1 Analyzing organic richness of source rocks from well log data by using SVM and ANN classifiers: a case study from the Kazhdumi formation, the Persian Gulf basin, offshore Iran Vahid Bolandi 1 ; Ali Kadkhodaie 2,3 ; Reza Farzi 4 1. Faculty of Geosciences, Shahid Chamran University, Ahwaz, Iran 2. Department of Earth Science, Faculty of Natural Science, University of Tabriz, Tabriz, Iran 3. Department of Petroleum Engineering, Curtin University, Perth, Western Australia 4. School of Geology, University College of Science, University of Tehran, Tehran, Iran Abstract Determination of TOC is critical to the evaluation of every source rock unit. Methods which are dependent upon extensive laboratory testing are limited by the availability and integrity of the rock samples. Prediction of TOC (Total Organic Carbon) from well Log data being available for the majority of wells being drilled provides rapid evaluation of organic content, producing a continuous record while eliminating sampling issues. Therefore, the ideal method for determining the TOC fraction within source rock units would utilize common well log data. So a model was developed to formulate TOC values in the absence of laboratory TOC measurements from conventional well log data. Consequently, with the assistance of FL (Fuzzy Logic), TOC estimated from well log data with an overall prediction accuracy of 0.9425 for the test set. Following that TOC content of the Kazhdumi formation optimally has been divided into 4 zones using K-means cluster analysis, since searching for patterns is one of the main goals in data mining. There is a general increase in TOC from zone 1 to zone 4. The optimal number of zones has been detected by means of the knee method that finds the  Corresponding author: Tel: +98 912 638 3051 E-mail addresses: kadkhodaie_ali@tabrizu.ac.ir (A. Kadkhodaie), bolandi_v@yahoo.com (Vahid Bolandi), rezafarzi@akumni.ut.ac.ir (Reza Farzi)