Applicability evaluation technology of perforating parameters in different reservoirs

Authors

BI Gang, College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China; Shaanxi Key Laboratory of Well Stability and Fluid & Rock Mechanics in Oil and Gas Reservoirs, Xi’an 710065, ChinaFollow
WU Jiemin, College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China
YANG Shangyu, China Petroleum Engineering Materials Research Institute Co., Ltd., Xi’an 710077, China
LI Mengmeng, College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China
HAN Fei, College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China
WANG Xin, College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China
CUI Ying, College of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China

Abstract

Perforating parameters have an important impact on the productivity of oil and gas wells. Currently, the optimization of perforating parameters is mostly based on single factor analysis, with no multi-factor comprehensive evaluation analysis performed. In this paper, the finite element simulation method was used to analyze and study the influence law of perforating parameters on wellhead flow under different reservoir conditions. Firstly, a geometric model of pressure drop in reservoir with perforation completion was established to simulate the fluid flow after perforation. In this way, the influence laws of perforating parameters, anisotropy parameters and natural fracture parameters on the pressure and seepage fields of homogeneous reservoir, anisotropic reservoir and fractured reservoir were obtained. On this basis, the relationship between the parameters, such as hole depth, hole density, hole size, phase angle, pollution zone depth and pollution degree, and the wellhead flow was calculated quantitatively. Meanwhile, orthogonal experiment was designed for the multi-factor analysis of perforating parameters under different perforation modes in different reservoirs, and the wellhead flow under various working conditions was obtained. Then, the grey correlation coefficient between the parameters and wellhead flow under different reservoir conditions and different perforation methods was analyzed with the grey correlation theory. Then, the applicability of the parameters was evaluated, and the optimization design software of perforating parameters was formed. To ensure that the casing collapse resistance is reduced by no more than 5%, and to maximize the perforation completion productivity ratio, the perforation optimization scheme under different reservoirs and different perforation modes was given according to the actual perforating parameter combinations and the optimization of perforating parameters combined with F oilfield. Finally, the sensitivity analysis of perforating parameters was carried out, obtaining the influence law of perforation depth, phase angle and hole density on the productivity of directional well. With the increase of hole depth and density, the daily production and cumulative production of horizontal well gradually increases. Specifically, the daily production and cumulative production of well at 45° phase angle were both higher than that at the phase angle of 0°. Through the orthogonal experiment based on the finite element simulation, the multi-factor comprehensive evaluation of perforating parameters was realized, and the reliability of the weight of perforating parameters was improved with the grey correlation method. Generally, this study provides a basis for the reasonable range and optimization of perforating parameters.

Keywords

oil and gas reservoir, perforating parameter, grey correlation, productivity prediction, sensitivity analysis

DOI

10.12363/issn.1001-1986.22.11.0835

Recommended Citation

BI Gang, WU Jiemin, YANG Shangyu, et al. (2023) "Applicability evaluation technology of perforating parameters in different reservoirs," Coal Geology & Exploration: Vol. 51: Iss. 7, Article 10.
DOI: 10.12363/issn.1001-1986.22.11.0835
Available at: https://cge.researchcommons.org/journal/vol51/iss7/10

Reference

[1] 郑建东,王春燕,章华兵,等. 松辽盆地古龙页岩油储层七性参数和富集层测井评价方法[J]. 大庆石油地质与开发,2021,40(5):87−97.

ZHENG Jiandong,WANG Chunyan,ZHANG Huabing,et al. Logging evaluating methods of seven property parameters and enriched layers for Gulong shale oil reservoir in Songliao Basin[J]. Petroleum Geology & Oilfield Development in Daqing,2021,40(5):87−97.

[2] 李士斌,任伟,张立刚,等. 综合考虑孔眼稳定及产能情况的射孔参数优选[J]. 特种油气藏,2013,20(6):116−120.

LI Shibin,REN Wei,ZHANG Ligang,et al. Optimization of perforating parameters by taking account of hole stability and productivity[J]. Special Oil and Gas Reservoirs,2013,20(6):116−120.

[3] 徐兵祥,白玉湖,陈岭,等. 页岩气解析模型产量预测技术优化方案[J]. 科学技术与工程,2021,21(9):3571−3575.

XU Bingxiang,BAI Yuhu,CHEN Ling,et al. Optimization of production forecasting technique using analytical models for shale gas wells[J]. Science Technology and Engineering,2021,21(9):3571−3575.

[4] 文敏,邱浩,毕刚,等. 海上油气田双层套管射孔穿透性能研究[J]. 西安石油大学学报(自然科学版),2021,36(6):37−43.

WEN Min,QIU Hao,BI Gang,et al. Research on perforation penetration performance of double casing in offshore oil and gas fields[J]. Journal of Xi’an Shiyou University (Natural Science Edition),2021,36(6):37−43.

[5] 许杰,贾立新,陈毅,等. 海上稠油热采井套管射孔参数设计[J]. 中国海上油气,2020,32(3):118−123.

XU Jie,JIA Lixin,CHEN Yi,et al. Design of casing perforation parameters for offshore heavy oil thermal recovery wells[J]. China Offshore Oil and Gas,2020,32(3):118−123.

[6] 唐汝众,王同涛,闫相祯,等. 射孔参数对套管强度影响的有限元分析[J]. 石油机械,2010,38(1):32−34.

TANG Ruzhong,WANG Tongtao,YAN Xiangzhen,et al. Finite element analysis of the influence of perforating parameters on casing strength[J]. China Petroleum Machinery,2010,38(1):32−34.

[7] 肖遥,邓金根,刘伟,等. 射孔参数对热采井套管抗热应力能力影响分析[J]. 科学技术与工程,2020,20(13):5094−5100.

XIAO Yao,DENG Jingen,LIU Wei,et al. Analysis on the effect of perforating parameters on thermal stress resistance of thermal production casing[J]. Science Technology and Engineering,2020,20(13):5094−5100.

[8] 邓晗,谯世均,朱志强,等. 水平井射孔完井参数优化的正交试验法[J]. 中国石油和化工,2014(4):59−61.

DENG Han,QIAO Shijun,ZHU Zhiqiang,et al. Orthogonal test method for optimization of perforation and completion parameters of horizontal wells[J]. China Petroleum and Chemical Industry,2014(4):59−61.

[9] 薛世峰,王斐斐,王海静. 射孔井产率比及其影响因素数值分析[J]. 油气地质与采收率,2012,19(2):102−105.

XUE Shifeng,WANG Feifei,WANG Haijing. Numerical study of productivity ratio and factors of perforated well[J]. Petroleum Geology and Recovery Efficiency,2012,19(2):102−105.

[10] 李春红. 高效射孔工艺技术在三类储层的应用效果评价[J]. 化学工程与装备,2020(7):140−141.

LI Chunhong. Evaluation of application effect of efficient perforation technology in three types of reservoirs[J]. Chemical Engineering and Equipment,2020(7):140−141.

[11] 丁熊,谭秀成,雷一文,等. 基于模糊聚类分析的复杂碳酸盐岩储层定量评价[J]. 西安石油大学学报(自然科学版),2009,24(3):25−27.

DING Xiong,TAN Xiucheng,LEI Yiwen,et al. Quantitative evaluation of complex carbonate reservoir based on fuzzy clustering analysis[J]. Journal of Xi’an Shiyou University (Natural Science Edition),2009,24(3):25−27.

[12] 段宏跃,陆鹿,谢卫东,等. 基于灰色模糊模型的塔山煤矿构造复杂程度定量评价[J]. 地质与勘探,2022,58(2):420−429.

DUAN Hongyue,LU Lu,XIE Weidong,et al. Quantitative Assessment of Structural Complexity in the Tashan Coal Mine Based on the Grey Fuzzy Model[J]. Geology and Exploration,2022,58(2):420−429.

[13] 夏东领,伍岳,夏冬冬,等. 鄂尔多斯盆地南缘红河油田长8致密油藏非均质性表征方法[J]. 石油实验地质,2021,43(4):704−712.

XIA Dongling,WU Yue,XIA Dongdong,et al. Characterization method of heterogeneity for Chang 8 tight reservoir in Honghe Oilfield,Southern margin of Ordos Basin[J]. Petroleum Geology & Experiment,2021,43(4):704−712.

[14] 涂乙,刘伟新,戴宗,等. 基于熵权法的储层非均质性定量评价:以珠江口盆地A油田为例[J]. 油气地质与采收率,2017,24(5):27−33.

TU Yi,LIU Weixin,DAI Zong,et al. Quantitative evaluation for reservoir heterogeneity based on entropy weight method:A case study of A Oilfield in Pearl River Mouth Basin[J]. Petroleum Geology and Recovery Efficiency,2017,24(5):27−33.

[15] 李龙龙,吴明录,姚军,等. 部分射开直井的产能计算方法[J]. 石油钻探技术,2014,42(3):80−89.

LI Longlong,WU Minglu,YAO Jun,et al. Calculation method of the productivity of partially perforated vertical well[J]. Petroleum Drilling Techniques,2014,42(3):80−89.

[16] HAGOORT J. An analytical model for predicting the productivity of perforated wells[J]. Journal of Petroleum Science and Engineering,2007,56(4):199−218.

[17] RAKHIMZHANOVA A,THORNTON C,AMANBEK Y,et al. Numerical simulations of sand production in oil wells using the CFD–DEM–IBM approach[J]. Journal of Petroleum Science and Engineering,2022,208:109529.

[18] TATSIPIE N R K,SHENG J J. Deep learning–based sensitivity analysis of the effect of completion parameters on oil production[J]. Journal of Petroleum Science and Engineering,2022,209:109906.

[19] 吴见,汤达祯,李松,等. 鄂尔多斯盆地东缘煤储层孔隙结构特征差异及影响因素[J]. 煤田地质与勘探,2017,45(5):58−65.

WU Jian,TANG Dazhen,LI Song,et al. Characteristics and influence factors of pore structure of coal reservoirs in the Eastern margin of Ordos Basin[J]. Coal Geology & Exploration,2017,45(5):58−65.

[20] 张权. 双层油藏中部分射开直井不稳态渗流研究[D]. 北京：中国地质大学 (北京)，2017.

ZHANG Quan. Unsteady flow research of partially penetrated vertical well in double−layer oil reservoir[D]. Beijing：China University of Geosciences (Beijing)，2017.