The power law scaling, geometric and kinematic characteristic of faults in the Northern part of the Kerman Coal Province (KCP), Iran
Subject Areas : Mineralogy
Hasan
Mansouri
1
(Department of Geology, North Tehran Branch, Islamic Azad University, Tehran, Iran)
Amir
Shafiei Bafti
2
(Department of Geology, Zarand Branch, Islamic Azad University, Zarand, Iran)
Mohsen
Pourkermani
3
(Department of Geology, North Tehran Branch, Islamic Azad University, Tehran, Iran)
Keywords: Kerman coal province, Faulting density, Statistical analysis of faults, Scaling relationship,
Abstract :
According to numerous studies,there are basic and initial scaling relationship for the geometric and kinematic characteristics of faults. The study area is located in the northern part of the Kerman coal province. The statistical calculations are consisting of: measure the surface density of faults per unite area and division of the area, determining the direction of the dominant faulting and evaluating the relationship between length-displacement, strike-displacement and strike-length. Based on diagrams, the highest fracture density is related to the middle portion (B zone) of study area because that enclosed between the four main faults and sandstone rock assemblage. The relationship between strike-length parameter is calculated as (y=0.0478x + 11.54), and R-squared rate is (R=0.341), strike-displacement is calculated as (y=2.68x + 147.4) and R-squared rate is (R=0.65) and length-displacement is calculated as (y= 243.58 x0.0336) and R-squared rate is (R=0/022). It was determined that increasing the density of fractures and faulting in the study area can be attributed to the complex geological structure, the formation of initial faults and long term progressive deformation. Due to deformations accumulation and formations of multiple structures (like faults, folds and shear zones), have Increasing the fracture density, and topography, and has interacted with together. Comparison the length-strike and strike-displacement parameters, represents a similarity on the clustering in the plotted data Despite that they have many similarities to each other, does not show a dependable dependence, this may indicate their asynchronous creation.