Effect of temperature on transport index of fish oil-based drilling mud in high pressure high temperature well: a hybrid model approach

被引:0
|
作者
Utthirapathy, Ashadevi [1 ]
Subbian, Sutha [1 ]
Jayaprakash, Jayapriya [2 ]
Arumugam, Ramaswamy [3 ]
机构
[1] Anna Univ, MIT Campus, Dept Instrumentat Engn, Chennai, India
[2] Anna Univ, Dept Appl Sci & Technol, AC Tech, Chennai, India
[3] Oil & Nat Gas Corp Ltd, Reg Geosci Lab, Chennai, India
关键词
Drilling; invert emulsion fish oil-based drilling mud; rheology; high; -pressure; -temperature; artificial neural network-nonlinear regression; hole cleaning; RHEOLOGICAL PROPERTIES; FORMULATION;
D O I
10.1080/01932691.2024.2428349
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Diesel Oil-based drilling mud used in the oil and gas industry causes severe environmental and public health issues due to its high toxicity, especially in high-pressure, high-temperature (HPHT) wells. Therefore, easily biodegradable synthetic oil-based mud with high drilling performance is essential. Fish oil is a bio-oil known for its non-toxicity, high lubricity, thermal stability, and biodegradability. Effective hole cleaning is crucial for drilling performance and is ensured by the rheological properties of drilling mud. While rheological parameter prediction can be performed using an artificial neural network (ANN) based model, such models often fail to provide accurate predictions for unseen data. In contrast, empirical models are more robust and facilitate generalization. This study aims at assessment of the suitability of invert emulsion fish oil-based drilling mud (IEFOBDM) in HPHT wells through evaluation of hole cleaning performance (HCP) using a hybrid approach that combines an ANN with nonlinear regression (NLR) for temperatures ranging from 40 degrees C to 80 degrees C.Firstly, an ANN model was developed considering mud weight, temperature, and shear rate. Secondly, the NLR model was used in the prediction of rheological parameters, namely, Yield point (YP) and Plastic viscosity (PV), based on the predicted shear stress from the ANN model. Finally, the performance metrics of the ANN-NLR rheological model were evaluated using the root mean square error (RMSE) and correlation coefficient (R2) and comparison made with the Single ANN rheological model. The results showed the outperformance of ANN-NLR model over the ANN model for rheological parameter prediction, with R2 values of (0.99) for YP and (1) for PV. The predicted PV and YP values were then used for evaluation of transport index (TI) for HCP analysis. The effect of temperature on TI analysis showed this with increase in temperature, TI also increased, indicating the proposed mud providing good HCP under HPHT conditions.
引用
收藏
页数:13
相关论文
共 50 条
  • [21] Artificial neural network model for predicting the density of oil-based muds in high-temperature, high-pressure wells
    Agwu, Okorie E.
    Akpabio, Julius U.
    Dosunmu, Adewale
    JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY, 2020, 10 (03) : 1081 - 1095
  • [22] Artificial neural network model for predicting the density of oil-based muds in high-temperature, high-pressure wells
    Okorie E. Agwu
    Julius U. Akpabio
    Adewale Dosunmu
    Journal of Petroleum Exploration and Production Technology, 2020, 10 : 1081 - 1095
  • [23] Improving Drilling-Operations Efficiency on an Ultranarrow-Margin High-Pressure/High-Temperature Managed-Pressure-Drilling Well With Use of a Mud Cap
    Oyovwevotu, Joy
    Low, Eric
    Nas, Steve
    SPE DRILLING & COMPLETION, 2014, 29 (03) : 311 - 322
  • [24] Experimental Optimization of High-Temperature-Resistant and Low Oil-Water Ratio High-Density Oil-Based Drilling Fluid
    Shen, Zhenzhen
    Zhang, Heng
    Yu, Xingying
    Wang, Mingwei
    Gao, Chaoli
    Li, Song
    Zhang, Haotian
    PROCESSES, 2023, 11 (04)
  • [25] Propagation of Measurement-While-Drilling Mud Pulse during High Temperature Deep Well Drilling Operations
    Li, Hongtao
    Meng, Yingfeng
    Li, Gao
    Wei, Na
    Liu, Jiajie
    Ma, Xiao
    Duan, Mubai
    Gu, Siman
    Zhu, Kuanliang
    Xu, Xiaofeng
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, 2013
  • [26] Shape memory resin with high temperature resistance for plugging fracture formations drilled with oil-based drilling fluid
    Zhao, Zhen
    Sun, Jinsheng
    Wang, Ren
    Liu, Fan
    Cheng, Rongchao
    Qu, Yuanzhi
    Hao, Huijun
    Bai, Yingrui
    Li, Yingying
    Geng, Yuan
    GEOENERGY SCIENCE AND ENGINEERING, 2024, 243
  • [27] Study on the coupling model of wellbore temperature and pressure during the production of high temperature and high pressure gas well
    Liu, Xiangkang
    Liu, Liming
    Yu, Zhaocai
    Zhang, Lin
    Zhou, Lang
    Zhang, Zheng
    Guo, Fang
    ENERGY REPORTS, 2022, 8 : 1249 - 1257
  • [28] ALC crystal oscillators based pressure and temperature measurement integrated circuit for high temperature oil well applications
    Bianchi, RA
    Karam, JMM
    Courtois, B
    IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 2000, 47 (05) : 1241 - 1245
  • [29] Evaluation of Claytone-ER as a novel rheological additive for enhancing oil-based drilling fluid performance under high-pressure high-temperature conditions
    Mahmoud, Ali
    Gajbhiye, Rahul
    Elkatatny, Salaheldin
    CLAYS AND CLAY MINERALS, 2025, 73
  • [30] Thermal stability of a vegetable oil-based thermal fluid at high temperature
    Gomna, Aboubakar
    N'Tsoukpoe, Kokouvi Edem
    Le Pierres, Nolwenn
    Coulibaly, Yezouma
    AFRICAN JOURNAL OF SCIENCE TECHNOLOGY INNOVATION & DEVELOPMENT, 2020, 12 (03): : 317 - 326