首页|King Fahd University of Petroleum and Minerals Researcher Highlights Recent Rese arch in Machine Learning (Improving Water- Based Drilling Mud Performance Using B iopolymer Gum: Integrating Experimental and Machine Learning Techniques)
King Fahd University of Petroleum and Minerals Researcher Highlights Recent Rese arch in Machine Learning (Improving Water- Based Drilling Mud Performance Using B iopolymer Gum: Integrating Experimental and Machine Learning Techniques)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from Dhahran, Saudi Arabia, by N ewsRx editors, the research stated, “Drilling through shale formations can be ex pensive and time-consuming due to the instability of the wellbore. Further, ther e is a need to develop inhibitors that are environmentally friendly.” Our news reporters obtained a quote from the research from King Fahd University of Petroleum and Minerals: “Our study discovered a cost-effective solution to th is problem using Gum Arabic (ArG). We evaluated the inhibition potential of an A rG clay swelling inhibitor and fluid loss controller in water-based mud (WBM) by conducting a linear swelling test, capillary suction timer test, and zeta poten tial, fluid loss, and rheology tests. Our results displayed a significant reduct ion in linear swelling of bentonite clay (Na-Ben) by up to 36.1% a t a concentration of 1.0 wt. % ArG. The capillary suction timer (C ST) showed that capillary suction time also increased with the increase in the c oncentration of ArG, which indicates the fluid-loss-controlling potential of ArG . Adding ArG to the drilling mud prominently decreased fluid loss by up to 50% . Further, ArG reduced the shear stresses of the base mud, showing its inhibitio n and friction-reducing effect. These findings suggest that ArG is a strong cand idate for an alternate green swelling inhibitor and fluid loss controller in WBM .”
King Fahd University of Petroleum and Mi neralsDhahranSaudi ArabiaAsiaCyborgsEmerging TechnologiesMachine Lea rning
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