الفهرس 
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Abstract
This thesis demonstrated a petrophysical study on a field in Iraq using the wireline well logging applications and data analytics synchronization using machine learning regression method. Going through the Wireline conventional logs (Triple Combo) and unconventional logs such as CMR porosity (TCMR), bound fluid volume (BFV), free fluid volume (CMFF), Schlumberger doll research permeability (KSDR) and Timur-Coates permeability (KTIM) which were used in nuclear magnetic resonance (NMR) petrophysical evaluation of three wells were set. Well logging dataset consisted of Gamma Ray (GR), resistivity with multiple depths of investigation, neutron porosity and bulk density are used for conventional well logging formation evaluation techniques such as shale volume calculation (Vsh), total porosity (PHIT), effective porosity (PHIE), total water saturation (SWT), effective water saturation (SWE) calculations. Neutron and bulk density were used for lithology computation using Neu-Den Cross plots.