{"id":7776,"date":"2025-04-13T23:52:44","date_gmt":"2025-04-13T20:52:44","guid":{"rendered":"https:\/\/en.coeng.uobaghdad.edu.iq\/?p=7776"},"modified":"2025-04-13T23:52:44","modified_gmt":"2025-04-13T20:52:44","slug":"college-of-engineering-at-the-university-of-baghdad-discusses-a-ph-d-dissertation-titled-estimating-of-in-situ-strength-of-rock-from-real-time-drilling-data-using-conventional-regression-an","status":"publish","type":"post","link":"https:\/\/en.coeng.uobaghdad.edu.iq\/?p=7776","title":{"rendered":"College of Engineering at the University of Baghdad Discusses a Ph.D. Dissertation Titled: \u201cEstimating of in-Situ Strength of Rock from Real Time Drilling Data using Conventional Regression Analysis and Machine Learning\u201d"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]<\/p>\n

On Thursday, February 27, 2025, the College of Engineering at the University of Baghdad held a public defense for the Ph.D. dissertation submitted by the student Doaa Ali Saleh from the Department of Petroleum Engineering, titled:<\/p>\n

\u201cEstimating of in-Situ Strength of Rock from Real Time Drilling Data using Conventional Regression Analysis and Machine Learning\u201d<\/p>\n

The defense was supervised by Prof. Dr. Eyad Abdul-Haleem Abdul-Razzaq, and took place in the postgraduate hall of the Petroleum Engineering Department.<\/p>\n

The discussion committee consisted of the following esteemed members:<\/p>\n

    \n
  1. Dr. Ghassan Hameed Abdul-Majeed \u2013 University of Baghdad, College of Engineering, Production Engineering \u2013 Chair<\/li>\n
  2. Dr. Manal Shakir Ali \u2013 University of Baghdad, College of Science, Earth Sciences \u2013 Member<\/li>\n
  3. Dr. Rafeed Kadhim Abbas \u2013 University of Al-Qadisiyah, College of Engineering, Chemical Engineering \u2013 Member<\/li>\n
  4. Prof. Dr. Sameera Mohammed Hamdallah \u2013 University of Baghdad, College of Engineering, Reservoir Engineering \u2013 Member<\/li>\n
  5. Prof. Dr. Hassan Abdul-Hadi Abdul-Hussein \u2013 University of Baghdad, College of Engineering, Drilling Engineering \u2013 Member<\/li>\n
  6. Dr. Eyad Abdul-Haleem Abdul-Razzaq \u2013 University of Baghdad, College of Engineering, Drilling Engineering \u2013 Member and Supervisor<\/li>\n<\/ol>\n

    Study Objective:<\/p>\n

    To develop advanced methods for estimating key geomechanical properties (such as Young\u2019s modulus, rock strength, friction angle, and pore pressure) and to enhance the efficiency and stability of drilling operations in the Rumaila oil field. The study also aimed to employ artificial intelligence and mathematical modeling to analyze real-time drilling data.<\/p>\n

    Study Summary:<\/p>\n

    New empirical equations were developed to accurately estimate Young\u2019s modulus for carbonate, sandstone, and shale formations, reducing evaluation costs. The most suitable predictive equations for rock strength were identified for each geological formation using data from 12 wells. An artificial neural network (ANN) model was developed to estimate rock strength in real time with an accuracy exceeding 90%. Another ANN model was created to predict mud loss rate based on drilling variables and mud properties, with a high predictive accuracy (R = 0.995). The concept of Specific Mechanical Energy (SME) was applied to enhance drilling efficiency, resulting in an increase in the rate of penetration by up to 80% and a reduction in total drilling time by up to 50%.<\/p>\n

    Finally, the study provided effective and reliable alternatives to traditional methods, improving performance, reducing costs, and enhancing borehole stability.<\/p>\n

    After an extensive scientific discussion by the committee and hearing the student\u2019s defense and evaluation of the dissertation, the committee decided to award the student a Ph.D. in Petroleum Engineering, wishing her continued success in her academic and research journey.[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_gallery interval=”3″ images=”7778″ img_size=”large” css=””][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"

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