基于模糊层次分析法的页岩气井产能影响因素分析及综合评价模型——以四川盆地焦石坝页岩气田为例

doi:10.13809/j.cnki.cn32-1825/te.2022.03.003

摘要/Abstract

摘要：

页岩气藏为“人造气藏”,流动机理复杂,影响气井产能的因素较多,明确气井产能影响因素并建立对应的产能评价模型,是科学高效开发页岩气田的关键。针对涪陵焦石坝页岩气田的地质条件和压裂效果,以分区研究为基础,系统分析页岩气多段压裂水平井的产能影响因素,并利用雷达面积模型和模糊层次分析方法对筛选出的8类产能影响因素进行综合分析。研究结果表明：不同分区各因素对产能的影响程度存在明显差异,主体北区和西区储层物性条件较好,水平段参数和压裂规模是气井产能的主控因素;东区气井产能则与保存条件相关性明显;主体南区埋深增大,可压性参数和压裂规模共同决定气井产能;西南区气井的可压性决定了气井产能。通过模糊层次分析法确定不同分区产能影响因素的权重,进而建立适用于页岩气井的产能综合评价模型。调整井的数值模拟分析和实际应用效果均表明,模糊层次综合评价模型预测的气井产能对焦石坝调整井适用,模型可用于分析和预测页岩气井的产能及开发效果。

关键词: 页岩气, 产能, 影响因素, 模糊分析, 雷达模型, 焦石坝, 四川盆地

Abstract:

Shale gas reservoir is an “artificial reservoir” with complex flow mechanism and many factors affecting well productivity. The key to develop the shale gas field in a scientific and efficient way is to determine the factors influencing gas well productivity and further establish productivity evaluation model. Based on the geological background and fracturing effect of shale wells in the Jiaoshiba Block, Fuling Gas Field, the factors influencing the productivity of multi-stage fractured horizontal shale gas wells are systematically analyzed. Then, the radar chart and fuzzy analytic hierarchy process （FAHP） are used to analyze the eight main factors affecting the productivity. Results show that there are obvious differences in terms of the degree various factors influencing on well productivity in different regions. Specifically, since the reservoir physical properties in the northern of the main area and western areas are favorable, the horizontal section parameters and fracturing scale are the main control factors of gas well productivity; the productivity of gas wells in the eastern area is highly related to the preservation conditions; due to the increase of buried depth in the south of the main area, the compressibility parameters and fracturing scale jointly determine the gas well productivity. In contrast, the compressibility parameters of gas wells in the southwest of the Jiaoshiba are the controlling factor. In this paper, fuzzy analytic hierarchy process （FAHP） is applied to determine the weight of various factors affecting productivity in different areas, and then a comprehensive productivity evaluation model suitable for shale gas wells is established. The results of numerical simulation and practical application show that the gas well productivity predicted by fuzzy comprehensive evaluation model is applicable to the infill wells in the Jiaoshiba Block, and the model is effective to analyze and predict the productivity and development effect of shale gas well.

Key words: shale gas, productivity, influencing factors, fuzzy analysis, radar chart, Jiaoshiba, Sichuan Basin

中图分类号:

TE122

李东晖,田玲钰,聂海宽,等. 基于模糊层次分析法的页岩气井产能影响因素分析及综合评价模型——以四川盆地焦石坝页岩气田为例[J]. 油气藏评价与开发, 2022, 12(3): 417-428.

Donghui LI,Lingyu TIAN,Haikuan NIE, et al. Factor analysis and comprehensive evaluation model of shale gas well productivity based on fuzzy analytic hierarchy process: Taking Jiaoshiba shale gas field in Sichuan Basin as an example[J]. Petroleum Reservoir Evaluation and Development, 2022, 12(3): 417-428.

图/表 17

图1

图2

图3

图4

图5

图6

图7

图8

图9

表1

图10

图11

图12

表2

表3

图13

图14

参考文献 25

[1]	郭彤楼, 蒋恕, 张培先, 等. 四川盆地外围常压页岩气勘探开发进展与攻关方向[J]. 石油实验地质, 2020, 42(5):837-845.
	GUO Tonglou, JIANG Shu, ZHANG Peixian, et al. Progress and direction of exploration and development of normally-pressured shale gas from the periphery of Sichuan Basin[J]. Petroleum Geology & Experiment, 2020, 42(5): 837-845.
[2]	方栋梁, 孟志勇. 页岩气富集高产主控因素分析——以四川盆地涪陵地区五峰组—龙马溪组一段页岩为例[J]. 石油实验地质, 2020, 42(1):37-41.
	FANG Dongliang, MENG Zhiyong. Main controlling factors of shale gas enrichment and high yield: a case study of Wufeng-Longmaxi formations in Fuling area, Sichuan Basin[J]. Petroleum Geology & Experiment, 2020, 42(1): 37-41.
[3]	王玉芳, 翟刚毅, 王劲铸, 等. 四川盆地及周缘龙马溪组页岩产气效果影响因素[J]. 地质力学学报, 2017, 23(4):540-547.
	WANG Yufang, ZHAI Gangyi, WANG Jinzhu, et al. Factors influencing gas production effectiveness of longmaxi formation shale in Sichuan basin and adjacent areas[J]. Journal of Geomechanics, 2017, 23(4): 540-547.
[4]	廖东良, 路保平. 页岩气工程甜点评价方法——以四川盆地焦石坝页岩气田为例[J]. 天然气工业, 2018, 38(2):43-50.
	LIAO Dongliang, LU Baoping. An evaluation method of engineering sweet spots of shale gas reservoir development: A case study from the Jiaoshiba gas field, Sichuan Basin[J]. Natural Gas Industry, 2018, 38(2): 43-50.
[5]	邹才能, 董大忠, 王玉满, 等. 中国页岩气特征、挑战及前景(二)[J]. 石油勘探与开发, 2016, 43(2):166-178.
	ZOU Caineng, DONG Dazhong, WANG Yuman, et al. Shale gas in China; characteristics, challenges and prospects(Ⅱ)[J]. Petroleum Exploration and Development, 2016, 43(2): 166-178.
[6]	柳筠, 张梦吟. 页岩气田储层含气性测井评价——以四川盆地涪陵页岩气田J区块为例[J]. 石油实验地质, 2021, 43(1):128-135.
	LIU Yun, ZHANG Mengyin. Gas-bearing property evaluation by petrophysical logging in shale gas reservoirs:a case study in J area of Fuling shale gas field,Sichuan Basin[J]. Petroleum Geology & Experiment, 2021, 43(1): 128-135.
[7]	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.
	WANG Zhongdong, WANG Yebo, DONG Hong, 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.
[8]	廖东良, 路保平, 陈延军. 页岩气地质甜点评价方法-以四川盆地焦石坝页岩气田为例[J]. 石油学报, 2019, 40(2):18-25.
	LIAO Dongliang, LU Baoping, CHEN Yanjun. An evaluation method of geological sweet spots of shale gas reservoir: a case study of the Jiaoshiba gas field, Sichuan Basin[J]. Acta Petrolei Sinica, 2019, 40(2): 18-25.
[9]	张聪, 常小龙, 丁洋洋, 等. 页岩气地质特征及产能影响因素分析[J]. 中国石油和化工标准与质量, 2019, 39(21):32-33.
	ZHANG Cong, CHANG Xiaolong, DING Yangyang, et al. Geological characteristics of shale gas and analysis of factors affecting its productivity[J]. China Petroleum and Chemical Industry Standards and Quality, 2019, 39(21): 32-33.
[10]	唐军, 彭超. 涪陵页岩气藏水平井初始产能预测方法[J]. 大庆石油地质与开发, 2020, 39(4):1-8.
	TANG Jun, PENG Chao. Predicting method of the initial productivity for the horizontal well in Fuling shale gas reservoirs[J]. Petroleum Geology & Oilfield Development in Daqing, 2020, 39(4): 1-8.
[11]	WANG Y H. What factors control shale gas production decline trend: A comprehensive analysis and investigation[J]. Society of Petroleum Engineers, 2016.
[12]	郭艳东, 王卫红, 刘华, 等. 页岩气多段压裂水平井产能影响因素研究[J]. 科技通报, 2018, 34(4):72-78.
	GUO Yandong, WANG Weihong, LIU Hua, et al. Research on the production influencing factors of shale gas multi-stage fractured horizontal well[J]. Bulletin of Science and Technology, 2018, 34(4): 72-78.
[13]	白玉湖, 徐兵祥, 陈岭, 等. 页岩油气典型曲线及解析模型产量预测新方法[J]. 中国海上油气, 2018, 30(4):120-126.
	BAI Yuhu, XU Bingxiang, CHEN Ling, et al. New production prediction methods for typical curve and analytical model of shale oil and gas[J]. China Offshore Oil and Gas, 2018, 30(4): 120-126.
[14]	孙海成, 汤达祯, 蒋廷学. 页岩气储层裂缝系统影响产量的数值模拟研究[J]. 石油钻探技术, 2011, 39(5):63-67.
	SUN Haicheng, TANG Dazhen, JIANG Tingxue. Numerical simulation of the impact of fracture system on well production in shale formation[J]. Petroleum Drilling Techniques, 2011, 39(5): 63-67.
[15]	钱旭瑞, 刘广忠, 唐佳, 等. 页岩气井产能影响因素分析[J]. 特种油气藏, 2012, 19(3):81-83.
	QIAN Xurui, LIU Guangzhong, TANG Jia, et al. Analysis of influencing factors on shale gas well productivity[J]. Special Oil & Gas Reservoirs, 2012, 19(3): 81-83.
[16]	郭彤楼, 张汉荣. 四川盆地焦石坝页岩气田形成与富集高产模式[J]. 石油勘探与开发, 2014, 41(1):28-36.
	GUO Tonglou, ZHANG Hanrong. Formation and enrichment mode of Jiaoshiba shale gas field in Sichuan Basin[J]. Petroleum Exploration and Development, 2014, 41(1): 28-36.
[17]	胡明, 黄文斌, 李加玉. 构造特征对页岩气井产能的影响-以涪陵页岩气田焦石坝区块为例[J]. 天然气工业, 2017, 37(8):31-39.
	HU Ming, HUANG Wenbin, LI Jiayu. Effects of structural characteristics on the productivity of shale wells-A case study on the Jiaoshiba block in the Fuling shale gasfield in Sichuan Basin[J]. Natural Gas Industry, 2017, 37(8): 31-39.
[18]	王志刚. 涪陵焦石坝地区页岩气水平井压裂改造实践与认识[J]. 石油与天然气地质, 2014, 35(3):425-430.
	WANG Zhigang. Practice and cognition of shale gas horizontal well fracturing stimulation in Jiaoshiba of Fuling areas[J]. Oil & Gas Geology, 2014, 35(3): 425-430.
[19]	梁榜, 李继庆, 郑爱维, 等. 涪陵页岩气田水平井开发效果评价[J]. 天然气地球科学, 2018, 29(2):289-295.
	LIANG Bang, LI Jiqing, ZHENG Aiwei, et al. Development effect evaluation for shale gas wells in Fuling shale gasfield[J]. Natural Gas Geoscience, 2018, 29(2): 289-295.
[20]	郑爱维, 梁榜, 舒志国, 等. 基于大数据PLS法的页岩气产能影响因素分析——以四川盆地涪陵气田焦石坝区块为例[J]. 天然气地球科学, 2020, 31(4):542-551.
	ZHENG Aiwei, LIANG Bang, SHU Zhiguo, et al. Analysis of influencing factors of shale gas productivity based on large data technology: A case of Jiaoshiba block in Fuling Gas Field, Sichuan Basin[J]. Natural Gas Geoscience, 2020, 31(4): 542-551.
[21]	王强, 魏祥峰, 魏富彬, 等. 川东南涪陵地区五峰组—龙马溪组页岩气藏中的超压作用[J]. 石油实验地质, 2019, 41(3):333-340.
	WANG Qiang, WEI Xiangfeng, WEI Fubin, et al. Overpressure in shale gas reservoir of Wufeng Longmaxi formation in Fuling area, Southeast Sichuan[J]. Petroleum experimental geology, 2019, 41(3): 333-340.
[22]	聂海宽, 何治亮, 刘光祥, 等. 四川盆地五峰组—龙马溪组页岩气优质储层成因机制[J]. 天然气工业, 2020, 40(6):31-41.
	NIE Haikuan, HE Zhiliang, LIU Guangxiang, et al. Genetic mechanism of high-quality shale reservoirs in the Wufeng-Longmaxi Fms in the Sichuan Basin[J]. Natural Gas lndustry, 2020, 40(6): 31-41.
[23]	林波, 秦世群, 谢勃勃, 等. 涪陵深层页岩气井压裂工艺难点及对策研究[J]. 石化技术, 2019, 26(5):162-168.
	LIN Bo, QIN Shiqun, XIE Bobo, et al. Study on difficulties and countermeasures of fracturing technology for Fuling deep shale gas well[J]. Petrochemical Technology, 2019, 26(5): 162-168.
[24]	陶余会. 如何构造模糊层次分析法中模糊一致判断矩阵[J]. 四川师范学院学报(自然科学版), 2002, 23(3):282-285.
	TAO Yuhui. How to make fuzzy consistent judgement matrix of the FAHP[J]. Journal of Sichuan Teachers College (Natural Sciene), 2002, 23(3): 282-285.
[25]	兰继斌, 徐扬, 霍良安, 等. 模糊层次分析法权重研究[J]. 系统工程理论与实践, 2006, 26(9):107-112. doi: 10.12011/1000-6788(2006)9-107
	LAN Jibing, XU Yang, HUO Liang'an, et al. Research on the priorities of fuzzy analytical hierarchy process[J]. Systems Engineering-Theory & Practice, 2006, 26(9): 107-112. doi: 10.12011/1000-6788(2006)9-107

权重	有机碳含量	压力系数	含气量	储层埋深	优质储层钻遇长度	压裂段数	施工液量	加砂强度
主体北区	0.036	0.043	0.011	0.040	0.487	0.168	0.402	0.055
主体南区	0.067	0.114	0.052	0.334	0.002	0.004	0.391	0.084
东区	0.006	0.598	0.004	0.091	0.258	0.217	0.146	0.064
西区	0.021	0.224	0.032	0.064	0.051	0.417	0.529	0.079
西南区	0.024	0.082	0.046	0.181	0.012	0.062	0.010	0.055

标度	定义	说明
0.5	同等重要	两元素同等重要
0.6	稍微重要	一元素比另一元素稍微重要
0.7	明显重要	一元素比另一元素明显重要
0.8	重要得多	一元素比另一元素重要得多
0.9	极端重要	一元素比另一元素极端重要
0.1,0.2,0.3,0.4	反比较

权重	有机碳含量	压力系数	含气量	储层埋深	优质储层钻遇长度	压裂段数	施工液量	加砂强度
主体北区	0.126	0.116	0.116	0.073	0.168	0.189	0.116	0.095
主体南区	0.101	0.131	0.111	0.161	0.121	0.131	0.092	0.152
东区	0.074	0.176	0.138	0.118	0.116	0.184	0.088	0.106
西区	0.105	0.105	0.105	0.116	0.169	0.105	0.177	0.116
西南区	0.075	0.168	0.130	0.254	0.075	0.108	0.092	0.098