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Enregistrement W2599283420 · doi:10.22067/econg.v8i2.60499

Geology, Geochemistry and Ground Magnetic Survey on Kalateh Naser Iron Ore Deposit, Khorasan Jonoubi Province

2017· article· en· W2599283420 sur OpenAlexaboutno aff

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueGeological and Geochemical Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeochemistryGeologyMagnetic surveyMining engineeringIron oreArchaeologyMagnetic anomalyGeographyGeophysics

Résumé

récupéré en direct d'OpenAlex

Introduction Ground magnetometer surveys is one of the oldest geophysical exploration methods used in identifying iron reserves. The correct interpretation of ground magnetic surveys, along with geological and geochemical data will not only reduce costs but also to indicate the location, depth and dimensions of the hidden reserves of iron (Robinson and Coruh, 2005; Calagari, 1992). Kalateh Naser prospecting area is located at 33° 19َ to 33° 19ََ 42" latitude and 60° 0' to 60° 9َ 35" longitude in the western side of the central Ahangaran mountain range, eastern Iran (Fig.1). Based on primary field evidences, limited outcrops of magnetite mineralization were observed and upon conducting ground magnetic survey, evidence for large Iron ore deposits were detected (Saadat, 2014). This paper presents the geological and geochemical studies and the results of magnetic measurements in the area of interest and its applicability in exploration of other potential Iron deposits in the neighboring areas. Materials and methods To better understand the geological units of the area, samples were taken and thin sections were studied. Geochemical studies were conducted through XRF and ICP-Ms and wet chemistry analysis. The ground magnetic survey was designed to take measurements from grids of 20 meter apart lines and 10 meter apart points along the north-south trend. 2000 points were measured during a 6-day field work by expert geophysicists. Records were made by Canadian manufactured product Magnetometer Proton GSM19T (Fig. 2). Properties of Proton Magnetometer using in magnetic survey in Kalateh Naser prospecting area is shown in Table 1. Total magnetic intensity map, reduced to pole magnetic map, analytic single map, first vertical derivative map and upward continuation map have been prepared for this area. Results The most significant rock units in the area are cretaceous carbonate rocks (Fig. 3). The unit turns to shale and thin bedded limestone in the central part and into red and white crystalline limestone towards the west, which sometimes can be referred as marble and skarn (Figs. 4, 5 and 6; Saadat, 2014). Iron mineralization is mostly observed in these units. Acidic to intermediate intrusive bodies consisting hornblende quartz monzonite, biotite granodiorite, pyroxene quartz diorite have outcrops in the north and northwestern part of the area (Fig. 3). Outcrops from andesite to dacite volcanic rocks in combination with ultra-mafic rocks can be seen in the southern part of the region. The geochemical results indicated F2O3 value range of %31 to %96. P2O5 of maximum %0.45 was observed and TiO2 varied from %0.02 to %0.54 (Tables 2 and 3 and Figs 7, 8 and 9). The highest values of iron and copper are found in the northern part, titanium and phosphorus are located in the southern part and manganese and vanadium are placed in the central sector. According to the obtained results, the highest magnetic susceptibility was associated with the skarn units and was measured at 34000*10-5 SI which is related to the mineralization of Iron in the area. Magnetic susceptibility of limestone crystalline units were close to 50*10-5 SI and marble was less than 10* 10-5 SI which highlights the influence of iron mineralization in the carbonates rocks. This value was around 80*10-5 SI for intrusive rocks such as hornblende quartz monzonite in the area (Table 4). Ground magnetic studies suggest minimum of 40000 nT and maximum of 70000 nT total magnetic intensity in the area (Fig. 10-A; Ryahei, 2013). Utilizing the Reduced to Pole Magnetic Filter is to locate the anomalies in the study area (Fig. 11-A). Since magnetic declination causes a degree of deviation between the source and magnetic anomalies, the said filter is applied to magnetic data and ultimately, analysis is done based on the magnetic data transferred to the pole (Nakatsuka and Okuma, 2006; Clark, 1997). The results of reduce to pole magnetic map for this area yielded three large and two small magnetic anomalies (Figs 12-A and 12-B). The upward continuation maps were taken with 5m, 10m, 20m, 30m, 40m, and 50m. Smaller anomalies tend to disappear more comparing the 5m to 20m continuation maps respectively, and a homogenous large anomaly starts to form in the 50m map (Fig. 13). Large and clear anomalies continue to be present in the 50m continuation map and only two smaller anomalies are disappeared from the west of the area (Ryahei, 2013). Discussion The results of geological, geochemical and magnetic susceptibility measurements indicate that magnetic anomalies in the Kalate-Naser area is related to the iron mineralization in this area. Lower amount of magnetic susceptibility in intrusive mass outcrops also indicate that these intrusive rocks did not play the main role in iron mineralization and were in fact have been weakly altered. It can only be concluded that the intrusive mass that led to mineralization sits beneath, at a higher depth. The initial geophysical survey results are closely comparable to the powder drilling trials that confirm magnetite mineralization to the named depth (Saadat, 2014). Thus far, 1.5 Million ton of Iron ore deposits have been confirmed in the area and exploration continues during production. The obtained results once again highlight the importance of ground magnetic surveys that combined with other exploration methods can reduce costs, increase efficiency and simplify the exploration process. Methodology and results of the magnetic measurements conducted in Kalateh Naser can help to better understand the magnetite bodies in the neighboring areas. Acknowledgement Hereby, I would like to thank my colleagues particularly, Ryahi, Shokri, Madani, Ebrahimzadeh, Salari, Maldar family, Ghoorchi, amongst others that assisted with field visits, mapping, processing and data analysis. References Calagari, A.A., 1992. Principals of geophysics exploration. Tabesh press, Tabriz, 588 pp. Clark. D.A., 1997, Magnetic petrophysics and magnetic petrology: aids to geological interpretation of magnetic surveys. Journal of Australian Geology and Geophysics, 17(2): 83-103. Nakatsuka, T. and Okuma S., 2006. Reduction of magnetic anomaly observations from helicopter surveys at varying elevations. Exploration Geophysics, 37(1): 121-128. Robinson, E.S. and Coruh, C. (translated by Haydarian Shahri, M.R.), 2005. Basic exploration geophysics. Ferdowsi University of Mashhad Press, Mashhad, 750 pp. Ryahei, H., 2013. Magnetite data of Kalateh Naser prospecting area. Madan Yaran Lut Company, Mashhad, Internal report, Report 1, 17 pp. Saadat, S., 2014. Final exploration report of Kalateh Naser prospecting area. Madan Yaran Lut Company, Mashhad, Internal report, Report 3, 100 pp.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,064

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0030,002
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,128
Tête enseignante GPT0,427
Écart entre enseignants0,299 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2017
Routes d'admission1
Résumé présentoui

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