Application of fractal models for determining the relationship between REEs and faults in North Kochakali coal deposit, Central Iran.

The purpose of this research is to use the Concentration-Distance (C-D) fractal model to determine the relationship between the concentrations of ƩREEs and faults in coal seams of the North Kochakali coal deposit. For this purpose, three Concentration-Distance fractal models including: ƩREEC-DDF, ƩREEC-DSF, and ƩREEC- DTF were created based on ƩREEs concentrations and the distance from dextral, sinistral, and thrust faults, respectively. Four different geochemical populations were obtained according to fractal diagrams.

Electrical facies of the Asmari Formation in the Mansouri oilfield, an application of multi-resolution graph-based and artificial neural network clustering methods.

Electrofacies analysis conducted the distribution effects throughout the reservoir despite the difficulty of characterizing stratigraphic relationships. Clustering methods quantitatively define the reservoir zone from non-reservoir considering electrofacies. Asmari Formation is the most significant reservoir of the Mansouri oilfield in SW Iran, generally composed of carbonate and sandstone layers.

Hydraulic flow unit and rock types of the Asmari Formation, an application of flow zone index and fuzzy C-means clustering methods.

Rock types are the reservoir's most essential properties for special facies modeling in a defined range of porosity and permeability. This study used clustering techniques to identify rock types in 280 core samples from one of the wells drilled in the Asmari reservoir in the Mansouri field, SW Iran. Four hydraulic flow units (HFUs) were determined for studied data utilizing histogram analysis, normal probability analysis, and the sum of squared errors (SSE) statistical methods.