应力敏感性差异对天然裂缝储层直井产能的影响

Abstract

Abstract:

In order to study the productivity characteristics of low permeability reservoirs with natural fractures, we established a prediction model of natural fractured reservoir productivity considering stress sensitivity differences between matrix and natural fractures based on the theory of plane radial flow. After that, we derived the productivity equation of natural fracture reservoir considering the difference of matrix and natural fracture stress sensitivity. Then taking the basic data of the low permeability oilfield as an example, we calculated and analyzed the influence of fracture parameters, matrix stress sensitivity coefficient and crack stress sensitivity coefficient on productivity by the productivity equation above. The results showed that with the increase of matrix stress sensitivity coefficient, the oil well productivity decreased. When the crack width was small, the stress sensitivity of fractures had a significant impact on the oil production. Therefore, in the low permeability reservoirs with natural fractures, increasing the length of the fractures and linking more microcracks would be beneficial to the increase of production.

Key words: low permeability reservoir, natural fracture, productivity equation, fracture parameters, matrix stress sensitivity coefficient, fracture stress sensitivity coefficient

CLC Number:

TE31

Jun Cao,Hai Tang,Dongliang Lyu, et al. Influence of stress sensitive differences on natural well productivity in fractured reservoirs[J]. Reservoir Evaluation and Development, 2019, 9(1): 23-28.

Figures/Tables 8

Fig. 1

Fig. 2

Fig. 3

Table 1

Comparison of different models of production capacity"

预测模型	产能公式	产量/（m³·d^-1）
未考虑应力敏感（模型1）	$Q = 2 π h (p e - p wf) μ K 1 ln r e r 2 + μ K 1 + n w f K f 2 π r 2 ln r 2 r w ln r 2 r w B o$	166.25
本文模型	$q 1 = 2 π h K 1 {[1 - e - a 1 (p e - p 1)] - a 1 G e - a 1 (p e - p_) (r e - r 2)} a 1 μ B o ln r e r 2 q 2 = K f 0 × K f 0 8.33 × 105 13 n 3 a 2 1 - e - 4 a 2 3 (p 1 - p wf) B o μ (r 2 - r w) + 2 π h K 1 [1 - e - a 1 (p 1 - p wf)] μ B o ln r 2 r w$	103
未考虑天然裂缝（模型2）	$Q = 2 π h K 1 {[1 - e - a 1 (p e - p wf)] - a 1 G e - a 1 (p e - p_) (r e - r w)} a 1 μ B o ln r e r w p_= p e + p wf 2$	68.2

Table 1

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References 21

[1]	李芳芳, 高旺来, 杨胜来 , 等. 安塞油田高 52 区低渗油藏储层敏感性研究[J]. 特种油气藏, 2012,19(4):126-129. doi: 10.3969/j.issn.1006-6535.2012.04.032
[2]	张用德 . 深层高压低渗透油藏渗流机理研究[D].北京: 中国地质大学(北京), 2015: 1-184.
[3]	肖文联, 李滔, 李闽 , 等. 致密储集层应力敏感性评价[J]. 石油勘探与开发, 2016,43(1):1-8. doi: 10.11698/PED.2016.01.13
[4]	蒋利平, 李茂, 姜平 , 等. 低流度油藏考虑启动压力和压敏效应的渗流特征[J]. 大庆石油地质与开发, 2011,30(6):88-93. doi: 10.3969/J.ISSN.1000-3754.2011.06.018
[5]	雷刚, 董睿涛, 杨书 , 等. 致密砂岩气藏垂直压裂井拟稳态流动产能分析[J]. 大庆石油地质与开发, 2014,33(1):170-174. doi: 10.3969/J.ISSN.1000-3754.2014.01.033
[6]	王军磊, 贾爱林, 位云圭 , 等. 启动压力梯度对致密气动态储量评价的影响[J]. 大庆石油地质与开发, 2013,32(6):165-169. doi: 10.3969/J.ISSN.1000-3754.2013.06.034
[7]	杨朝蓬, 高树生, 刘广道 , 等. 致密砂岩气藏渗流机理研究现状及展望[J]. 科学技术与工程, 2012,12(32):125-131. doi: 10.3969/j.issn.1671-1815.2012.32.026
[8]	兰林, 康毅力, 陈一建 , 等. 储层应力敏感性评价实验方法与评价指标探讨[J]. 钻井液与完井液, 2005,22(3):1-4. doi: 10.3969/j.issn.1001-5620.2005.03.001
[9]	齐亚东, 战剑飞, 李晓明 , 等. 特低渗透砂岩储层应力敏感性实验[J]. 科技导报, 2012,30(3):49-52. doi: 10.3981/j.issn.1000-7857.2012.03.007
[10]	焦春艳, 何顺利, 谢全 , 等. 超低渗透砂岩储层应力敏感性实验[J]. 石油学报, 2011,32(3):489-494. doi: 10.7623/syxb201103018
[11]	李传亮 . 应力敏感对油井产能的影响[J]. 西南石油大学学报(自然科学版), 2009,31(1):170-172. doi: 10.3863/j.issn.1674-5086.2009.01.041
[12]	吴克柳, 李相方, 胥珍珍 , 等. 考虑变启动压降的异常高压气藏新产能方程[J]. 大庆石油地质与开发, 2012,31(5):74-78. doi: 10.3969/J.ISSN.1000-3754.2012.05.015
[13]	任俊杰, 郭平, 汪周华 . 考虑变渗透率模量的压敏油藏产能计算模型[J]. 大庆石油地质与开发, 2012,31(5):65-68. doi: 10.3969/J.ISSN.1000-3754.2012.05.013
[14]	张志伟, 刘卫东, 孙灵辉 , 等. 等效裂缝渗流模型在天然裂缝储层产能预测中的应用[J]. 科技导报, 2010,28(14):56-58. doi: 10.1360/972009-1380
[15]	张楠, 王晓琴, 徐锋 , 等. 启动压力梯度和应力敏感效应对低渗透油藏直井产能的影响[J]. 特种油气藏, 2012,19(1):74-77. doi: 10.3969/j.issn.1006-6535.2012.01.017
[16]	徐新利 . 含微裂缝低渗透储层应力敏感性及其对产能的影响[J]. 特种油气藏, 2015,22(1):127-130. doi: 10.3969/j.issn.1006-6535.2015.01.030
[17]	董利飞, 岳湘安, 徐星 , 等. 不同渗透率油藏储层应力敏感性实验研究[J]. 地质科技情报, 2015,34(6):155-158.
[18]	何更生, 唐海 . 油层物理[M]. 北京: 石油工业出版社, 2011: 64-65.
[19]	吴婷婷, 卢晓敏, 张烈辉 , 等. 水平井产能计算新方法[J]. 科学技术与工程, 2014,14(9):20-24. doi: 10.3969/j.issn.1671-1815.2014.09.004
[20]	李敬松, 刘汝敏, 吴茵 , 等. 致密气藏压胀松动井产能预测模型[J]. 大庆石油地质与开发, 2017,36(3):163-167. doi: 10.3969/J.ISSN.1000-3754.2017.03.029
[21]	李小益, 刘德华 . 应力敏感实验评价结果与开发特征矛盾分析[J]. 大庆石油地质与开发, 2016,35(6):63-67. doi: 10.3969/J.ISSN.1000-3754.2016.06.012

Influence of stress sensitive differences on natural well productivity in fractured reservoirs

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