Petroleum Reservoir Evaluation and Development >
2020 , Vol. 10 >Issue 1: 37 - 42
DOI: https://doi.org/10.13809/j.cnki.cn32-1825/te.2020.01.006
An evaluation method of shale reservoir crushability based on grey correlation analysis
Received date: 2019-03-18
Online published: 2020-02-04
The crushability evaluation of shale reservoir is a complex system engineering. But as there are many parameters that affect the reservoir crushability, including the reservoir basic geological parameters, the rock mechanics, the formation pressure, the in-situ stress and the engineering technology, and the main influencing factors of different gas fields are different, multiple round of pilot tests are needed just to find out the main control factors affecting the productivity in complex working areas. Until now, there is no unified and authoritative evaluation method for shale reservoir crushability in China, it is extremely urgent to complete this task. Therefore, a method for shale gas reservoir crushability evaluation based on grey correlation analysis is proposed. This method has the advantages that it can quickly identify the main control sensitive parameters that affect the production. The correlation of the parameters is strong. And the production after fracturing can be predicted according to the sensitive parameters. With the increase of the number of developed wells, the prediction accuracy will be higher. In the gas field, the main control sensitive parameters can be adjusted by the optimization of engineering process, so as to further improve the fracturing effect.
Zhangliang LONG , Zhentao WEN , Hui LI , Xianwei ZENG . An evaluation method of shale reservoir crushability based on grey correlation analysis[J]. Petroleum Reservoir Evaluation and Development, 2020 , 10(1) : 37 -42 . DOI: 10.13809/j.cnki.cn32-1825/te.2020.01.006
| [1] | 王学萌, 张继忠, 王荣 . 灰色系统分析及实用计算程序[M]. 武汉: 华中科技大学出版社, 2001: 8-16. |
| [1] | WANG X M, ZHANG J Z, WANG R. Grey system analysis and practical calculation program[M]. Wuhan: Huazhong University of science and Technology Press, 2001: 8-16. |
| [2] | 邓聚龙 . 灰色系统基本方法[M]. 武汉: 华中理工大学出版社, 1987: 1-42. |
| [2] | DENG J L. Basic method of grey system[M]. Wuhan: Huazhong University of Technology Press, 1987: 1-42. |
| [3] | 连承波, 钟建华, 蔡福龙 , 等. 油田产量影响因素的灰色关联分析[J]. 天然气地球科学, 2006,17(6):851-853. |
| [3] | LIAN C B, ZHONG J H, CAI F L , et al. Influencing factors analysis of oil field output based on grey correlation analytical method[J]. Natural Gas Geoscience, 2006,17(6):851-853. |
| [4] | 李颖川 . 采油工程[M]. 北京: 石油工业出版社, 2002: 284. |
| [4] | LI Y C. Oil production engineering[M]. Beijing: Petroleum Industry Press, 2002: 284. |
| [5] | 宋毅, 伊向艺, 卢渊 , 等. 基于灰色关联分析法的酸压后产能主控因素研究[J]. 石油地质与工程, 2009,23(1):82-84. |
| [5] | SONG Y, YI X Y, LU Y , et al. Study on main factors of off- take potential after gray associative analysis- based acidification and fracturing[J]. Petroleum Geology and Engineering, 2009,23(1):82-84. |
| [6] | 肖寒 . 威远区块页岩气水平井基于灰色关联分析的产能评价方法[J]. 油气井测试, 2018,27(4):73-78. |
| [6] | XIAO H . Productivity evaluation method based on grey correlation analysis for shale gas horizontal wells in Weiyuan block[J]. Well Testing, 2018,27(4):73-78. |
| [7] | 洪亚飞, 王建忠, 孙强 , 等. 焦石坝页岩气储层产能影响因素分析[J]. 非常规油气, 2016,3(5):73-78. |
| [7] | HONG Y F . Analysis of the influence factors for shale gas reservoir in Jiaoshiba area[J]. Unconventional Oil and Gas, 2016,3(5):73-78. |
| [8] | 马文礼, 李治平, 孙玉平 , 等. 基于机器学习的页岩气产能非确定性预测方法研究[J]. 特种油气藏, 2019,26(6):101-105. |
| [8] | MA W L, LI Z P, SUN Y P , et al. Non-deterministic shale gas productivity forecast based on machine learning[J]. Special Oil and Gas Reservoir, 2019,26(6):101-105. |
| [9] | 徐小明, 周明, 熊巍 , 等. 页岩气产能影响因素分析[J]. 石油化工应用, 2013,32(9):10-13. |
| [9] | XU X M, ZHOU M, XIONG W , et al. Analysis on shale gas production affecting factors[J]. Petrochemical Industry Application, 2013,32(9):10-13. |
| [10] | 王衍, 马俯波, 张海英 , 等. 灰色关联分析法在页岩储层评价中的应用——以湖南保靖页岩气区块为例[J]. 非常规油气, 2017,4(6):8-12. |
| [10] | WANG Y, MA F B, ZHANG H Y , et al. Application of grey relational analysis in shale gas reservoir evaluation——Taking shale gas block in Baojing, Hunan as an example[J]. Unconventional Oil and Gas, 2017,4(6):8-12. |
| [11] | 王忠东, 王业博, 董红 , 等. 页岩气水平井产量主控因素分析及产能预测[J]. 测井技术, 2017,41(5):577-582. |
| [11] | WANG Z D, WANG Y B, DONG H , et al. Production main control factors analysis and productivity prediction for shale gas of horizontal well[J]. Well Logging technology, 2017,41(5):577-582. |
| [12] | 梁榜, 卢文涛, 曾勇 , 等. 涪陵焦石坝页岩气初期产能主控因素研究[J]. 江汉石油职工大学学报, 2016,29(5):1-4. |
| [12] | LIANG B, LU W T, ZENG Y , et al. Main controlling factors for early productivity of shale gas in Fuling Jiaoshiba area[J]. Journal of Jianghan Petroleum University of Staff and Workers, 2016,29(5):1-4. |
| [13] | 侯腾飞, 张士诚, 马新仿 , 等. 涪陵页岩气X井裂缝网络参数对产能的影响[J]. 深圳大学学报, 2016,33(4):409-417. |
| [13] | HOU T F, ZHANG S C, MA X F , et al. Influence of fracture network parameters on productivity of shale gas well X in Fuling block[J]. Journal of Shenzhen University(Science & Engineering), 2016,33(4):409-417. |
| [14] | 王娟 . 天然裂缝对页岩气储层产能贡献不大[J]. 天然气勘探与开发, 2017,40(3):119. |
| [14] | WANG J . Natural fracture has little contribution to shale gas reservoir productivity[J]. Natural gas exploration and development, 2017,40(3):119. |
| [15] | 李凯, 张浩, 冉超 , 等. 考虑应力敏感的页岩气产能预测模型研究——以川东南龙马溪组页岩气储层为例[J]. 西安石油大学学报(自然科学版), 2016,31(3):57-61. |
| [15] | LI K, ZHANG H, RAN C , et al. Productivity model of shale gas well with consideration of stress sensitivity: Taking Longmaxi Formation Shale Gas Reservoir in Southeastern Sichuan Basin as an example[J]. Journal of Xi'an Shiyou University(Natural Science), 2016,31(3):57-61. |
/
| 〈 |
|
〉 |