Open Journal of Geology

Volume 8, Issue 7 (July 2018)

ISSN Print: 2161-7570   ISSN Online: 2161-7589

Google-based Impact Factor: 0.83  Citations  h5-index & Ranking

Geostatistical Studies and Anomalous Elements Detection, Bardaskan Area, Iran

HTML  XML Download Download as PDF (Size: 1725KB)  PP. 697-710  
DOI: 10.4236/ojg.2018.87041    12,961 Downloads   15,262 Views  Citations

ABSTRACT

The aim of this study is geostatistical analysis and detection of anomalous elements in the Bardaskan area (in geological map of Bardaskan on scale 1:100,000 which is provided by the GSI organization). The study area is located in Khorasan province of Iran. Due to the availability of lithogeochemical regular data in the region as well as the importance of exploration of metal minerals in order to simplify and summarize the geochemical map, geostatistical methods were used to identify the mineralization potential of the region. Initially, using single-variable and multivariate statistical methods, anomalous elements were separated. Then, the thresholds (various communities) for the titanium element that was most likely to be anomalous were identified. Using these limits, the discriminant analysis was applied to the elements. Titanium, iron and magnesium elements were identified as the main mineral elements in the region. These elements indicate mineralization in the mafic bed rocks. Finally the map of the concentration of titanium element was mapped across the region with Kriging interpolation method. As a result, two anomalies of the titanium element in the region were identified.

Share and Cite:

Alahgholi, S. , Shirazy, A. and Shirazi, A. (2018) Geostatistical Studies and Anomalous Elements Detection, Bardaskan Area, Iran. Open Journal of Geology, 8, 697-710. doi: 10.4236/ojg.2018.87041.

Cited by

[1] Geophysical explorations by resistivity and induced polarization methods for the copper deposit, South Khorasan, Iran
Известия Томского …, 2022
[2] K-means clustering and general regression neural network methods for copper mineralization probability in Chahar-Farsakh, Iran
Türkiye Jeoloji …, 2022
[3] A Review of Mineralization of Rare Earth Elements in Iran
International Journal of …, 2022
[4] Feasibility of simultaneous application of fuzzy neural network and TOPSIS integrated method in potential mapping of lead and zinc mineralization in Isfahan …
Open Journal of …, 2022
[5] Multi-Dimensional Data Fusion for Mineral Prospectivity Mapping (MPM) Using Fuzzy-AHP Decision-Making Method, Kodegan-Basiran Region, East Iran
Minerals, 2022
[6] Assessment of the Influence of Sulfuric Acid/Hydrogen Peroxide Mixture on Organic Sulfur Reduction of High Sulfur Coals and Their Chemical Composition
Open Journal of …, 2022
[7] Geophysical Study to Identify Iron Mineralization Anomalies Using Terrestrial Magnetometry in the Chak-Chak Exploration Area, Iran
Türkiye Jeoloji …, 2022
[8] Analysis and interpretation of Ilorin aeromagnetic data, North—Central, Nigeria, using geostatistical techniques
Earth Science …, 2022
[9] Geochemical relations among elements in stream sediment samples from Siojan Prospecting Area, Iran using geostatistical methods
Ruhuna Journal of …, 2022
[10] Yenikapı M1–Kirazlı M1 hattı için istasyon ve hat bazlı yolcu talep tahmini ve raylı ulaşım sistemlerinde sefer sıklığı belirlemede kritik başarı faktörlerinin çok kriterli …
2022
[11] Türkiye Jeoloji Bülteni
İYE JEOLOJİ BÜLT …, 2022
[12] Geochemical behavior investigation based on k-means and artificial neural network prediction for titanium and zinc, Kivi region, Iran
2021
[13] Determination of Archie's Tortuosity Factor from Stoneley Waves in Carbonate Reservoirs
2021
[14] Geochemical and Behavioral Modeling of Phosphorus and Sulfur as Deleterious Elements of Iron Ore to Be Used in Geometallurgical Studies, Sheytoor Iron …
Open Journal of …, 2021
[15] Predict the Amount of Cu Using the Four Ca, Al, P, S Elements by Multiple Linear Regression Method
International Journal for …, 2021
[16] Investigation of Geochemical Sections in Exploratory Boreholes of Mesgaran Copper Deposit in Iran
International Journal for …, 2021
[17] Geophysical study: Estimation of deposit depth using gravimetric data and Euler method (Jalalabad iron mine, kerman province of IRAN)
2021
[18] ИССЛЕДОВАНИЕ ГЕОХИМИЧЕСКОГО ПОВЕДЕНИЯ ТИТАНА И ЦИНКА НА ОСНОВЕ МЕТОДА K-СРЕДНИХ И ИСКУССТВЕННЫХ НЕЙРОННЫХ СЕТЕЙ ДЛЯ …
2021
[19] Application of Remote Sensing in Earth Sciences–A Review
2021
[20] Hybrid fuzzy-analytic hierarchy process (AHP) model for porphyry copper prospecting in simorgh area, eastern lut block of Iran
Mining, 2021
[21] Investigation of magneto-/radio-metric behavior in order to identify an estimator model using K-means clustering and Artificial Neural Network (ANN)(Iron Ore …
Minerals, 2021
[22] Geostatistical and Remote Sensing Studies to Identify High Metallogenic Potential Regions in the Kivi Area of Iran
2020
[23] Introducing Geotourism Attractions in Toroud Village, Semnan Province, IRAN
2020
[24] Evaluation of Chromite Recovery from Shaking Table Tailings by Magnetic Separation Method
2020
[25] Minimalization of Ash from Iranian Gilsonite by Froth Flotation
2020
[26] Geochemical and Geostatistical Studies for Estimating Gold Grade in Tarq Prospect Area by K-Means Clustering Method
2019
[27] Copper Oxide Ore Leaching Ability and Cementation Behavior, Mesgaran Deposit in IRAN
2018
[28] Exploratory Geochemical Studies to Determine the Mineralization Zones Around the Zarshuran Gold Mine
International Journal of Science and Engineering Applications, 2018
[29] Exploratory Remote Sensing Studies to Determine the Mineralization Zones around the Zarshuran Gold Mine
International Journal of Science and Engineering Applications, 2018
[30] DCA Method in Mineral Exploration, Example: Predict the Location of New Samples
[31] Prediction of Copper Mineralization by the Artificial Neural Network (GRNN & BPNN) in Mesgaran Exploration Area, Eastern Iran

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.