, the selection of sand-body probability generation curve, training image analysis, impact ratio between well and seismic data, and their role in multi-point statistical modeling of braided river reservoir. Then, combined with the sedimentological characteristic of braided river reservoir, the modeling results of microfacies spatial distribution such as channel bar, river channel and flood plain in the study area are analyzed. Finally, the uncertainty of different reservoir modeling results is analyzed. The research shows that the multi-point statistical modeling method integrated well and seismic data can better reduce the uncertainty of modeling results in areas with sparse well pattern. Through the probability generation curve of sandstone, the wave impedance data is transformed into the spatial probability distribution of seismic facies. In this way, the relationship between seismic data and its geological significance is effectively established. Compared with modeling only with well-logging data, the method integrated well seismic data modeling result is more reasonable for inter well microfacies prediction, and the continuity of predicted river channel and channel bar is better displayed.
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图 1 研究区Oficina组油层划分图（W2井）
Fig. 1. Oil-bearing layers of the Oficina Formation in the study area
图 2 自然伽马‒波阻抗交汇图分析沉积微相
Fig. 2. Sedimentary micro-facies analysis with the cross plot of GR well-logging and seismic impedance data
图 3 相标定地震相数据
Fig. 3. Seismic facies classification result defined with sedimentary microfacies
图 5 参考地震相数据制成的辫状河训练图像
Fig. 5. Different learning maps of braided river referring to seismic facies in the study area
图 6 依据辫状河训练图像的建模结果
Fig. 6. Reservoir modelling results dominated by learning maps on braided river
图 7 不同地震信息影响比约束条件下的建模结果（第6片）
图中的3张直方图，描述了在三种影响比之下，泛滥平原（相代码为0）、河道（相代码为1）、心滩（相代码位为2）等微相的空间比例
Fig. 7. Different reservoir modelling results under the condition of different seismic impact ratios
图 12 利用测井数据的建模结果与原始地震波阻抗的对比
图12d的底部的那张剖面图是利用原始地震波阻抗生成的.从它的色标可以看出，波阻抗最小是兰色，标定为泛滥平原.波阻抗再大一些，就是灰色、红色，标定为河道.波阻抗最大时是黄色，可以标定为心滩；坐标单位为m
Fig. 12. Comparison modelling results between well-logging data and original seismic wave impedance
图 13 不同随机种子条件下井震结合建模结果与原始地震波阻抗的对比
坐标单位为m
Fig. 13. Comparison modelling results between well integrated seismic data under different random seed conditions and original seismic wave impedance
表 1 Morichal段主要沉积微相类型
Table 1. Main types of sedimentary micro-faicies in the Morichal Member
相 亚相 微相 垂向层序 推移质/悬移质比 辫状河相 河床 河道 正韵律 很大 心滩 复合韵律 很大 河漫 泛滥平原 无韵律 小 
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表 2 研究区辫状河主要砂体类型及其宽度与厚度规模统计
Table 2. Statistics on width and thickness scales of major sandbodies of braided river in the study area
成因砂体类型 宽度（m） 厚度（m） 宽度/厚度 单一河道 100~250 2~5 20~50 单一心滩 120~250 2.5~6 30~50 复合河道带或心滩 1 500~3 000 10~25 60~150
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[1] Avseth, P., 2000. Combining Rock Physics and Sedimentology for Seismic Reservoir Characterization of North Sea Turbidite System (Dissertation). Stanford University, Palo Alto. [2] Avseth, P., Mukerji, T., 2002. Seismic Lithofacies Classification from Well Logs Using Statistical Rock Physics. Petrophysics, 43(2): 70-81. [3] Chen, B. T., Yu, X. H., Wang, T. Q., et al., 2015. Lithofacies and Configuration Characteristics of Sandy Braided River-Taking the Outcrop of Middle Jurassic Yungang Formation in Datong Basin, Shanxi Province as an Example. Petroleum and Natural Gas Geology, 36(1): 111-117 (in Chinese with English abstract). [4] Chen, S. Z., Lin, C. Y., Ren, L. H., et al., 2015. Establishment of the Depositional Model of Sandy Braided River: A Case from the H Block in Orinoco Heavy Oil Belt, Venezuela. Acta Sedimentologica Sinica, 33(5): 965-971 (in Chinese with English abstract). [5] Doyen, M. P., 2007. Seismic Reservoir Characterization: An Earth Modeling Perspective. EAGE Publications, https://doi.org/10.3997/9789073781771 [6] Dubrule, O., Damsleth, E., 2001. Achievements and Challenges in Petroleum Geostatistics. Petroleum Geoscience, 7: 1-7. doi: 10.1144/petgeo.7.1.1 [7] He, Y. H., Song, B. Q., Zhang, C. S., 2012. Experimental Research and Understanding of Physical Simulation of Braided River Sand Body in Daqing Placanticline. Earth Science Frontiers, 19(2): 41-48 (in Chinese with English abstract). [8] Huang, W. S., Chen, H. P., Li, S. L., et al., 2018. Quantification of Braided-River Lithofacies Units and Sandbody Based on Horizontal Well Data: A Case of MPE3 Block in Orinoco Heavy-Oil Zone, Venezuela. Oil & Gas Geology, 39(2): 409-418 (in Chinese with English abstract). [9] Huang, W. S., Li, S. L., Chen, H. P., et al., 2020. A River-Dominated to Tide-Dominated Delta Transition: A Depositional System Case Study in the Orinoco Heavy Oil Belt, Eastern Veneuelan Basin. Marine and Petroleum Geology, 118: 104389. https://doi.org/10.1016/j.marpetgeo.2020.104389 [10] Jia, A. L., 2011. 20 Years of Reservoir Geological Model in China. Acta Petrolei Sinica, 32(1): 181-188 (in Chinese with English abstract). [11] Journel, A. G., 2002. Combining Knowledge from Diverse Sources: An Alternative to Traditional Data Independence Hypotheses. Mathematical Geology, 34(5): 573-596. doi: 10.1023/A:1016047012594 [12] Li, N., Li, C. B., Chu, W. K., et al., 2021. Uncertainty Visualisation of a 3D Geological Geometry Model and Its Application in GIS-Based Mineral Resource Assessment: A Case Study in Huayuan District, Northwestern Hunan Province, China. Journal of Earth Science, 32(2): 358-369. doi: 10.1007/s12583-021-1434-y [13] Li, S. L., Yu, X. H., Jiang, T., et al., 2017. Meander-Braided Transition Features and Abandoned Channel Patterns in Fluvial Environment. Acta Sedimentologica Sinica, 35(1): 1-9 (in Chinese with English abstract). [14] Li, S. L., Yu, X. H., Jin, J. L., 2016. Sedimentary Microfacies and Porosity Modeling of Deep-Water Sandy Debris Flows by Combinging Sedimentary Patterns with Seismic Data: An Example from Unit I of Gas Field A, South China Sea. Acta Geologica Sinica, 90(1): 182-194. doi: 10.1111/1755-6724.12650 [15] Liu, W. L., 2008. Seismic Constrained Reservoir Geological Modeling Technology. Acta Petrolei Sinica, 29(1): 64-68, 74 (in Chinese with English abstract). doi: 10.3321/j.issn:0253-2697.2008.01.011 [16] Martinius, A. W., Hegner, J., Kaas, I., et al., 2012. Sedimentology and Depositional Model for the Early Miocene Oficina Formation in the Petrocedeño Field (Orinoco Heavy-Oil Belt, Venezuela). Marine and Petroleum Geology, 35: 354-380. doi: 10.1016/j.marpetgeo.2012.02.013 [17] Meng, Y. J., Zhao, Y. C., Xiong, S., et al., 2021. Study on Reservoir Architecture and Reservoir Units of Fluvial Deposits of Dongying Formation in Yuke Oilfield. Earth Science, 46(7): 2481-2493 (in Chinese with English abstract). https://doi.org/10.3799/dqkx.2020.226 [18] Mu, L. X., Han, G. Q., 2009. Structural Genesis Analysis of Orinoco Heavy Oil Belt. Advances in Geophysics, 24(2): 488-493 (in Chinese with English abstract). [19] Mu, L. X., Xu, B. J., Zhang, S. C., et al., 2008. Integrated 3D Geology Modeling Constrained by Facies and Horizontal Well Data for Block M of the Orinoco Heavy Oil Belt. SPE 117468, Calgary. [20] Qiu, Y. N., 1991. Reservoir Geological Model. Journal of Petroleum, 12(4): 55-62 (in Chinese with English abstract). [21] Salaheddin, K., 2010. Rock Typing Approach for Reservoir Characterization of Ordovician Sandstones, Fields Case Study, Concessions NC115/NC186, Murzuq Basin, Libya. SPE 128825, Cairo. [22] Wang, J. H., Chen, T., 2013. Study on Multi-Point Geostatistical Modeling Method of Reservoir Sedimentary Facies. Application of Petrochemical Industry, 32(8): 57-59 (in Chinese with English abstract). [23] Wang, J. H., Xia, J. Z., 2013. 3D Seismic Constrained Multipoint Modeling to Reduce the Uncertainty of Cross Well Sand Body Prediction. Acta Sedimentologica Sinica, 31(5): 878-888 (in Chinese with English abstract). [24] Wang, W. S., Wang, S. H., Hou, K. F., et al., 2018. Comparative Study of Braided River Reservoir Modeling Methods. Low Permeability Oil and Gas Fields, (1): 41-44 (in Chinese with English abstract). [25] Wilson, R. P., Liebsch, N., Davies, I. M., et al., 2007. All at Sea with Animal Tracks; Methodological and Analytical Solutions for the Resolution of Movement. Deep Sea Research Part II: Topical Studies in Oceanography, 54(3-4): 193-210. doi: 10.1016/j.dsr2.2006.11.017 [26] Wu, S. H., Li, W. K., 2005. Multiple-Point Geostatistics: Theory, Application and Perspective. Journal of Palaeogeography, 7(1): 137-144 (in Chinese with English abstract). doi: 10.3969/j.issn.1671-1505.2005.01.013 [27] Yin, Y. S., Zhang, C. M., Li, S. H., et al., 2014. A Pattern-Based Multiple Point Geostatistics Method. Geological Review, 60(1): 216-221 (in Chinese with English abstract). [28] Yu, X. H., Li, S. L., 2009. The Development and Hotspot Problems of Chastic Petroleum Reservoir Sedimentology. Acta Sedimentologica Sinica, 27(5): 880-895 (in Chinese with English abstract). [29] Zahner, R., 2013. A Stochastic Model to Develop Braided Stream Reservoirs: Montalvo Field, Ventura Basin. SPE 165359, Monterey. [30] Zhu, H. T., Liu, K. Y., Zhu, X. M., et al., 2018. Varieties of Sequence Stratigraphic Configurations in Continental Basins. Earth Science, 43(3): 770-785 (in Chinese with English abstract). https://doi.org/10.3799/dqkx.2018.906 [31] 陈彬滔, 于兴河, 王天奇, 等, 2015. 砂质辫状河岩相与构型特征: 以山西大同盆地中侏罗统云冈组露头为例. 石油与天然气地质, 36(1): 111-117. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201501015.htm [32] 陈仕臻, 林承焰, 任丽华, 等, 2015. 砂质辫状河沉积模式的建立: 以委内瑞拉奥里诺科重油带H区块为例. 沉积学报, 33(5): 965-971. https://www.cnki.com.cn/Article/CJFDTOTAL-CJXB201505012.htm [33] 何宇航, 宋保全, 张春生, 2012. 大庆长垣辫状河砂体物理模拟实验研究与认识. 地学前缘, 19(2): 41-48. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY201202008.htm [34] 黄文松, 陈和平, 李胜利, 等, 2018. 基于水平井信息的辫状河岩相单元与砂体定量研究: 以委内瑞拉奥里诺科重油带MPE3区块为例. 石油与天然气地质, 39(2): 409-418. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201802020.htm [35] 贾爱林, 2011. 中国储层地质模型20年. 石油学报, 32(1): 181-188. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB201101034.htm [36] 李胜利, 于兴河, 姜涛, 等, 2017. 河流辫: 曲转换特点与废弃河道模式. 沉积学报, 35(1): 1-9. https://www.cnki.com.cn/Article/CJFDTOTAL-CJXB201701001.htm [37] 刘文岭, 2008. 地震约束储层地质建模技术. 石油学报, 29(1): 64-68, 74. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB200801013.htm [38] 孟玉净, 赵彦超, 熊山, 等, 2021. 榆科油田东营组河流相储层构型与油藏单元研究. 地球科学, 46(7): 2481-2493. doi: 10.3799/dqkx.2020.226 [39] 穆龙新, 韩国庆, 2009. 奥里诺科重油带构造成因分析. 地球物理学进展, 24(2): 488-493. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ200902018.htm [40] 裘怿楠, 1991. 储层地质模型. 石油学报, 12(4): 55-62. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB202111011.htm [41] 王家华, 陈涛, 2013. 储层沉积相多点地质统计学建模方法研究. 石油化工应用, 32(8): 57-59. https://www.cnki.com.cn/Article/CJFDTOTAL-NXSH201308019.htm [42] 王家华, 夏吉庄, 2013. 三维地震约束多点建模降低井间砂体预测的不确定性. 沉积学报, 31(5): 878-888. https://www.cnki.com.cn/Article/CJFDTOTAL-CJXB201305013.htm [43] 王文胜, 王树慧, 侯科锋, 等, 2018. 辫状河储层建模方法的比较研究. 低渗透油气田, (1): 41-44. [44] 吴胜和, 李文克, 2005. 多点地质统计学: 理论、应用与展望. 古地理学报, 7(1): 137-144. https://www.cnki.com.cn/Article/CJFDTOTAL-GDLX200501014.htm [45] 尹艳树, 张昌民, 李少华, 等, 2014. 一种基于沉积模式的多点地质统计学建模方法. 地质论评, 60(1): 216-221. https://www.cnki.com.cn/Article/CJFDTOTAL-DZLP201401022.htm [46] 于兴河, 李胜利, 2009. 碎屑岩系油气储层沉积学的发展历程与热点问题思考. 沉积学报, 27(5): 880-895. https://www.cnki.com.cn/Article/CJFDTOTAL-CJXB200905013.htm [47] 朱红涛, 刘可禹, 朱筱敏, 等, 2018. 陆相盆地层序构型多元化体系. 地球科学, 43(3): 770-785. doi: 10.3799/dqkx.2018.906 -
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