成像测井在灯影组微生物岩岩相识别中的应用

doi:10.11885/j.issn.1674-5086.2019.04.14.01

西南石油大学学报(自然科学版) ›› 2020, Vol. 42 ›› Issue (5): 75-85.DOI: 10.11885/j.issn.1674-5086.2019.04.14.01

成像测井在灯影组微生物岩岩相识别中的应用

田瀚^1,2,3, 张建勇^1,2,3, 李昌^1,2, 李文正^1,2,3, 姚倩颖^1,2,3

1. 中国石油杭州地质研究院, 浙江杭州 310023;
2. 中国石油勘探开发研究院四川盆地研究中心, 四川成都 610041;
3. 中国石油天然气集团公司碳酸盐岩储集层重点实验室, 浙江杭州 310023

收稿日期:2019-04-14 出版日期:2020-10-10 发布日期:2020-10-10
通讯作者: 田瀚,E-mail:tianh_hz@petrochian.com.cn
作者简介:田瀚,1989年生,男,汉族,湖北黄冈人,工程师,硕士,主要从事碳酸盐岩测井地质学研究。E-mail:tianh_hz@petrochian.com.cn;张建勇,1978年生,男,汉族,山东莘县人,高级工程师,博士,主要从事油气地质、沉积储层及油气地球化学研究。E-mail:zhangjy_hz@petrochian.com.cn;李昌,1978年生,男,汉族,黑龙江哈尔滨人,高级工程师,博士研究生,主要从事碳酸盐岩沉积储层测井评价方法研究与应用工作。E-mail:lic_hz@petrochina.com.cn;李文正,1988年生,男,汉族,安微亳州人,工程师,硕士,主要从事碳酸盐岩沉积储层研究。E-mail:liwz_hz@petrochian.com.cn;姚倩颖,1988年生,女,汉族,甘肃兰州人,工程师,硕士,主要从事碳酸盐岩沉积储层研究。E-mail:yaoqy_hz@petrochian.com.cn
基金资助:
国家科技重大专项（2017ZX05008-005）；中国石油科技部重点项目（2018A-0105）

The Application of Image Logging in the Identification of Microbialite Facies in Dengying Formation, Sichuan Basin

TIAN Han^1,2,3, ZHANG Jianyong^1,2,3, LI Chang^1,2, LI Wenzheng^1,2,3, YAO Qianying^1,2,3

1. Hangzhou Research Institute of Geology, PetroChina, Hangzhou, Zhejiang 310023, China;
2. Research Institute of Sichuan Basin, PetroChina Research Institute of Petroleum Exploration & Development, Chengdu, Sichuan 610041, China;
3. CNPC Key Laboratory of Carbonate Reservoirs, Hangzhou, Zhejiang 310023, China

Received:2019-04-14 Online:2020-10-10 Published:2020-10-10

摘要/Abstract

摘要： 岩相识别是沉积储层研究的基础，针对未取芯井开展测井岩相识别工作至关重要。对于四川盆地震旦系灯影组碳酸盐岩地层而言，由于经历过多期成岩改造作用，使得不同岩相的常规测井响应特征区分度较低，准确识别难度大。为了建立有效的测井岩相识别方法，在前人岩石分类的基础上，通过选取多口岩芯、薄片和测井等资料齐全的代表性钻井作为关键井，在充分发挥成像测井优势基础上，明确不同岩相典型成像特征，建立成像测井相岩相的转换模型，并采用多点地质统计学方法开展成像测井全井眼图像处理，提取图像典型特征，结合所建立的岩相转换模型，开展全井段岩相识别，并推广应用于研究区其他未取芯井。通过实际效果验证表明，相比常规测井，基于成像测井所建立的岩相识别方法岩性识别准确率更高，能为后续沉积微相和储层研究提供有力支撑。

关键词: 四川盆地, 灯影组, 微生物白云岩, 成像测井相, 岩性识别

Abstract: The lithology identification is the basis of study of the sedimentary facies and reservoirs, and it is very important to identify well logging lithofacies for uncored wells. The carbonate of Dengying Formation of Sinian system in Sichuan Basin, has undergone strong digenesis that led to the low discrimination for log response characteristics of different lithofacie, poses great challenge for conventional logs to identify carbonate lithofacies. In order to establish an effective identification method of log facies, on the basis of previous classification, the wells with complete core, thin section and logging data of the fourth Member of Dengying Formation in Gaoshiti-Moxi Area were selected as key wells. We conduct fine description of cores, extract the different typical imaging features of lithofacies, and establish the transformation model of the image logging facies and lithofacies. Finally, we use multi-point geostatistics method to carry out the whole wellbole imaging process. We extract image features, combine the established lithofacies identification model to carry out the lithofacies identification, then apply the method sto other uncored wells in the study area. The results show that the lithofacies identification method based on image logging has a high identification rate, which can provide a strong support for the subsequent studies of sedimentary microfacies and reservoir development mechanism.

Key words: Sichuan Basin, Dengying Formation, microbial dolomite, image logging facies, lithofacies identification

中图分类号:

TE122

田瀚, 张建勇, 李昌, 李文正, 姚倩颖. 成像测井在灯影组微生物岩岩相识别中的应用[J]. 西南石油大学学报(自然科学版), 2020, 42(5): 75-85.

TIAN Han, ZHANG Jianyong, LI Chang, LI Wenzheng, YAO Qianying. The Application of Image Logging in the Identification of Microbialite Facies in Dengying Formation, Sichuan Basin[J]. 西南石油大学学报(自然科学版), 2020, 42(5): 75-85.

0
/ / 推荐

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://journal15.magtechjournal.com/Jwk_xnzk/CN/10.11885/j.issn.1674-5086.2019.04.14.01

http://journal15.magtechjournal.com/Jwk_xnzk/CN/Y2020/V42/I5/75

参考文献

[1] 王玉玺,田昌炳,高计县,等. 常规测井资料定量解释碳酸盐岩微相——以伊拉克北Rumaila油田Mishrif组为例[J]. 石油学报, 2013, 34(6):1088-1099. doi:10.7623/syxb201306007 WANG Yuxi, TIAN Changbing, GAO Jixian, et al. A quantitative explanation of carbonate microfacies based on conventional logging data:A case study of the Mishrif Formation in north Rumaila Oilfield of Iraq[J]. Acta Petrolei Sinica, 2013, 34(6):1088-1099. doi:10.7623/syxb201306007
[2] 张洪,邹乐君,沈晓华. BP神经网络在测井岩性识别中的应用[J]. 地质与勘探, 2002, 38(6):63-65. doi:10.3969/j.issn.0495-5331.2002.06.015 ZHANG Hong, ZOU Lejun, SHEN Xiaohua. The application of BP neurai network in well lithology identification[J]. Geology and Prospecting, 2002, 38(6):63-65. doi:10.3969/j.issn.0495-5331.2002.06.015
[3] 焦翠华,张福明,李洪奇,等. 神经网络和分形几何方法在识别测井沉积微相中的应用[J]. 沉积学报, 1997, 15(3):62-66. JIAO Cuihua, ZHANG Fuming, LI Hongqi, et al. Application of the neural network and fractal geometry in sedimentary environment study from well logs[J]. Acta Sedimentologica Sinica, 1997, 15(3):62-66.
[4] 李道伦,卢德唐,孔祥言,等. BP神经网络隐式法在测井数据处理中的应用[J]. 石油学报, 2007, 28(3):105-108. doi:10.3321/j.issn:0253-2697.2007.03.021 LI Daolun, LU Detang, KONG Xiangyan, et al. Processing of well log data based on backpropagation neural network implicit approximation[J]. Acta Petrolei Sinica, 2007, 28(3):105-108. doi:10.3321/j.issn:0253-2697.2007.03.021
[5] 雍世和,陈钢花. 应用Bayes逐步判别分析自动确定岩性[J]. 石油物探, 1990, 29(2):68-77. YONG Shihe, CHEN Ganghua. Automatic determination of lithology by using of Bayes step-by-step discriminative analysis[J]. Geophysical Prospecting for Petroleum, 1990, 29(2):68-77.
[6] 张莹,潘保芝. 基于主成分分析的SOM神经网络在火山岩岩性识别中的应用[J]. 测井技术, 2009, 33(6):550-554. doi:10.3969/j.issn.1004-1338.2009.06.011 ZHANG Ying, PAN Baozhi. Application of SOM neural network method to volcanic lithology recognition based on principal components analysis[J]. Well Logging Technology, 2009, 33(6):550-554. doi:10.3969/j.issn.1004-1338.2009.06.011
[7] 蒋裕强,张春,张本健,等. 复杂砂砾岩储集体岩相特征及识别技术以川西北地区为例[J]. 天然气工业,2013,33(4):31-36. doi:10.3787/j.issn.1000-0976.2013.04.004 JIANG Yuqiang, ZHANG Chun, ZHANG Benjian, et al. Characteristics and identification of lithofacies in complex siliceous clastic reservoirs:A case study from northwestern Sichuan Basin[J]. Natural Gas Industry, 2013, 33(4):31-36. doi:10.3787/j.issn.1000-0976.2013.04.004
[8] 陈钢花,王中文,李德云,等. 利用多元统计方法自动识别沉积微相[J]. 石油物探, 1997, 36(1):71-76. CHEN Ganghua, WANG Zhongwen, LI Deyun, et al. Automatic discriminant sedimentary microfacies by means of multivariate statistics analysis[J]. Geophysical Prospecting for Petroleum, 1997, 36(1):71-76.
[9] 张小莉,沈英. 模式识别在测井相分析中的应用[J]. 西北大学学报(自然科学版), 1998, 28(5):439-442. ZHANG Xiaoli, SHEN Ying. Application of pattern recognition to logfaciese analysis[J]. Journal of Northwest University (Natural Science Edition), 1998, 28(5):439-442.
[10] 张治国,杨毅恒,夏立显. 自组织特征映射神经网络在测井岩性识别中的应用[J]. 地球物理学进展, 2005, 20(2):332-336. ZHANG Zhiguo, YANG Yiheng, XIA Lixian. The application of self-organizing feature map neural network to logging lithological identification[J]. Progress in Geophysics, 2005, 20(2):332-336.
[11] 任培罡,夏存银,李媛,等. 自组织神经网络在测井储层评价中的应用[J]. 地质科技情报, 2010, 29(3):114-118. doi:10.3969/j.issn.1000-7849.2010.03.018 REN Peigang, XIA Cunyin, LI Yuan, et al. Application of self-organizing neural network to logging reservoir evaluation[J]. Geological Science and Technology Information, 2010, 29(3):114-118. doi:10.3969/j.issn.1000-7849.2010.03.018
[12] 卢西亚F J. 碳酸盐岩储层表征[M]. 北京:石油工业出版社, 2011. LUCIA F J. Carbonate reservoir characterization[M]. Beijing:Petroleum Industry Press, 2011.
[13] 李昌,乔占峰,邓兴梁,等. 视岩石结构数技术在测井识别碳酸盐岩岩相中的应用[J]. 油气地球物理, 2017, 15(1):29-35. LI Chang, QIAO Zhanfeng, DENG Xingliang, et al. Application of the apparent rock fabric number calculation technique in logging identification of the carbonate rock type[J]. Petroleum Geophysics, 2017, 15(1):29-35.
[14] 刘宏,谭秀成,周彦,等. 基于灰色关联的复杂碳酸盐岩测井岩相识别[J]. 大庆石油地质与开发, 2008, 27(1):122-125. LIU Hong, TAN Xiucheng, ZHOU Yan, et al. Log lithofacies identification for complex carbonate rock based on grey correlation method[J]. Petroleum Geology & Oilfield Development in Daqing, 2008, 27(1):122-125.
[15] 李宁,肖承文,伍丽红,等. 复杂碳酸盐岩储层测井评价中国的创新与发展[J]. 测井技术, 2014, 38(1):1-10. doi:10.3969/j.issn.1004-1338.2014.01.001 LI Ning, XIAO Chengwen, WU Lihong, et al. The innovation and development of log evaluation for complex carbonate reservoir in China[J]. Well Logging Technology, 2014, 38(1):1-10. doi:10.3969/j.issn.1004-1338.2014.01.001
[16] 张龙海,代大经,周明顺,等. 成像测井资料在湖盆沉积研究中的应用[J]. 石油勘探与开发, 2006, 33(1):67-71. ZHANG Longhai, DAI Dajing, ZHOU Mingshun, et al. Application of imaging logs in studying lake basin sedimentations[J]. Petroleum Exploration and Development, 2006, 33(1):67-71.
[17] 吴煜宇,张为民,田昌炳,等. 成像测井资料在礁滩型碳酸盐岩储集层岩性和沉积相识别中的应用以伊拉克鲁迈拉油田为例[J]. 地球物理学进展, 2013, 28(3):1497-1506. doi:10.6038/pg20130345 WU Yuyu, ZHANG Weimin, TIAN Changbing, et al. Application of image logging in identifying lithologies and sedimental facies in reef-shoal carbonate reservoir:Take Rumaila Oilfield in Iraq for example[J]. Progress in Geophysics, 2013, 28(3):1497-1506. doi:10.6038/pg20130345
[18] 徐欣,胡明毅,高达. 磨溪高石梯地区灯影组四段微生物岩沉积特征及主控因素[J]. 中国海上油气, 2018, 30(2):25-34. doi:10.11935/j.issn.1673-1506.2018.02.004 XU Xin, HU Mingyi, GAO Da. Sedimentary characteristics and main control factors for microbialite of the fourth Member of Dengying Formation in Moxi-Gaoshiti Area, Central Sichuan Basin[J]. China Offshore Oil and Gas, 2018, 30(2):25-34. doi:10.11935/j.issn.1673-1506.2018.02.004
[19] 王文之,杨跃明,文龙,等. 微生物碳酸盐岩沉积特征研究以四川盆地高磨地区灯影组为例[J]. 中国地质, 2016, 43(1):306-318. WANG Wenzhi, YANG Yueming, WEN Long, et al. A study of sedimentary characteristics of microbial carbonate:A case study of the Sinian Dengying Formation in Gaomo Area, Sichuan Baisn[J]. Geology in China, 2016, 43(1):306-318.
[20] 文龙,王文之,张健,等. 川中高石梯磨溪地区震旦系灯影组碳酸盐岩岩石类型及分布规律[J]. 岩石学报, 2017, 33(4):1285-1294. WEN Long, WANG Wenzhi, ZHANG Jian, et al. Classification of Sinian Dengying Formation and sedimentary evolution mechanism of Gaoshiti-Moxi Area in central Sichuan Basin[J]. Acta Petrologica Sinica, 2017, 33(4):1285-1294.
[21] 王良军. 川北地区灯影组四段优质储层特征及控制因素[J]. 岩性油气藏, 2019, 31(2):35-45. doi:10.12108/yxyqc.20190205 WANG Liangjun. Characteristics and controlling factors of high-quality reservoirs of the fourth member of Dengying Formation in northern Sichuan Basin[J]. Lithologic Reservoirs, 2019, 31(2):35-45. doi:10.12108/yxyqc.20190205
[22] 张荫本,唐泽尧,陈季高. 粘结岩分类及应用[J]. 天然气勘探与开发, 1996, 19(4):24-33. ZHANG Yinben, TANG Zeyao, CHEN Jigao. Bond rock classification and application[J]. Natural Gas Exporation and Development, 1996, 19(4):24-33.
[23] 段金宝,代林呈,李毕松,等. 四川盆地北部上震旦统灯影组四段储层特征及其控制因素[J]. 天然气工业, 2019, 39(7):9-20. doi:10.3787/j.issn.1000-0976.2019.07.002 DUAN Jinbao, DAI Lincheng, LI Bisong, et al. Reservoir characteristics and their controlling factors of the fourth Member of Upper Sinian Dengying Fm in the northern Sichuan Basin[J]. Natural Gas Industry, 2019, 39(7):9-20. doi:10.3787/j.issn.1000-0976.2019.07.002
[24] 李国欣,赵太平,石玉江,等. 鄂尔多斯盆地马家沟组碳酸盐岩储层成岩相测井识别评价[J]. 石油学报, 2018,39(10):1141-1154. doi:10.7623/syxb201810006 LI Guoxin, ZHAO Taiping, SHI Yujiang, et al. Diagenetic facies logging recognition and evaluation of carbonate reservoirs in Majiagou Formation, Ordos Basin[J]. Acta Petrolei Sinica, 2018, 39(10):1141-1154. doi:10.7623/syxb201810006
[25] 孙建孟,赵建鹏,赖富强,等. 电测井图像空白条带填充方法[J]. 测井技术, 2011, 35(6):532-537. doi:10.3969/j.issn.1004-1338.2011.06.008 SUN Jianmeng, ZHAO Jianpeng, LAI Fuqiang, et al. Method to fill in the gaps between pads of electrical logging images[J]. Well Logging Technology, 2011, 35(6):532-537. doi:10.3969/j.issn.1004-1338.2011.06.008
[26] 张挺. 基于多点地质统计的多孔介质重构方法及实现[D]. 合肥:中国科学技术大学, 2009. ZHANG Ting. Research on the reconstruction of porous media based on multiple-point geostatistics[D]. Hefei:University of Science and Technology of China, 2009.

成像测井在灯影组微生物岩岩相识别中的应用

The Application of Image Logging in the Identification of Microbialite Facies in Dengying Formation, Sichuan Basin

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	白晓亮, 杨跃明, 文龙, 罗冰, 洪海涛. 四川盆地中二叠统栖霞组沉积相展布及勘探意义[J]. 西南石油大学学报(自然科学版), 2020, 42(5): 13-24.
[2]	王伟东, 彭军, 夏青松, 段冠一, 孙恩慧. 川北大安寨生屑灰岩储层主控因素及预测思路[J]. 西南石油大学学报(自然科学版), 2020, 42(4): 13-21.
[3]	侯明才, 何亮, 徐胜林, 汤智江. 镇巴地区灯影组岩石微相研究与沉积环境分析[J]. 西南石油大学学报(自然科学版), 2020, 42(3): 31-42.
[4]	刘欢, 李明隆, 江林, 夏吉文, 王廷栋. 油气分段捕获揭示震旦——寒武系天然气成藏过程[J]. 西南石油大学学报(自然科学版), 2019, 41(3): 42-50.
[5]	刘红岐, 李博, 王拥军, 田杰, 孙杨沙. 川中大安寨段致密油储层储集特征研究[J]. 西南石油大学学报(自然科学版), 2018, 40(6): 47-55.
[6]	李松, 马辉运, 张华, 叶颉枭, 韩慧芬. 四川盆地震旦系气藏大斜度井水平井酸压技术[J]. 西南石油大学学报(自然科学版), 2018, 40(3): 146-155.
[7]	刘宏, 王高峰, 刘南, 乔琳, 崔健. 自贡地区嘉陵江组台内滩储层特征与主控因素[J]. 西南石油大学学报(自然科学版), 2017, 39(5): 1-9.
[8]	厚刚福, 倪超, 陈薇, 谷明峰, 郝毅. 川中地区大安寨段介壳滩沉积特征及控制因素[J]. 西南石油大学学报(自然科学版), 2017, 39(1): 25-34.
[9]	李烨*，司马立强，吴丰，黄丹，李清. 注汞压力对致密砂岩储层物性下限分析的影响[J]. 西南石油大学学报(自然科学版), 2015, 37(5): 79-84.
[10]	李宇平*. 涪陵北部长兴组礁滩相沉积模式与勘探领域[J]. 西南石油大学学报(自然科学版), 2015, 37(4): 29-34.
[11]	冯动军1，2 *，肖开华1，2. 四川盆地陆相烃源岩成熟史及生排烃史[J]. 西南石油大学学报(自然科学版), 2015, 37(2): 57-64.
[12]	张宪国1 *，张涛2，林承焰1，于景锋3. 塔南凹陷复杂岩性低渗透储层测井岩性识别[J]. 西南石油大学学报(自然科学版), 2015, 37(1): 85-90.
[13]	周川闽1，2，宋丽红3，刘庆松4，罗忠1，2，高志勇1，2. 川中须家河组五段河道砂体地震沉积学刻画[J]. 西南石油大学学报(自然科学版), 2014, 36(4): 1-11.
[14]	王坤1，张奉2，张翊2，王东坤3. 准西车排子凸起石炭系岩性识别与储层特征[J]. 西南石油大学学报(自然科学版), 2014, 36(4): 21-28.
[15]	王兴志1，李宜真1，杜洋1，2，胡杨2，李烨1. 四川盆地下志留统龙马溪组底部界线研究[J]. 西南石油大学学报(自然科学版), 2014, 36(1): 45-50.