Maqola

Predicting filter cake thickness in drilling fluids using machine learning techniques

Minghui OUSchool of Big Data and Internet of Things, Chongqing Vocational Institute of Engineering, Jiangjin, Chongqing, 402260, ChinaMohammed Al-BahraRaman KumarFaculty of Engineering, Sohar University, PO Box 44, Sohar, PCI 311, OmanAshutosh PattanaikDepartment of Mechanical Engineering, School of Engineering and Technology, JAIN (Deemed to be University), Bangalore, Karnataka, IndiaHrushikesh SarangiDepartment of Mechanical Engineering, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha-751030, IndiaDeepak GuptaCentre for Promotion of Research, Graphic Era Deemed to be University, Dehradun, Uttarakhand-248002, IndiaVikram RaoMamurakhon ToshpulatovaDepartment of Mathematics and Teaching Methods in Primary Education, Tashkent State Pedagogical University named after Nizami, Bunyodkor street 27, Tashkent, UzbekistanVikasdeep Singh MannDepartment of Mechanical Engineering, Chandigarh Engineering College, Chandigarh Group of Colleges-Jhanjeri, Mohali 140307, Punjab, IndiaHeyder MhohamdiDepartment of computers Techniques engineering, College of technical engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, IraqUsama S. AltimariDepartment of Medical Laboratories Technology, AL-Nisour University College, Baghdad, IraqAseel SmeratComputer Technologies Engineering, Mazaya University College, Nasiriyah, IraqSamim SherzodFaculty of Engineering, Nangarhar University, Nangarhar, Afghanistan

Physics and Chemistry of the Earth Parts A/B/Cjournal2025en

ABI

Annotatsiya

Annotatsiya mavjud emas.

Mavzular

Drilling and Well Engineering Hydraulic Fracturing and Reservoir Analysis Oil and Gas Production Techniques

Identifikatorlar

DOI: 10.1016/j.pce.2025.104078

Iqtiboslar va manbalar

0 ta iqtibos71 ta foydalanilgan manba

Koʻrsatkichlar — AkademScholar · Tez orada