Concentration Volume Fractal Model Research Articles

Delineation of the porphyry-skarn mineralized zones (NW Turkey) using concentration–volume fractal model

This study is carried out for delineation of the Tepeoba porphyry-skarn Cu-Mo ± Au mineralized zones at the Biga peninsula (NW Turkey) using the concentration–volume (C–V) fractal model. The power-law C–V relationships of Cu, Mo, and Au reveal five mineralized zones of Cu, three zones of Mo, and five zones for gold in the Tepeoba deposit. The main phase of the mineralization has average ore grades of 0.257% Cu, 0.357% Mo and 5.3083 ppm Au. Cu–Mo sulfide-rich hypogene ore zone overlain by mineralized oxidation zone are encompassed by three main alteration types, which are represented by biotite ± muscovite-K-feldspar, actinolite-albite and outer chlorite-epidote-calcite mineral associations occurring within the porphyritic microgranite and hornfels in the mine area. The delineated mineralization trend, based on the C–V fractal model, suggested that Cu and Mo enrichment zones were controlled by the same geochemical processes in the deposit due to their similar trends with the C–V log-log plot. Cu and Mo occurred mainly within the breccia zones along with stockwork veining at the contact between the hornfels and the biotite (±muscovite)-K-feldspar-altered Eybek microgranite. The main mineralization zone of Au developed in the oxidation zone due to of supergene enrichment processes.

Three-dimensional weights of evidence modelling of a deep-seated porphyry Cu deposit

Given the challenges in data acquisition and spatial modelling at the detailed exploration stage, it is difficult to develop a prospectivity model, particularly for disseminated ore deposits. Recently, the weights of evidence (WofE) method has demonstrated a high efficiency for modelling such deposits. In this study, we propose a framework for creating a three-dimensional (3D) WofE-based prospectivity model of the Nochoun porphyry Cu deposit in SE Iran. The input data include qualitative geological and quantitative geochemical information obtained from boreholes and field observations. We combine ordinary and fuzzy weights of evidence for integrating qualitative and quantitative exploration criteria in a 3D space constrained by a metallogenic model of the study area for identifying a deep-seated ore body. Ordinary weights of evidence are determined for geological data, including lithology, alteration, rock type and structure. Moreover, we determine the fuzzy weight of evidence for each class of the continuous geochemical models created based on the factors analysis of Fe, Mo and Zn concentration values derived from boreholes. We integrate the input evidential models using WofE and create the posterior probability model. We also determine anomalous voxels in the probability model using a concentration–volume fractal model and validate them using a prediction–volume plot and test boreholes. The modelling results indicate the efficiency of the posterior probability model in identifying the anomalous voxels representing copper mineralized rock volumes. We provide open source software for the proposed framework which can be used for exploring deep-seated ore bodies in other regions.Supplementary data: Python scripts for implementing the proposed framework and supplementary files including more details on the evidential models are available at https://github.com/intelligent-exploration/3D_WofE.

Typomorphic characteristics of pyrite: Criteria for 3D exploration targeting in the xishan gold deposit, China

This paper describes 3D modeling of exploration criteria derived from typomorphic characteristics of pyrite in the Xishan quartz vein-type gold deposit (China). The methodology consists of five steps: (1) modeling of orebody thickness and grade using ordinary kriging in longitudinal section; (2) analysis of major/trace element content of Au-bearing pyrite from each ore paragenetic stage; (3) analysis of thermoelectric parameters of Au-bearing pyrites and estimation of ore-forming temperatures and comparison with homogenization temperatures from fluid inclusion analysis; (4) 3D modeling of orebodies using surface geological mapping, mining tunnels in different levels, and a borehole dataset; and (5) 3D modeling of thermoelectricity coefficients and estimated temperatures from Au-bearing pyrites for exploration targeting via discrete smooth interpolation and concentration-volume fractal modeling. The results indicate that: (1) Au-bearing pyrites from four ore paragenetic stages record gradually decreasing temperatures from the earliest to the latest stages, and the frequencies of occurrence of pyrite crystal combination forms and element components are closely correlated with P-type values of pyrite; (2) orebodies Nos. 108–1 and 107 are continuous at depth and potential exploration targets of their continuations extend more than 700m downward from their present mining levels; whereas orebodies Nos. 55 and 108–2 discontinue at depth.

Multi-Gaussian kriging: a practice to enhance delineation of mineralized zones by Concentration–Volume fractal model in Dardevey iron ore deposit, SE Iran

The purpose of this study is to identify the effect of ordinary and simple multi-Gaussian kriging (oMK, sMK) estimation methods for the delineation of iron mineralized zones based on subsurface data using Concentration–Volume (C–V) fractal modeling in the Dardevey iron ore deposit, NE Iran. Spatial data analyses (variograms and anisotropic ellipsoid) were initially calculated for the Fe distribution. The C–V log–log plots based on the estimation methods represent the various mineralized zones via threshold values. Additionally, variance in the both methods was compared. The comparison and interpretation of the mineralized zones based on the C–V fractal modeling show that the methods are similar, but the enriched and highly zones resulted by the oMK have variances lower than the sMK method. Furthermore, the weakly and moderately mineralized zones have lower variances based on the sMK method. According to the comparison and variance, optimum threshold values for enriched, highly, moderately and weakly iron mineralized zones are 56%, 51%, 41% and 35%, respectively.

Outlining of high quality coking coal by concentration–volume fractal model and turning bands simulation in East-Parvadeh coal deposit, Central Iran

This study aims at identifying the proper parts of C1 and B2 coking coal seams in the North block of East-Parvadeh coal deposit (Central Iran) using the concentration–volume (C–V) fractal modeling according to sulfur and ash values which were calculated by turning bands conditional simulation. The C–V log–log plots were generated based on results of 100 realizations derived via turning bands simulation which show seven different geochemical populations for both sulfur and ash data in B2 seam which has a relatively good quality for coking coal with sulfur and ash values lower than 1.548% and 6.39% respectively. Additionally, C–V log–log plots indicate that there are seven and six for sulfur and ash geochemical populations in C1 seam containing a proper coal quality with respect to sulfur and ash values less than 1.41% and 6.92% respectively. High quality populations are located in the northern and western parts of the studied area which correlated with USGS standard. The logratio matrix was used for the correlation between results obtained by the C–V fractal modeling and geological particulars consisting of pyritic veins and ash coals. Based on the logratio matrix for sulfur values higher than 3.55% and 3.39% for C1 and B2, respectively, low quality parts of the seams have good correlation with pyritic veins in the eastern and central parts of the area. Moreover, there are high values of overall accuracy (OA) for correlation between parts of the seams with high values of ash which are 47.86% and 39.81% for C1 and B2, respectively, and ash coals obtained by geological data.

Delineation of alteration zones based on Sequential Gaussian Simulation and concentration–volume fractal modeling in the hypogene zone of Sungun copper deposit, NW Iran

The main aim of this study is the identification of potassic, phyllic and propylitic alteration zones in the hypogene zone of the Sungun Cu porphyry deposit (NW Iran) based on drillcore data, utilizing sequential geostatistical simulation (SGS) and concentration–volume (C–V) fractal model. C–V log–log plots were generated for the results obtained by 10 realizations and the average of those realizations (E-type) which was used for the determination of Cu threshold values for the alteration zones. Based on correlation between geological models and the results derived via SGS and C–V fractal modeling by log ratio matrix, the propylitic zone has Cu values <0.005% as a result of simulation numbers (sims) 1, 5 and 9 with overall accuracy (OA) of 0.94. Additionally, the phyllic alteration contents of Cu values between 0.25% and 0.63% with OA of 0.70 are delineated by E-type. Moreover, a correlation between C–V fractal modeling of realizations and the potassic alteration zone derived via the geological model reveals that this alteration zone has Cu values higher than 2.23% (sims 1, 5 and 9) with OA of 0.816. The results of this research reveal that phyllic alteration due to having many existing geological samples with the grades close to the average ore grade (0.44%) of the Sungun deposit has a proper overlap with E-type; however, potassic and propylitic alterations containing the highest and lowest ore grades have a strong overlap with sims 1, 5 and 9.

Correlation between geology and concentration-volume fractal models: significance for Cu and Mo mineralized zones separation in the Kahang porphyry deposit (Central Iran)

Abstract This study identifies the major mineralized zones including supergene enrichment and hypogene enrichment in the Kahang Cu-Mo porphyry deposit which is located in Central Iran based on subsurface data and utilization of the concentration-volume (C-V) fractal model. Additionally, a correlation between results achieved from a C-V fractal model and geological models consisting of zonation, mineralography and alteration have been conducted in order to have an accurate recognition and modification of the main mineralized zones. Log-log plots indicate five geochemical populations for Cu and Mo in the deposit which means that mineralization commences with 0.075 % and 13 ppm for Cu and Mo (as the first thresholds) respectively. The main mineralization began for Cu ≥ 0.42 % and Mo ≥ 100 ppm and also enriched mineralization containing Cu ≥1.8 % and Mo ≥ 645 ppm which is located in the central part of the deposit. According to the C-V model, the main Cu-Mo mineralized zones occur in the hypogene zone, especially in the central, NW and NE parts of the Kahang deposit. The supergene enrichment zone derived via the C-V model is smaller than that in the geological model and is located in the central and eastern parts of the deposit. Results analysed by the C-V fractal model certify that the interpreted zones based on the fractal model are accurate. To certify this, a logratio matrix has been employed to validate the C-V fractal model for the Cu and Mo main mineralized zones