JOURNAL OF SCIENCE (UNIVERSITY OF TEHRAN) (JSUT)
Year:2009 | Volume:35 | Issue:2 (SECTION: GEOLOGY)|Papers Count:11

Stoneley wave velocity (Vst) which is a type of surface waves provides valuable information from hydrocarbon reservoirs. In this study Vst was predicted from well log data using neuro-fuzzy, Sugeno and Mamdani fuzzy inference systems, and then results of each intelligent system were combined by an intelligent committee machine (CMIS). A genetic algorithm was used for constructing CMIS. For this purpose a total of 3030 data points from two wells in Sarvak carbonate reservoir which have Vst and conventional well log data were utilized. These data were divided into two parts, one part included 2047 data points used for constructing intelligent models and the other part included 983 data points used for models testing.The results show that CMIS technique has been useful method for prediction of Vst in Sarvak Formation with correlation coefficient equals to 0.98 and mean squared error equals to 0.000096.

Incompatible elements ratios (Th/Ta, Th/Hf, Ta/Hf, Th/Yb and Ta/Yb) in volcanic rocks reflect the tectonomagmatic evolution of magmatic suites in different regions. On the basis of the behavior of these elements, the tectonic environment of Eocene volcanogenic rocks of South Kahrizak (South Tehran), were examined. Petrologic facies in this area are mainly composed of pyroclastics and acid to basic lava flows. In geochemical diagrams, rhyolite-trachyandesite and basalt lavas always plot within the active continental margin field with tendency toward within-plate volcanic zone, especially for basic rock units. Enrichment of light rare earth elements (LREE) compared to chondrites without Eu anomalies in basaltic rocks (unlike rhyolite and trachyandesite rocks) and similarity in rare elements ratio between Kahrizak rocks and some back arc environments, are geochemical evidences for the tendency of South Kahrizak rocks to a extensional region especially for basic and intermediate lavas. Volcanic rocks of this erea are enriched in incompatible elements relative to compositions such as depleted MORB mantle (DMM) or primitive mantle (PM). The distribution of metallic elements in these rocks, reveals that, they are more aboundant in basalts compared to rhyolites and intermediate rocks. Basaltic rocks also show enrichment in Co, Sc, Cu, Au, V and deplation in Pb, Ni, Zn, to some degree respect to continental lithosphere.

The objective of exploration seismology is to measure accurately reflected wavefields from subsurface interfaces in order to generate an image of the geological formations. More often the seismic data is non-uniformly sampled, i.e. the data is not acquired on an equidistantly spaced grid. This may result in artifacts during data processing that complicate interpretation. Sampling may be nonuniform because of human-related reasons such as: 1. Faulty equipment and positioning errors, 2. It may be due to environmental circumstances, such as cable feathering in marine acquisition induced by ocean currents or 3. Due to inaccessible areas in land acquisition (cities, rivers, and canyons).The generation of uniformly sampled data from nonuniformly sampled data is called reconstruction and many different methods to reconstruct seismic data have been published over the years. The method used in this paper is called reconstruction of nonuniformly sampled data with least squares Fourier transform. It is based on estimating the Fourier coefficients that describe the non-uniformly sampled data, and once these coefficients have been found the signal can be reconstructed on any suitable grid via an inverse Fourier transformation. The efficiency of the method is evaluated on both real and synthetic seismic. All necessary codes were written in MATLAB environment.

Permeability is one of the very important features of the oil and gas reservoirs, and usually it could provided by core analysis and well test which are expensive. Geophysical logs are one of the best tools for identification of petrophysical properties of reservoir, such as porosity and permeability. Most of the petrophysical parameters are directly related to a specific log. Whereas, permeability doesn’t correlate with any specific logs. Sonic, density, neutron, specific resistivity and GR logs and also photoelectrical index are important logs and indices to determine the permeability. It’s natural that all of the logs don't have identical effects on the permeability. Thus, in order to determining the effects of each of them on permeability values, we can use artificial neural networks. Also we can calculate factor as RSE by using artificial neural network ratios which show effects of each input parameters on the output ones. Via the study of RSE it can be concluded that each log has specific role in determination of permeability .Thus, at first it’s better to pay attention to more effective logs. With this regard, after training the artificial neural networks, the data provided from the geophysical logs as input of network and the horizontal and vertical permeability as the output; the weights of the most appropriate neural networks were saved.Then by using these relations, comparative effects of each of logs on the permeability were indicated and RSE values were registered. These processes have been done several times and provided results have been calculated as Frequency of per cent of RSE value in the interval [-1, +1] and with 0.1 distance. Then bar diagrams have been drawn. With the Study of diagrams it could be shown that some of the logs such as NPHI, RHOB, DT and LLS have more effects on the determination of permeability in reservoir rocks.

Jajarm bauxite ore deposit which is the largest bauxite deposit in Iran is located in northern khorasan province. Red bauxite and bauxitic clay are the main parts of the body. Recently by using bayer process, alumina powder (Al2O3) is producing in the Jajarm alumina producing factory and also large volume of red mud is creating as the byproduct. The main purposes of this paper are comparison of the Jajarm bauxite with other bauxite deposits and study of the recovery potential of different elements in it. Rare Earth Elements (REE) are strongly concentrated in some parts of the bauxitic clay horizon and it seems that they are mostly adsorbed by clay minerals and this is an important factor in low cost of their recovery. In comparison with other bauxite deposits, Jajarm bauxite is not enriched in gallium but this element is strongly enriched in the liquor phase of the bayer process and this implies the importance of gallium in the Jajarm deposit. Red mud is also enriched in TiO2 but it seems that its enrichment of REE and Sc is not economically important. In addition, the comparison of the Jajarm bauxite composition with average composition of the crust, diabase and granites shows enrichment of the Jajarm bauxite from Zr, V, As, Nb, Hf, U, Ta and Bi but their concentrations are not economically important.

Sarvak, Surgah and Ilam Formations from Bangestan Group with Cenomanian to Santonian age consist of carbonate units and have a total thickness of 679 m in Mongasht Anticline, Shivand area, 45 km southeast of Izeh, in Zagros basin.Recognition of original carbonate mineralogy based on petrographic evidence is difficult, because aragonite and high Mg calcite transformed to low Mg calcite during diagenesis.Major (Ca, Mg) and minor elements (Sr, Na, Fe, Mn) and carbon and oxygen isotope values used to determine carbonate mineralogy in Sarvak, Surgah and Ilam Formations. Bivariate plots of major and minor elements and oxygen and carbon isotopes values indicate that aragonite is the original carbonate mineralogy in studied formations. Major and minor elements and oxygen and carbon isotopes values along stratigraphic columns were used to distinguish between Sarvak, Surgah and Ilam Formations.Paleotemperature calculation based on oxygen isotope values of the least altered samples indicate that sea water temperature during precipitations of Sarvak, Surgah and Ilam Formations were 27oC (-3.49 ‰PDB), 31oC (-4.40 ‰PDB), 26oC (-3.21‰PDB) respectively.

Ramin oilfield is located at Dezful Embayment. It consists of Asmari and Bangestsn reservoirs which are in production stage. The present study focused on Asmari reservoir. It was attempted to construct 3D structural- petrophysical models which is important in field development. In this oilfield the Asmari reservoir is divided into 4 zones. Model utilized all available data such as geophysical data, well logs, petrophysical data evaluation, core data, thin sections, and reservoir engineering reports.Reservoir Modeling System (RMS) was implemented using geostatistical method to construct 3D reservoir modeling. This model consists of structural and petrophysical models.Structural output data were applied to create petrophysical model. Modeling steps included of griding, kriging and account experimental variogram for available data. Dimensions of each cell in grid model is 193×228×1m except for zone 4 (nonreservoir) changed to 193×228×5m. Asmari reservoir modeling in Ramin oilfield revealed that zone 1 is the main pay zone and contains about 97.9% of total oil volume in this field.

Granitic rocks of the Malayer Plutonic Complex located at the periphery of Sanandaj-Sirjan zone, with NW-SE trend have a 35×10km extent and contains enclaves of different types. Magmatic enclaves of this area according to their shape, texture, mineralogical and chemical composition are categorized into two groups: Mafic and Felsic.Mafic magmatic enclaves have been observed in a variety of shapes (i.e. spherical, ellipsoidal, elongated and non-elongated lenses) of size <10cm->75cm. The aforementioned enclaves, while relatively similar with the host from the point of view of mineralogical composition but finer grain size and darker color, from the perspective of whole rock chemistry exhibit distinguish similarities and dissimilarities with the host. Higher contents of some oxides such as TiO2, CaO, MgO, FeO(t), MnO and lower content of other oxides (i.e. SiO2, K2O, Na2O) is in agreement with observed mineralogical form and superiority of the ratio of modal values of Plagioclase, Biotite and Amphibole crystal in comparison to the host. Investigating the variation of fundamental elements against the scale of magmatic fractionation index (SiO2) reveals a higher level of fractionation in the hosts and the role of magma mixing event in linear trend of some of oxide variations. Some of oxides (e.g. K2O, Na2O) have a distributed pattern in both of enclaves and hosts that related to disagreement in transformation trend of theirs between the enclave and the host (role of magma mixing and metasomatism), and coherence of the variation pattern of trace elements between them is related to the high mobility of the reduced elements and the role of compositional homogenization. Which both of them confirm the effective role of volatile substances and fluidic magma in prompting the aforementioned chemical reaction at the enclave/host interface in the molten, semi-molten and even solid phase? Considerable redistribution of K+ from the host rock (high K calc-alkaline affinity) to the magmatic enclaves to form Biotite in the enclave and especially at its interface with the host rock is among the most determinative signs of the establishment of chemical equilibrium through intermediary chemical reactions during magma mixing event.

At present, GIS technology plays a significant role in exploration studies of natural resources. GIS can not only organize the mineral potential-related information, but also integrate different datasets and produce quickly and precisely required mineral potential maps. It also supports the spatial decisionmaking process. Here, we use GIS to produce the mineral potential map, MPM of the Chahefirozeh porphyrtic copper prospect to determine sufficient drilling localities. The procedure consists of four steps as following: 1) preparing various data layers (e.g. rock type, alterations, structures, mineral anomalies etc). 2) Producing the mineral factor maps, MFMs, 3) assigning the reasonable weights to the MFMs, and 4) integrating the weighted MFMs in the Inference Network using the Fuzzy-logic and index-overlay operators. The later is introduced as new method which can eliminates those defects involved with previous methods. It can integrate factor maps with more flexibility. The resulted MPM of the study regions indicates that main potential areas show N-S trend and locate in the central part of the region. Eventually, the degree of correlation between MPMs and 24 drilled exploration boreholes have been estimated for two different classes, 72.73% and 74.42%. Regarding to the resulted MPM, some new promising drilling localities have been suggested. Comparison between the high potential points indicated by our MPMs with those previous drilled boreholes reveals about 60% miscorrelation. In other word, if the present proposed methodology had been performed before drilling operation, about 900,000$ could be saved in this stage.