Biological marker geochemistry of selected oils and possible
source rocks from central Alborz Basin
Mohammad Reza
Kamali
Research Institute of Petroleum Industry, Tehran, Iran
author
Ziba
Zamani
author
Mohammad
Moeinpour
author
Mahmoud
Memariani
author
Shahrzad
Akbarpour
author
text
article
2013
eng
Surface oil seeps from Alasht, Lapur and Jenesem share many compositional affinities including distributions and concentrations ofnormal alkanes, terpanes and steranes. These oils also show many similarities with that of Jurassic sediments (Shemshak Group, KlarizFormation) systematically sampled from the Galandrud Coal Mine. Recent geochemical studies in this area indicated that theShemshak Group is rich in organic matter and has potential to generate oil and chiefly gas. The Kalariz Formation here is composed of350 m of mudstones, siltstones and fine-grained sandstones with over 30 coal seams. This formation is thought to have sourced Alashtand Lapur oil seeps. GC and GC-MS chromatograms of Jenesem oil are unique and show no any similarities with that of abovementioned oils or the Shemshak Formation. This indicates that the Jenesem oil has been generated from a different source rock but itsorigin is still unknown.
Geopersia
University of Tehran
2228-7817
3
v.
1
no.
2013
1
9
https://geopersia.ut.ac.ir/article_31927_0f0709891c36a86ccd9b49a7e1a2830e.pdf
dx.doi.org/10.22059/jgeope.2013.31927
Palynomorphs’ response to sea-level fluctuations: a case study from
Late Cretaceous – Paleocene, Gurpi Formation, SW Iran
Bijan
Beiranvand
Exploration & Production Division, Research Institute of Petroleum Industry, Tehran, Islamic Republic of Iran
author
Ebrahim
Ghasemi-Nejad
Department of Geology, University College of Sciences, University of Tehran, Tehran, Iran
author
Mohammad Reza
Kamali
Exploration & Production Division, Research Institute of Petroleum Industry, Tehran, Islamic Republic of Iran
author
text
article
2013
eng
Statistical studies on Palynology contents of Late Cretaceous to Paleocene age Gurpi Formation in a surface section in Zagros Basin,SW Iran indicate changes in abundance, species diversity, ratio of Spiniferites to Cyclonephelium (S/C), palynological marine index(PMI) values and organic facies. These palynological variations clearly reflect fluctuations in relative sea-level and depositionalenvironment and can be used for recognition and differentiation of systems tracts and key horizons such as flooding surfaces andsequence boundaries. Dramatic increase in PMI, dinoflagellate species diversity and S/C ratio associated with sedimentary faciesparameters indicate a marine transgressive systems tract while, a reduced species diversity, lower S/C ratio and PMI value along withincrease in abundance of phytoclasts and degraded land-plant materials are characteristics of marine regression. The variation trends ofthe palynological parameters when consecutive indicate a complete cycle of relative sea-level change. Abundance of Spiniferites,Achomosphaera, Areoligera, and Cleistosphaeridium species and presence of peridiniacean dinoflagellate cysts show a warm Tethyan,upper bathyal to middle shelf environment of deposition for the Gurpi Formation. The nine depositional sequences identified here canbe correlated to the global third-order sea-level cycles. The main regional sequence surfaces like K180 (maximum flooding surface) inthe Late Cretaceous sequences (68Ma) in northeast of Arabian Plate are recognizable here.
Geopersia
University of Tehran
2228-7817
3
v.
1
no.
2013
11
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https://geopersia.ut.ac.ir/article_31928_14fd23c754ec2bd0da7dc9cb53cd962c.pdf
dx.doi.org/10.22059/jgeope.2013.31928
Late Devonian Fish micro-remains from Central Iran
Tahereh
Habibi
Department of Earth Science, Faculty of Science, Shiraz University, Shiraz, Iran
author
Mehdi
Yazdi
Department of Geology, Faculty of Science, University of Isfahan, Isfahan, Iran
author
Saina
Zarepoor
Department of Geology, Payame Noor University, Shiraz, Iran
author
Mahnaz
Parvanehnejad Shirazi
Department of Geology, Payame Noor University, Shiraz, Iran
author
text
article
2013
eng
Well exposed Famennian, mainly carbonate rocks of the Bahram Formation in the vicinity of Bagher Abad village, Central Iran,yielded chondrichthyan teeth some sarcopterygii and actinopterygii teeth and fragments. Three different genera were recognizedamong the chondrichthyan teeth represented by: Phoebodus turnerae, Ph. spp., Deihim mansureae (M2, M3), Stethacanthus sp..Acanthodian and sarcopterygians teeth and fragments include: Dipnoi indet., Onychodonthid tooth?, Osteichthyes bone andPaleonisciformes indet. This assemblage recovered from a shallow shelf environment on the northern margin of Gondwana during LateDevonian time.
Geopersia
University of Tehran
2228-7817
3
v.
1
no.
2013
25
34
https://geopersia.ut.ac.ir/article_31929_2ae0a670129cf0bc032101fccfc865d0.pdf
dx.doi.org/10.22059/jgeope.2013.31929
Groundwater level simulation using artificial neural network: a case
study from Aghili plain, urban area of Gotvand, south-west Iran
Manouchehr
Chitsazan
Faculty of Earth Sciences, Shahid Chamran University, Ahvaz, Iran
author
Gholamreza
Rahmani
Faculty of Earth Sciences, Shahid Chamran University, Ahvaz, Iran
author
Ahmad
Neyamadpour
Faculty of Earth Sciences, Shahid Chamran University, Ahvaz, Iran
author
text
article
2013
eng
In this paper, the Artificial Neural Network (ANN) approach is applied for forecasting groundwater level fluctuation in Aghili plain,southwest Iran. An optimal design is completed for the two hidden layers with four different algorithms: gradient descent withmomentum (GDM), levenberg marquardt (LM), resilient back propagation (RP), and scaled conjugate gradient (SCG). Rain,evaporation, relative humidity, temperature (maximum and minimum), discharge of irrigation canal, and groundwater recharge fromthe plain boundary were used in input layer while future groundwater level was used as output layer. Before training, the available datawere divided into three groups, according to hydrogeological characteristics of different parts of the plain surrounding, eachpiezometer. Therefore, FFN-LM algorithm has shown best result in the present study for all three hydrogeological groups. At last, toevaluate applied division, a unit network with all data and using LM algorithm was trained. Validation of the network shows thatdividing the piezometers into different groups of data and designing distinct networks gives more focus on simulating groundwaterlevel in the plain. The degree of accuracy of the ANN model in prediction is acceptable. Thus, it can be determined that ANN providesa feasible method in predicting groundwater level in Aghili plain.
Geopersia
University of Tehran
2228-7817
3
v.
1
no.
2013
35
46
https://geopersia.ut.ac.ir/article_31930_e3e6543579dc5ef8a302e7b1db9660d7.pdf
dx.doi.org/10.22059/jgeope.2013.31930
Groundwater contamination analysis using Fuzzy Water Quality index
(FWQI): Yazd province, Iran
Amir
Saberi Nasr
Faculty of Earth Science, Kharazmi University, Tehran, Iran
author
Mohsen
Rezaei
Faculty of Earth Science, Kharazmi University, Tehran, Iran
author
Majid
Dashti Barmaki
Faculty of Earth Science, Kharazmi University, Tehran, Iran
author
text
article
2013
eng
Fuzzy Water Quality Index (FWQI) was applied in order to assess the degree of drinking water resources in Yazd province, Iran. Thisstudy has also offered the creation of a new fuzzy water quality index (FWQI) to evaluate this tool’s applicability. 12 chemicalparameters including toxic and non-toxic heavy metals measured in 71 groundwater samples collected from drinking water resourcesin rural areas were used. In FWQI, input data are categorized into three linguistic terms (“Desirable” or “Low”, “Acceptable” or“Medium” and “Not-acceptable” or “High”) based on water quality standards for drinking water, Whereas the output data arecategorized into five classes (“Poor”, “Fair”, “Medium”, “Good” and “Excellent”) based on water quality index (WQI). The resultsshow that 8 groundwater samples were classified in the “Excellent” class with a certainty level of 5.33-76.67%, 41 samples in the“Good” group with a certainty level of 8.5-96.5%, 8 samples were in the “Medium” category with a certainty level of 14-93.5%, 1sample in the “Fair” level with a certainty level of 36.5%, and 13 samples were classified in the “Poor” class with a certainty level of54.8-81.5% for potable purposes. The proposed Index can be a useful tool to be used in decision-making and environmental.
Geopersia
University of Tehran
2228-7817
3
v.
1
no.
2013
47
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https://geopersia.ut.ac.ir/article_31931_1f366c80fbf823dee62f89e09c0e1af7.pdf
dx.doi.org/10.22059/jgeope.2013.31931
Multivariate statistical analyzing of chemical parameters of thermal
and non-thermal springs of Mahalat area in Iran
Feridon
Ghadimi
Arak University of Technology, Department of Mining Engineering, Arak, Iran
author
Mahmoud
Mirzaei
Department of Physics, Faculty of Science, Arak University, Arak, Iran
author
Mohammad
Ghomi
Arak University of Technology, Department of Mining Engineering, Arak, Iran
author
text
article
2013
eng
In this study multivariate statistical analysis are used to characterize relationships between hydrochemical properties ofthermal and non-thermal springs. Four factors for thermal waters and two for non-thermal springs were extracted basedon factor analysis. In thermal springs, the first factor showed high loading on Ca, Mg, Na and K and this factor wasinterpreted as leaching of cations in the rocks by meteoric thermal water. The second factor showed high loading on SO4and it was assumed to be extracted from gypsum dissolution. The third factor showed loading on HCO3 and it wasinterpreted to be caused by dissolution of limestone. The forth factor showed high loading on SiO2 and it was supposed tobe result of alteration of silicate minerals. The δ18O-enrichment with respect to the meteoric water line (MWL), confirmsthat thermal waters have been diluted by shallow waters with meteoric origin. Comparison of the chemistry of thermaland non-thermal springs and other evidences are indicative of an immature hydrothermal water system in Mahalat.Quartz and Chalcedony geothermometery show the range of 96oC to 131 oC temperature for the Mahalat reservoir.
Geopersia
University of Tehran
2228-7817
3
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1
no.
2013
57
68
https://geopersia.ut.ac.ir/article_31932_f06b6cb597a14e5ff76a7a13bea660e3.pdf
dx.doi.org/10.22059/jgeope.2013.31932
Chemical characteristics of biotite from Boroujerd Granitoid complex
(Middle Jurassic), Western Iran
Dariush
Esmaeily
Department of Geology, University College of Sciences, University of Tehran, Tehran, Iran
author
Reza
Maghdour-Mashhour
Department of Geology, University College of Sciences, University of Tehran, Tehran, Iran
author
Amir Ali
Tabbakh Shabani
Faculty of Earth Sciences, Kharazmi University, Tehran, Iran
author
text
article
2013
eng
Biotite samples from different units of Boroujerd Granitoid Complex (BGC) of the Sanandaj-Sirjan Zone, western Iran, have beenanalyzed by electron microprobe for major elements. Biotite analyses from three units of quartzdiorite, granodiorite and monzograniteof BGC have their own distinct non-overlapping compositional fields in the annite – siderophyllite – phlogopite – eastonitequadrilateral (ASPE), reflecting their host rock compositions. Biotite from each rock unit has an increasing trend of Al contents atalmost fixed Fe/(Fe+Mg) values. In quartzdiorite it shows an approximately constant range of Fe/(Fe+Mg) with a low to moderate Alcontent from 2.5 to 3 atoms per formula unit (apfu). Biotite from granodiorite exhibits a fairly wide range of Al values reaching up to3.32 apfu, at Fe/(Fe+Mg) from 0.6 to 0.7, whereas biotite from monzogranite have a relatively narrow range of Fe/(Fe+Mg) and totalAl values of limited range of 3.1 to 3.3 apfu. Biotite compositions from these two latter units considered to be derived entirely fromcrustal material, characterized by a remarkable increase in total Al at relatively high Fe contents. Biotite samples of quartzdioritesdefine a distinct and non-overlapping trend from those of granidiorites and monzogranites and hence interpreted to be derived from aparental magma with different composition. Calculation of log(XMg/XFe) ranges from -0.09 to -0.02 and most of samples fromquartzdiorite fall within weakly and moderately contaminated I-type field of log(XF/XOH) versus log(XMg/XFe) diagram, whereasthe other two units, containing biotites with log(XMg/ XFe)< -0.21, classified as strongly contaminated reduced I-type. Oxygenfugacity (log ƒO2) of -15.4 to -17.5 bars and ƒH2O of 200 to 560 bars were calculated for quartzdiorite. Likewise, log (ƒO2) of –17.66bars and water fugacity (ƒH2O) of 400 and 700 bars were also calculated for granodiorite and monzogranites respectively. In theFeO*–MgO–Al2O3 biotite discrimination diagram, biotite compositions from BGC are distributed between the calc-alkaline andperaluminous fields, i.e., biotite from the qaurtzdioritic rocks fall principally in the calc-alkaline field, whereas those from thegranodioritic and monzogranitic units plot almost exclusively in the peraluminous field consistent with their host rock nature
Geopersia
University of Tehran
2228-7817
3
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1
no.
2013
69
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https://geopersia.ut.ac.ir/article_31933_bce6807afd328d2f5c00977b02299ed5.pdf
dx.doi.org/10.22059/jgeope.2013.31933