Prediction of thermal maturity by indirect methods using seismic attributes in the central part of the Persian Gulf

In this paper, a method is proposed for the prediction of thermal maturity in the source rock using indirect methods. The applied data are well logs (neutron, density, resistance, and acoustic) in 13 wells and seismic data in six oil and gas fields in the central part of the Persian Gulf. Well-logs and seismic data are much more abundant than geochemical data and cover an extensive area in the oil and gas fields. These properties compensate for the lack of geochemical data that are scattered and limited to a few wells. This study is carried out in two steps. First, the amount of thermal maturity in the Kazhdumi Formation is calculated from well logs and is presented as an index in each well. Data obtained from organic thermal evaluation analyses are used to validate the results of thermal maturity prediction. These data include Rock-Eval pyrolysis in two wells. Then, seismic data are processed and studied in two-dimensional sections at the location of the target fields. In this step, seismic attributes are extracted from the seismic data using the multi-attribute regression analysis method, and thermal maturity is calculated using these attributes. Prediction is performed by probabilistic neural network analysis, and a seismic section is extracted indicating variations in thermal maturity in the Kazhdumi Formation.