Thermal maturity and TOC prediction using machine learning techniques: case study from the Cretaceous–Paleocene source rock, Taranaki Basin, New Zealand

• Published in: Journal of Petroleum Exploration and Production Technology
• Main Authors: Mohamed Ragab Shalaby, Owais Ahmed Malik, Daphne Lai, Nurhazwana Jumat, Md Aminul Islam
• Format: Article in Journal/Newspaper
• Language: English
• Published: SpringerOpen 2020
• Subjects: Machine learning; Neural networks; Random forest; Support vector machine; Linear regression; Well-logging; Petroleum refining. Petroleum products; TP690-692.5; Petrology; QE420-499; New Zealand; North Cape
• Online Access: https://doi.org/10.1007/s13202-020-00906-4; https://doaj.org/article/74efff3ddfd3437bbcec35582a218786

Abstract Thermal maturity, organic richness and kerogen typing are very important parameters to be evaluated for source rock characterization. Due to the difficulties of high cost geochemical analyses and the unavailability of rock samples, it was necessary to examine and test many different method...