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Source rock characterization is one of the important approaches in the field of geophysics and petroleum geology. The source rock characterization in a sedimentary basin is economically crucial in conventional and unconventional hydrocarbon resources. This investigation uses the integration of seismic data inversion methods and geochemical data to evaluate an accurate total organic carbon (TOC) of the Kazhdumi Formation in the NW of the Persian Gulf. The Kazhdumi Formation with Cretaceous age is an important source rock in the NW of the Persian Gulf and Zagros region. The main purpose of this study is to evaluate the TOC content as one of the important geochemical parameters of the Kazhdumi Formation by integrating pre- and post-seismic inversion results, and well logs analysis. This study uses the artificial neural network (ANN) algorithm and well logs e.g., sonic, neutron, density, gamma-ray, and resistivity to evaluate the TOC log along with the Rock-Eval pyrolysis to analyze the actual data. The performance of the ANN algorithm was evaluated using correlation analysis as a cross-validation method by the bind core data sample. The simultaneous, and model-based seismic inversion methods were evaluated in the studied oil field, and the obtained results of seismic inversion methods were evaluated by well logs. The seismic data inversion attributes and the TOC log from the well logs analysis were used in the TOC volume evaluation procedure. Integrating seismic inversion attributes with high lateral resolution and well log with high vertical resolution creates a more accurate TOC value than the conventional methods. The multi-attribute regression (MAR) and artificial neural network (ANN) methods were utilized to estimate the TOC volume of the Kazhdumi Formation, and The obtained results of the MAR and ANN methods of RMSE analysis values are 0.1456 and 0.1098, respectively. The correlation of evaluated TOC between the actual TOC and TOC values using the ANN method based on the seismic inversion attributes is 0.89. The obtained results and data evaluation procedure of this investigation can provide useful information for the geological and geochemical studies in this oil field.
Source rock characterization is one of the important approaches in the field of geophysics and petroleum geology. The source rock characterization in a sedimentary basin is economically crucial in conventional and unconventional hydrocarbon resources. This investigation uses the integration of seismic data inversion methods and geochemical data to evaluate an accurate total organic carbon (TOC) of the Kazhdumi Formation in the NW of the Persian Gulf. The Kazhdumi Formation with Cretaceous age is an important source rock in the NW of the Persian Gulf and Zagros region. The main purpose of this study is to evaluate the TOC content as one of the important geochemical parameters of the Kazhdumi Formation by integrating pre- and post-seismic inversion results, and well logs analysis. This study uses the artificial neural network (ANN) algorithm and well logs e.g., sonic, neutron, density, gamma-ray, and resistivity to evaluate the TOC log along with the Rock-Eval pyrolysis to analyze the actual data. The performance of the ANN algorithm was evaluated using correlation analysis as a cross-validation method by the bind core data sample. The simultaneous, and model-based seismic inversion methods were evaluated in the studied oil field, and the obtained results of seismic inversion methods were evaluated by well logs. The seismic data inversion attributes and the TOC log from the well logs analysis were used in the TOC volume evaluation procedure. Integrating seismic inversion attributes with high lateral resolution and well log with high vertical resolution creates a more accurate TOC value than the conventional methods. The multi-attribute regression (MAR) and artificial neural network (ANN) methods were utilized to estimate the TOC volume of the Kazhdumi Formation, and The obtained results of the MAR and ANN methods of RMSE analysis values are 0.1456 and 0.1098, respectively. The correlation of evaluated TOC between the actual TOC and TOC values using the ANN method based on the seismic inversion attributes is 0.89. The obtained results and data evaluation procedure of this investigation can provide useful information for the geological and geochemical studies in this oil field.
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