油气藏评价与开发 >
2020 , Vol. 10 >Issue 1: 37 - 42
DOI: https://doi.org/10.13809/j.cnki.cn32-1825/te.2020.01.006
一种基于灰色关联分析的页岩储层可压性评价方法
收稿日期: 2019-03-18
网络出版日期: 2020-02-04
基金资助
“十三五”国家科技重大专项“彭水地区常压页岩气勘探开发示范工程”(2016ZX05061)
An evaluation method of shale reservoir crushability based on grey correlation analysis
Received date: 2019-03-18
Online published: 2020-02-04
页岩储层的可压性评价是个复杂的系统工程。由于影响储层可压性的参数众多,包括储层基础地质参数（孔隙度、渗透率、含气量、有机碳含量等）,工程地质参数（岩石强度、弹性模量、泊松比、地层压力、地应力等）以及工程参数（水平段长、优质储层钻遇率、分段分簇、压裂规模等）多参数影响,且不同气田的主要影响因素不同,复杂工区光是寻找影响产能的主控因素都需要进行多轮先导试验进行分析评价。由于目前国内还没有一个统一、权威的页岩储层可压性评价方法,气田储层可压性评价任务迫在眉睫,因此,提出了一种基于灰色关联分析的页岩气储层可压性分析评价方法。其优点在于可快速地明确影响产量主控敏感参数。参数相关性强,可根据敏感参数预测压后产量,且随后期开发井数量越多预测精度越高。气田可以通过工程工艺优化调整得出的主控敏感参数,达到进一步提高压裂效果的目的。
龙章亮 , 温真桃 , 李辉 , 曾贤薇 . 一种基于灰色关联分析的页岩储层可压性评价方法[J]. 油气藏评价与开发, 2020 , 10(1) : 37 -42 . DOI: 10.13809/j.cnki.cn32-1825/te.2020.01.006
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.
| [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. |
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