Petroleum Reservoir Evaluation and Development >
2021 , Vol. 11 >Issue 4: 597 - 604
DOI: https://doi.org/10.13809/j.cnki.cn32-1825/te.2021.04.016
Quantitative analysis on drilling and completion loss factors by all data in Shunbei Oilfield
Received date: 2021-05-08
Online published: 2021-08-19
The analytical method and other qualitative research methods to guide the field leakage prevention and plugging lack of pertinence. Meanwhile, the engineering data used by the quantitative prediction method in the prediction of leakage is incomplete and how to control the leakage quantitatively by adjusting the relevant parameters is not proposed after the loss degree is predicted. In order to solve the above problems, the cocoon stripping algorithm is proposed. Selecting all measurement parameters of 27 of 29 wells in Shunbei Oilfield with average loss rate recorded, and then taking the average loss rate as the objective function, the well depth and drilling and completion fluid density as the independent variables, the multiple linear regression equation is established, and the undetermined coefficients of the equation are solved. Theoretically, T test and F test are used to prove that the equation can meet the requirements of engineering analysis. In practice, the relative error between the calculated value and the actual value of two wells that did not participate in the equation establishment is about 6 %, proving that the equation meets the needs of engineering control. Finally, 17 factors affecting the average loss rate have been screened out by the target equation simplified by the contribution rate method and the cutting element method, among which 10 drilling fluid factors contribute more than 50 %, indicating that a certain average loss rate could be controlled by adjusting the performance of drilling fluid. For the convenience of field control, the performance of drilling fluid is changed by the reading of six-speed viscometer at 300 r/min, so that the main controlling parameters of drilling fluid are reduced to two, which are pH value and the reading of six-speed viscometer at 300 r/min. The minimum average loss is predicted to be 2.3 m3/h through the analysis of the three-element equation. Considering the characteristics of Shunbei block, the leakage in Shunbei oilfield involves geological, engineering, and other operation links is found out through quantitative analysis, and so does the main controlling factors of drilling and completion leakage. By means of cutting elements, contribution rate and other methods, the minimum average leakage rate obtained by controlling the funnel viscosity and the reading of six-speed viscometer at 300 r/min is calculated. In the aspect of guiding the field practice of plugging leakage, it can provide basic data support for the subsequent construction measures to obtain the ideal leak control effect, and provide an optional means for decision-making.
Lihui ZHENG , Yandong XU , Ziyao QIU , Yunpeng GENG , Shengwei DONG , Xumin YANG . Quantitative analysis on drilling and completion loss factors by all data in Shunbei Oilfield[J]. Petroleum Reservoir Evaluation and Development, 2021 , 11(4) : 597 -604 . DOI: 10.13809/j.cnki.cn32-1825/te.2021.04.016
| [1] | 李冬梅, 柳志翔, 李林涛, 等. 顺北超深断溶体油气藏完井技术[J]. 石油钻采工艺, 2020, 42(5):600-605. |
| [1] | LI Dongmei, LIU Zhixiang, LI Lintao, et al. Well completion technologies for the ultra-deep fault-dissolved oil and gas reservoir in Shunbei Oil and Gas Field[J]. Oil Drilling & Production Technology, 2020, 42(5):600-605. |
| [2] | 冯英, 王骁男. 杭锦旗工区井漏机理分析与防漏堵漏技术[J]. 西部探矿工程, 2017, 29(10):82-85. |
| [2] | FENG Ying, WANG Xiaonan. Analysis of lost circulation mechanism and lost circulation prevention and plugging technology in Hangjinqi work area[J]. Western Exploration Engineering, 2017, 29(10):82-85. |
| [3] | 李占军. 大港油田南部油区防漏堵漏机理与对策[J]. 中国石油石化, 2017, 20(10):113-114. |
| [3] | LI Zhanjun. Mechanism and countermeasures of leak prevention and plugging in southern Dagang Oilfield[J]. China Petrochem, 2017, 20(10):113-114. |
| [4] | 李宁, 李龙, 王涛, 等. 库车山前盐膏层与目的层漏失机理分析与治漏措施研究[J]. 广州化工, 2020, 48(11):101-103. |
| [4] | LI Ning, LI Long, WANG Tao, et al. Leakage mechanism analysis and leakage control measures of salt gypsum layer and target layer in front of Kuqa mountain[J]. Guangzhou Chemical Industry, 2020, 48(11):101-103. |
| [5] | 郑力会, 吴通, 陶秀娟, 等. 稳定井壁封堵材料分类的研究进展[J]. 石油机械, 2021, 49(4):1-9. |
| [5] | ZHENG Lihui. WU Tong, TAO Xiujuan, et al. Progress of research on classification of plugging materials for stabilizing borehole wall[J]. China Petroleum Machinery, 2021, 49(4):1-9. |
| [6] | 王海彪. 井漏智能识别及处理决策研究[D]. 成都:西南石油大学, 2017. |
| [6] | WANG Haibiao. Study of intelligent recognition and management decisions of lost circulation[D]. Chengdu: Southwest Petroleum University, 2017. |
| [7] | 刘彪, 李窚晓, 李双贵, 等. 基于支持向量回归的井漏预测[J]. 钻采工艺, 2019, 42(6):17-20. |
| [7] | LIU Biao, LI Chenxiao, LI Shuanggui, et al. Lost circulation prediction based on support vector regression[J]. Drilling and Production Technology, 2019, 42(6):17-20. |
| [8] | HOU X X, YANG J, YIN Q S, et al. Lost circulation prediction in South China Sea using machine learning and big data technology[C]// Paper OTC-30653-MS presented at the Offshore Technology Conference, 4-7 May, 2020, Houston, Texas, USA. |
| [9] | SABAH M, TALEBKEIKHAH M, AGIN F, et al. Application of decision tree, artificial neural networks, and adaptive neuro-fuzzy inference system on predicting lost circulation: A case study from Marun oil field[J]. Journal of Petroleum Science and Engineering, 2019, 177:236-249. |
| [10] | LI Z J, CHEN M, JIN Y, et al. Study on intelligent prediction for risk level of lost circulation while drilling based on machine learning [C]// Paper ARMA-2018-105 presented at the 52nd U.S. Rock Mechanics/Geomechanics Symposium, Seattle, Washington, June 2018. |
| [11] | AL-HAMEEDI A T, ALKINANI H H, NORMAN S D, et al. Insights into mud losses mitigation in the Rumaila Field, Iraq[J]. Journal of Petroleum & Environmental Biotechnology, 2018, 9(1):1-10. |
| [12] | 郑力会, 张莉, 张广清, 等. 低碳有机酸盐水溶液成本数学模型及其应用[J]. 江汉石油学院学报, 2004, 26(1):71-73. |
| [12] | ZHENG Lihui, ZHANG Li, ZHANG Guangqing, et al. Mathematical model of low carbon organic salt aqueous solution cost and its application[J]. Journal of Jianghan Petroleum Institute, 2004, 26(1):71-73. |
| [13] | ZHENG L H, WANG J F, LI X P, et al. Optimization of rheological parameter for micro-bubble drilling fluids by multiple regression experimental design[J]. Journal of Central South University of Technology, 2008, 15(s1):424-428. |
| [14] | REN Y W, NIE S S, DUAN B J, et al. A novel method for quantitative analysis of engineering factors influencing CBM production[J]. International Journal of Engineering and Technical Research, 2016, (1):1-10. |
| [15] | 聂帅帅. 储层伤害控制参数剥茧方法构建[D]. 北京:中国石油大学(北京), 2018. |
| [15] | NIE Shuaishuai. A method for prediction, diagnosis and control of reservoir damage[D]. Beijing: China University of Petroleum(Beijing), 2018. |
| [16] | 郑力会, 刘皓, 曾浩, 等. 流量替代渗透率评价破碎性储层工作流体伤害程度[J]. 天然气工业, 2019, 39(12):74-80. |
| [16] | ZHENG Lihui, LIU Hao, ZENG Hao, et al. Evaluation of working fluid damage in fractured reservoir using flow rate instead of permeability[J]. Natural Gas Industry, 2019, 39(12):74-80. |
| [17] | 陶杉, 余星, 宋海, 等. 大数据方法寻找顺北碳酸盐岩储层开采过程中井壁坍塌主控因素[J]. 石油钻采工艺, 2020, 42(5):627-631. |
| [17] | TAO Shan, YU Xing, SONG Hai, et al. Application of the big data method to search for the main factors controlling the hole collapse in the production process of Shunbei carbonate reservoir[J]. Petroleum Drilling and Production Technology, 2020, 42(5):627-631. |
| [18] | 范胜, 宋碧涛, 陈曾伟, 等. 顺北5-8井志留系破裂性地层提高承压能力技术[J]. 钻井液与完井液, 2019, 36(4):431-436. |
| [18] | FAN Sheng, SONG Bitao, CHEN Zengwei, et al. Technology for enhancing pressure bearing capacity of fractured silurian system in Well Shunbei 5-8[J]. Drilling Fluid & Completion Fluid, 2019, 36(4):431-436. |
| [19] | 黄知娟, 潘丽娟, 路辉, 等. 大数据分析顺北油田SHB-X井试采产液量骤降原因[J]. 石油钻采工艺, 2019, 41(3):341-347. |
| [19] | HUANG Zhijuan, PAN Lijuan, LU Hui, et al. The reasons for sudden production drop by big data analysis in trial production for Well SHB-X in Shunbei oilfield[J]. Oil Drilling & Production Technology, 2019, 41(3):341-347. |
| [20] | 李昌盛. 基于多元回归分析的钻速预测方法研究[J]. 科学技术与工程, 2013, 13(7):1740-1744. |
| [20] | LI Changsheng. Study of method for predict rate of penetration based of multiple regression analysis[J]. Sience Technology and Engineering, 2013, 13(7):1740-1744. |
| [21] | 王越之, 邝明聪. 用曲线回归确定钻井液的流变模式[J]. 钻井液与完井液, 1993, 10(2):11-13. |
| [21] | WANG Yuezhi, KUANG Mingcong. Selecting Rheological model for drilling fluid by curvilinear regrssion method[J]. Drilling Fluid & Completion Fluid, 1993, 10(2):11-13. |
| [22] | 郑力会, 李秀云, 苏关东, 等. 煤层气工作流体储层伤害评价方法的适宜性研究[J]. 天然气工业, 2018, 38(9):28-39. |
| [22] | ZHENG Lihui, LI Xiuyun, SU Guandong, et al. Applicability of working fluid damage assessment methods for coalbed methane reservoirs[J]. Natural Gas Industry, 2018, 38(9):28-39. |
| [23] | WANG J F, ZHENG L H, LI B W, et al. A novel method applied to optimize oil and gas well working fluids[J]. International Journal of Engineering and Technical Research, 2016, 5(1):2454-4698. |
| [24] | 樊建明, 屈雪峰, 王冲, 等. 鄂尔多斯盆地致密储集层天然裂缝分布特征及有效裂缝预测新方法[J]. 石油勘探与开发, 2016, 43(5):740-748. |
| [24] | FAN Jianming, QU Xuefeng, WANG Chong, et al. Natural fracture distribution and a new method predicting effective fractures in tight oil reservoirs in Ordos Basin, NW China[J]. Petroleum Exploration & Development, 2016, 43(5):740-748. |
| [25] | 刘敏, 曲鹏飞, 郭华才. 考虑多因素影响的钻井液漏失模型[J]. 中国石油和化工标准与质量, 2020, 40(24):32-34. |
| [25] | LIU Min, QU Pengfei, GUO Huacai. Drilling fluid loss model considering multiple factors[J]. China Petroleum and Chemical Standard and Quality, 2020, 40(24):32-34. |
| [26] | 郑力会, 鄢捷年, 陈勉, 等. 油气井工作液成本控制优化模型[J]. 石油学报, 2005, 26(4):102-105. |
| [26] | ZHENG Lihui, YAN Jienian, CHEN Mian, et al. Optimization model for cost control of working fluids in oil and gas wells[J]. Acta Petrolei Sinica, 2005, 26(4):102-105. |
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