چکیده مقاله
Pressure loss in drilling operations is one of the most critical hydraulic parameters that directly influences both efficiency and safety Improper control of pressure loss can lead to challenges such as reduced drilling performance, increased operational costs, and unexpected incidents In this study, pressure loss was analyzed and predicted using operational data from a drilling well, including multiple depth dependent parameters To achieve this, the CatBoost machine learning algorithm recognized as one of the most powerful models in the field of gradient boosting was employed The dataset was pre processed, cleaned, and divided into training, validation, and test sets for model development The results demonstrated that CatBoost achieved reliable predictions of pressure loss, with a low root mean square error RMSE and a high coefficient of determination R2 Furthermore, the feature importance analysis revealed that parameters such as flow rate and standpipe pressure exert the greatest influence on pressure loss These findings highlight the effectiveness of machine learning approaches in enhancing drilling operation management and underscore their potential for predictive applications under real world operational conditions
کلیدواژهها
نویسندگان
Sajad Dolati
Chemical Engineering Department / Tarbiat Modares University / Tehran / Iran
شیوه ارجاع
Dolati, Sajad,1404,Analysis of the Impact of Operational Parameters on Drilling Pressure Loss Using the CatBoost Model,Fourth International Congress for Chemical Engineering and Petroleum Industry students,Tehran
ارائهشده در
مجموعه مقالات چهارمین کنگره بین المللی دانشجویان مهندسی شیمی و صنعت نفت29 آبان 1404 · تهران