Blar i Studentoppgaver (TN-IEP) på emneord "machine learning"
Viser treff 1-6 av 6
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Data Driven ROP Modeling - Analysis and Feasibility Study
(Masteroppgave/UIS-TN-IEP/2020;, Master thesis, 2020-07-15)Increasing the drilling speed in wells while maintaining the operational safety standards is a challenge that many Petroleum Engineers have undertaken. In recent years, high complexity wells (Horizontal, Extended Reach, ... -
Integrated Modelling and Simulation of Wellbore Heat Transfer Processes through High-level Programming, Sensitivity Analysis and Initial Approach with Machine Learning Predictive Models
(Masteroppgave/UIS-TN-IEP/2020;, Master thesis, 2020-06-30)During designing of downhole systems and selecting equipment and materials, engineers must consider in-situ conditions before taking decisions in order to be able to handle any operation in a safe and adequate manner. The ... -
Integration of Neural Networks and Wellbore Stability, a Modern Approach to Recognize Drilling Problems Through Computer Vision and Machine Learning
(Masteroppgave/UIS-TN-IEP/2019;, Master thesis, 2019-06-15)Cavings are an endless and valuable source of information when drilling operations is being performed. Multiple parameters can contribute to produce cavings which indicate that failure has occurred or is about to occur ... -
A LSSVR-PSO machine learning model for the estimation of reservoir porosity from petrophysical well logs
(Masteroppgave/UIS-TN-IEP/2020;, Master thesis, 2020-06-10)Reservoir porosity is a key parameter in the reservoir evaluation and geomechanics. To obtain accurate measurement of porosity can be time-consuming and expensive by core sampling or applying various well logging tools. ... -
Optimization of an Intelligent Autonomous Drilling Rig: Testing and Implementation of Machine Learning and Control Algorithms for Formation Classification, Downhole Vibrations Management and Directional Drilling
(Masteroppgave/UIS-TN-IEP/2019;, Master thesis, 2019-06-14)In recent years, considerable resources have been invested to explore applications for- and to exploit the vast amount of data that gets collected during exploration, drilling and production of oil and gas. Such data will ... -
The Application of Data Analytics and Machine Learning for Formation Classification and Bit Dull Grading Prediction
(Masteroppgave/UIS-TN-IEP/2019;, Master thesis, 2019-06-15)The oil and gas industry, especially its upstream part generates a massive amount of data. The proper data collection and processing are the vital elements of reducing the non-productive time and increasing the drilling ...