•  
  •  
 

Coal Geology & Exploration

Abstract

In recent years, the research on the automatic performance testing technology for drilling fluids has achieved significant progress both domestically and internationally. However, automatic drilling fluid testing instruments face challenges, such as high costs, complicated structures, and restricted working environments. Given these challenges, this study developed an automatic online testing instrument for the funnel viscosity and density of drilling fluids. The testing instrument consists of mud pumping, testing, cleaning, and control modules, which are built using a programmable logic controller (PLC), an Internet of things (IoT) module, a pressure sensor, an ultrasonic sensor, a peristaltic mud pump, an electric ball valve, and a diaphragm pump. It can fulfill functions including the automatic funnel viscosity and density testing of drilling fluids, and the data viewing and operation at the mobile terminal. This study enhanced the accuracy and stability of the testing instrument through sensor data fusion and filtering algorithms. The testing instrument was employed to test the performance of various drilling fluid systems, yielding funnel viscosity and density errors controlled at ±1 s and ±0.01 g/cm3, respectively. Furthermore, it allowed for continuous automatic performance testing for drilling fluids. The laboratory and field testing results suggest that the testing instrument boasts convenient operations, accurate testing results, high repeatability, minimal manual measurement errors, and labor saving. Therefore, it meets the demand for performance testing of drilling fluids in practical drilling construction, demonstrating high universality and great potential for application.

Keywords

drilling fluid, automatic testing, funnel viscosity, density

DOI

10.12363/issn.1001-1986.23.06.0384

Reference

[1] 崔学兵,胡中志,柳忠彬,等. 钻井液性能在线监测技术研究进展[J]. 中国石油和化工标准与质量,2023,43(10):177−179.

CUI Xuebing,HU Zhongzhi,LIU Zhongbin,et al. Research progress of online monitoring technology for drilling fluid performance[J]. China Petroleum and Chemical Standard and Quality,2023,43(10):177−179.

[2] 李贵红,赵佩佩,吴信波. 煤层气地质工程一体化平台的建设构想[J]. 煤田地质与勘探,2022,50(9):130−136.

LI Guihong,ZHAO Peipei,WU Xinbo. Construction concept of integrated geological engineering platform for coalbed methane[J]. Coal Geology & Exploration,2022,50(9):130−136.

[3] 陈明. 钻井液密度和粘度自动连续测量系统设计应用[D]. 大庆:东北石油大学,2017.

CHEN Ming. Design and application of automatic continuous measurement system for density and viscosity of drilling fluid[D]. Daqing:Northeast Petroleum University,2017.

[4] 张峰,乌效鸣,吴川,等. 泥浆性能检测系统设计[J]. 传感器与微系统,2015,34(7):57−59.

ZHANG Feng,WU Xiaoming,WU Chuan,et al. Design of mud property detection system[J]. Transducer and Microsystem Technologies,2015,34(7):57−59.

[5] 张志财,刘保双,王忠杰,等. 钻井液性能在线监测系统的研制与现场应用[J]. 钻井液与完井液,2020,37(5):597−601.

ZHANG Zhicai,LIU Baoshuang,WANG Zhongjie,et al. Development and field application of an online drilling fluid property monitoring system[J]. Drilling Fluid & Completion Fluid,2020,37(5):597−601.

[6] 孙浩玉,周延军,刘海东. 变径异型管式钻井液流变性在线监测装置研究与应用[J]. 中外能源,2019,24(12):49−54.

SUN Haoyu,ZHOU Yanjun,LIU Haidong. Research and application of online monitoring device for rheology of drilling fluid with the type of altered–diameter shaped tube[J]. Sino–Global Energy,2019,24(12):49−54.

[7] 孙浩玉. 钻井液性能参数在线监测系统[J]. 中外能源,2020,25(增刊1):38.

SUN Haoyu. Online monitoring system for drilling fluid performance parameters[J]. Sino–Global Energy,2020,25(Sup.1):38.

[8] 熊安华. 钻井液密度传感器影响因素及校验方法探讨[J]. 西部探矿工程,2022,34(4):73−75.

XIONG Anhua. Discussion on influencing factors and calibration method of drilling fluid density sensor[J]. West–China Exploration Engineering,2022,34(4):73−75.

[9] 王鹏,刘伟,张果. 钻井液性能自动监测装置的现状及改进建议[J]. 钻采工艺,2022,45(3):42−47.

WANG Peng,LIU Wei,ZHANG Guo. Status quo and improvement suggestions of automatic monitoring equipment for drilling fluid performance[J]. Drilling and Production Technology,2022,45(3):42−47.

[10] 蒋官澄,董腾飞,崔凯潇,等. 智能钻井液技术研究现状与发展方向[J]. 石油勘探与开发,2022,49(3):577−585.

JIANG Guancheng,DONG Tengfei,CUI Kaixiao,et al. Research status and development directions of intelligent drilling fluid technologies[J]. Petroleum Exploration and Development,2022,49(3):577−585.

[11] LYSYANNIKOV A,KONDRASHOV P,PAVLOVA P. Means and method for measurement of drilling fluid properties[J]. IOP Conference Series:Materials Science and Engineering,2016,132:012014.

[12] 陈现军,郭书生,张志财. 钻井液性能在线监测技术在南海钻井施工中的应用[J]. 录井工程,2022,33(2):73−77.

CHEN Xianjun,GUO Shusheng,ZHANG Zhicai. Application of the on–line monitoring of drilling fluid performance in Nanhai Sea drilling operations[J]. Mud Logging Engineering,2022,33(2):73−77.

[13] 梁海波,宋洋,于志刚,等. 钻井液流变性实时测量方法及系统研究[J]. 石油机械,2022,50(1):10−18.

LIANG Haibo,SONG Yang,YU Zhigang,et al. Real–time measurement method and systematic study on drilling fluid rheology[J]. China Petroleum Machinery,2022,50(1):10−18.

[14] 李垚,梁升平,居迎军,等. 国外钻井工具与仪器新进展及国内发展建议[J]. 钻探工程,2022,49(5):145−155.

LI Yao,LIANG Shengping,JU Yingjun,et al. New advances in drilling tools and instruments abroad and suggestions for domestic development[J]. Drilling Engineering,2022,49(5):145−155.

[15] 吴尤. 页岩气录井技术进展及展望[J]. 钻探工程,2022,49(5):171−176.

WU You. Progress and prospect of shale gas mud–logging technologies[J]. Drilling Engineering,2022,49(5):171−176.

[16] 张勇,张长亮,李江,等. 钻井液自动在线测量技术和应用介绍[J]. 石油化工自动化,2021,57(增刊1):141−145.

ZHANG Yong,ZHANG Changliang,LI Jiang,et al. Technology and application introduction of automatic on–line measurement for drilling fluid[J]. Automation in Petro–Chemical Industry,2021,57(Sup.1):141−145.

[17] 陈强,顾彬彬,李鹏. 超声波雪深测量回波信号的卡尔曼滤波建模方法[J]. 电子器件,2020,43(2):439−444.

CHEN Qiang,GU Binbin,LI Peng. Kalman filter modeling method for echo signal of ultrasonic snow depth measurement[J]. Chinese Journal of Electron Devices,2020,43(2):439−444.

[18] BRODIE I. An evaluation of a multi–day rainfall–runoff volume– peak discharge transform for flood frequency estimation[J]. Australasian Journal of Water Resources,2020,24(2):167−182.

[19] 刘改芹,李哲,李永喜. 马氏漏斗黏度计容量校准方法探讨[J]. 工业计量,2020,30(5):76−79.

LIU Gaiqin,LI Zhe,LI Yongxi. Discussion on the volume calibration method of martensitic funnel viscometer[J]. Industrial Measurement,2020,30(5):76−79.

[20] 刘保双,王忠杰,马云谦,等. 钻井液流变性在线检测新方法[J]. 钻井液与完井液,2016,33(4):56−59.

LIU Baoshuang,WANG Zhongjie,MA Yunqian,et al. New method of online measurement of drilling fluid rheology[J]. Drilling Fluid & Completion Fluid,2016,33(4):56−59.

[21] 陈德飞,孟祥娟,康毅力,等. 气体吸附对煤层安全钻井液密度的影响[J]. 煤田地质与勘探,2017,45(1):152−157.

CHEN Defei,MENG Xiangjuan,KANG Yili,et al. The influence of gas adsorption on the density of drilling fluid[J]. Coal Geology & Exploration,2017,45(1):152−157.

[22] 王敏生,光新军. 智能钻井技术现状与发展方向[J]. 石油学报,2020,41(4):505−512.

WANG Minsheng,GUANG Xinjun. Status and development trends of intelligent drilling technology[J]. Acta Petrolei Sinica,2020,41(4):505−512.

[23] SAASEN A,OMLAND T H,EKRENE S,et al. Automatic measurement of drilling fluid and drill–cuttings properties[J]. SPE Drilling & Completion,2009,24(4):611−625.

[24] 王华,乔鹏. 公路定额测定异常数据剔除方法研究[J]. 中外公路,2013,33(6):354−356.

WANG Hua,QIAO Peng. Research on the exclusion method of abnormal data for highway quota determination[J]. Journal of China & Foreign Highway,2013,33(6):354−356.

[25] 杨景宏,冯立辉,郭军强,等. 基于超声波测距的自适应双足绑式惯性导航算法研究[J]. 自动化与仪器仪表,2022(5):1−5.

YANG Jinghong,FENG Lihui,GUO Junqiang,et al. Research on adaptive dual foot–mounted inertial navigation algorithm based on ultrasonic ranging[J]. Automation & Instrumentation,2022(5):1−5.

[26] 朱红运,苗岩松,庞建国. 基于卡尔曼滤波的遥测数据野值剔除方法[J]. 航天返回与遥感,2021,42(4):137−143.

ZHU Hongyun,MIAO Yansong,PANG Jianguo. An outliers elimination method of telemetry data based on Kalman filter[J]. Spacecraft Recovery & Remote Sensing,2021,42(4):137−143.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.