Citation: | HAN X Y, YANG Q L, LIU Z, et al. Pre-stack Multidimensional Facies-controlled Thin Sandstone Prediction under Rock Physics Modeling of Coal-Bearing Strata in the Southern Ordos Basin[J]. CT Theory and Applications, xxxx, x(x): 1-10. DOI: 10.15953/j.ctta.2024.262. (in Chinese). |
In the southern region of the Ordos Basin, the thin, single-layer distributary channel sands in the Lower Shihezi Formation cause coupling between the sidelobes of the underlying Shanxi-Taiyuan coal seam reflections and the reflections of thin sand bodies within a limited seismic resolution, making it difficult to accurately analyze the reservoir response characteristics. Additionally, challenges in petrophysical analysis arise owing to the poor quality of the logging curves and insufficient shear wave data in this area block, which impede quantitative reservoir prediction. To address these issues, this study proposes a set of sand, mud, and coal three-phase petrophysical modeling techniques based on the Xu–White petrophysical model, employing a multiparameter fitting curve correction and stepwise fusion method. This approach effectively improves the quality of logging curves and enhances the accuracy of shear wave velocity prediction, thereby providing reasonable logging information for subsequent inversions. Furthermore, to address the reservoir prediction problems mentioned above, this study introduces a multidimensional facies-controlled pre-stack geostatistical inversion method suitable for the study area. First, based on the existing geological understanding and well log information, seismic attributes related to channel sands were analyzed, and a two-dimensional lithofacies probability density conforming to sedimentary variation patterns was extracted as a planar constraint for the Shihezi Formation reservoir. Then, using the coal seam inversion volume combined with Bayesian discrimination principles, a three-dimensional coal facies probability density was extracted as a spatial constraint for the underlying coal seam. Finally, both two- and three-dimensional constraints were comprehensively integrated to conduct a pre-stack geostatistical inversion. The prediction results obtained using this method comprehensively considered the coupling characteristics of the underlying coal seams and sandstone reservoirs, effectively reducing the uncertainty in predicting thin reservoirs and demonstrating good practical application with significantly improved drilling concordance.
[1] |
张杨. 利用Xu-White模型估算地震波速度[J]. 成都理工大学学报: 自然科学版, 2005, 32(2): 188-195.
ZHANG Y. Xu White’s model for seismic wave velocity prediction[J]. Journal of Chengdu University of Technology: Science and Technology Edition, 2005, 32(2): 188-195. (in Chinese).
|
[2] |
洪忠, 张猛刚, 朱筱敏. 基于岩石物理的致密碎屑岩气藏岩性及流体概率预测[J]. 石油物探, 2015, 54(6): 735-744. DOI: 10.3969/j.issn.1000-1441.2015.06.012.
HONG Z, ZHANG M G, ZHU X M. Prediction of lithology and fluid probabilities of tight clastic gas reservoirs based on rock physics[J]. Geophysical Prospecting for Petroleum, 2015, 54(6): 735-744. DOI: 10.3969/j.issn.1000-1441.2015.06.012. (in Chinese).
|
[3] |
边婧. 地震岩石物理分析在致密砂岩储层预测中的应用[J]. 东北石油大学学报, 2015, 39(5): 63-70. DOI: 10.3969/j.issn.2095-4107.2015.05.007.
BIAN J. Application of rock physics to the prediction of tight sandstone reservoirs[J]. Journal of Northeast Petroleum University, 2015, 39(5): 63-70. DOI: 10.3969/j.issn.2095-4107.2015.05.007. (in Chinese).
|
[4] |
窦龑, 高刚 梁琳 等. 基于Xu-White 模型的横波速度预测[J]. 新疆石油地质, 2016, 37(1): 83-87.
DOU Y, GAO G, LIANG LET AL. Prediction of S-Wave velocity based on Xu-White model[J]. Xinjiang Petroleum Geology, 2016, 37(1): 83-87. (in Chinese).
|
[5] |
王金伟, 张尔华, 谢春临. 虚拟孔隙度优化的Xu-White模型法预测横波速度[J]. 断块油气田, 2011, 18(4): 445-448.
WANG J W, ZHANG E H, XIE C L. Prediction of shear wave velocity with optimized Xu-White model based on virtual porosity[J]. Fault-Block Oil & Gas Field, 2011, 18(4): 445-448. (in Chinese).
|
[6] |
杨志芳, 曹宏, 姚逢昌, 等. 复杂孔隙结构储层地震岩石物理分析及应用[J]. 中国石油勘探, 2014, 19(3): 50-56. DOI: 10.3969/j.issn.1672-7703.2014.03.006.
YANG Z F, CAO H, YAO F C, ET AL. Seismic rock physical analysis of complex porous reservoir and its application[J]. China Petroleum Exploration, 2014, 19(3): 50-56. DOI: 10.3969/j.issn.1672-7703.2014.03.006. (in Chinese).
|
[7] |
杨勤林, 李洋, 曹少蕾, 等. 松辽盆地苏家屯区块致密砂岩岩石物理分析和含气性预测[J]. 天然气地球科学, 2020, 31(4): 578-585.
YANG Q L, LI Y, CAO S L, ET AL. Rock physics analysis and gas-bearing prediction of tight clastic reservoir in Sujiatun Block, Songliao Basin[J]. Natural Gas Geoscience, 2020, 31(4): 578-585. (in Chinese).
|
[8] |
陈强, 彭盛强, 赵光亮, 等. 地震岩石物理建模技术在迪北阿合组致密砂岩气中的应用[J]. 物探化探计算技术, 2024, 46(3): 315-323. DOI: 10.3969/j.issn.1001-1749.2024.03.08.
CHEN Q, PENG S Q, ZHAO G L, ET AL. Application of seismic rock physical modeling technology in tight sandstone gas of Dibei Ahe Formation[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2024, 46(3): 315-323. DOI: 10.3969/j.issn.1001-1749.2024.03.08. (in Chinese).
|
[9] |
HAAS A, DUBRULE O. Geostatistical inversion: A sequential method of stochastic reservoir modelling constrained by seismic data[J]. First Break, 1994, 12(11): 561-569.
|
[10] |
姜文龙, 杨锴. 岩石物理参数高分辨率地质统计学反演[J]. 石油物探, 2012, 51(6): 638-648. DOI: 10.3969/j.issn.1000-1441.2012.06.014.
JIANG W L, YANG K. High-resolution geostatistical petrophysical parameter inversion[J]. Geophysical Prospecting for Petroleum, 2012, 51(6): 638-648. DOI: 10.3969/j.issn.1000-1441.2012.06.014. (in Chinese).
|
[11] |
刘占族, 张雷, 霍丽娜, 等. 地质统计学反演在煤层气薄储层识别中的应用[J]. 石油地球物理勘探, 2012, 47(S1): 30-34.
LIU Z, ZHANG L, HUO L N, ET AL. Identification of thin coalbed methane reservoirs using geostatistical inversion[J]. Oil Geophysical Prospecting, 2012, 47(S1): 30-34. (in Chinese).
|
[12] |
赵晨, 张广智, 张佳佳, 等. 基于Metropolis优化的叠前全局迭代地质统计学反演方法[J]. 地球物理学报, 2020, 63(8): 3116-3130. DOI: 10.6038/cjg2020M0674.
ZHAO C, ZHANG G Z, ZHANG J J, ET AL. Prestack global iteration geostatistical inversion method based on Metropolis sampling algorithm[J]. Chinese Journal of Geophysics, 2020, 63(8): 3116-3130. DOI: 10.6038/cjg2020M0674. (in Chinese).
|
[13] |
闵小刚, 康安, 周守信. 基于相控地质统计学反演的薄储层岩性、物性预测[J]. 海洋地质前沿, 2015, 31(3): 27-32.
MIN X G, KANG A, ZHOU S X. Lithological and physical properties prediction of thin reservoirs based on faciescontrolled geo-statistical inversion[J]. Marine Geology Frontiers, 2015, 31(3): 27-32. (in Chinese).
|
[14] |
段新意, 李尧, 郭军, 等. 相控地质统计学反演方法及其在油田开发中的应用[J]. 断块油气田, 2021, 28(5): 683-690.
DUAN X Y, LI Y, GUO J, ET AL. The facies-control geostatistical inversion method and its application in development stage of oilfield[J]. Fault-Block Oil and Gas Field, 2021, 28(5): 683-690. (in Chinese).
|
[15] |
林利明, 郑颖, 史浩, 等. 基于相控地质统计学叠前反演的致密砂岩薄储层含气性预测——以鄂尔多斯盆地临兴中区为例[J]. 天然气工业, 2023, 43(2): 56-66. DOI: 10.3787/j.issn.1000-0976.2023.02.006.
LIN L M, ZHENG Y, SHI H, ET AL. Gas-bearing prediction of thin tight sandstone reservoirs based on facies-controlled geostatistical pre-stack inversion: A case study of the middle Linxing Block in the Ordos Basin[J]. Natural Gas Industry, 2023, 43(2): 56-66. DOI: 10.3787/j.issn.1000-0976.2023.02.006. (in Chinese).
|
[16] |
伊振林, 吴胜和, 张保国, 等. 一种新的测井曲线环境校正方法——在平湖油气田中的应用[J]. 天然气工业, 2010, 30(1): 39-41. DOI: 10.3787/j.issn.1000-0976.2010.01.010.
YI Z L, WU S H, ZHANG B G, ET AL. Anewapproachto environmental correction of logs: Acase study in the Pinghu oil and gas field[J]. Natural Gas Industry, 2010, 30(1): 39-41. DOI: 10.3787/j.issn.1000-0976.2010.01.010. (in Chinese).
|
[17] |
刘之的, 王剑, 杨秀春, 等. 密度测井扩径影响校正方法在煤层气储层中的适用性分析[J]. 地球物理学进展, 2014, 29(5): 2219-2223. DOI: 10.6038/pg20140534.
LIU Z D, WANG J, YANG X C, ET AL. Applicability analysis of correction method for expanding diameter influence of density logging in coalbed methane reservoir[J]. Progress in Geophysics, 2014, 29(5): 2219-2223. DOI: 10.6038/pg20140534. (in Chinese).
|
[18] |
王小玄, 肖程释, 郑翔天. 基于岩石物理分析的煤系地层测井曲线扩径影响校正[J]. 中国煤炭, 2016, 42(2): 22-26. DOI: 10.3969/j.issn.1006-530X.2016.02.006.
WANG X X, XIAO C S, ZHENG X T. Expanding effect correction of coal measure strata logging curves based upon rock physics analysis[J]. China Coal, 2016, 42(2): 22-26. DOI: 10.3969/j.issn.1006-530X.2016.02.006. (in Chinese).
|
[19] |
XU S Y, WHITE R E. A new velocity model for clay-sand mixtures[J]. Geophysical Prospecting, 1995, 43(1): 91-118. DOI: 10.1111/j.1365-2478.1995.tb00126.x.
|
[20] |
ROBERT G, KEYS, XU S Y. An approximation for the Xu-White velocity model[J]. Geophysics, 2002, 65(5): 1406-1414.
|
[21] |
TORRES-VERDIN C, VICTORIA M, MERLETTI G, ET AL. Trace-based and geostatistical inversion of 3-D seismic data for thin-sand delineation: An application in San Jorge Basin, Argentina[J]. The Leading Edge, 1999, 18(9): 1070-1077. DOI: 10.1190/1.1438434.
|
[22] |
CONTRERAS A, TORRES-VERDIN C, KVIEN K, et al. AVA stochastic inversion of pre-stack seismic data and well logs for 3D reservoir modeling[C]//67th EAGE Conference & Exhibition. Madrid: European Association of Geoscientists & Engineers, 2005: cp-1-00310.
|
[23] |
张广智, 王丹阳, 印兴耀, 等. 基于MCMC的叠前地震反演方法研究[J]. 地球物理学报, 2011, 54(11): 2926-2932. DOI: 10.3969/j.issn.0001-5733.2011.11.022.
ZHANG G Z, WANG D Y, YIN X Y, ET AL. Study on prestack seismic inversion using Markov Chain Monte Carlo[J]. Chinese Journal of Geophysics, 2011, 54(11): 2926-2932. DOI: 10.3969/j.issn.0001-5733.2011.11.022. (in Chinese).
|
[24] |
王丹阳. 基于MCMC方法的叠前反演方法研究[D]. 青岛: 中国石油大学(华东), 2012.
WANG D Y. Pre-stack seismic inversion based on Markov Chain Monte Carlo Method[D]. Qingdao: China University of Petroleum (East China), 2012. (in Chinese).
|