Geopersia
Volume:8 Issue: 1, Winter-Spring 2018

The best exposed Early Miocene (820 m. thick. ) shales and interbedded silty sandstones beds of the Pyawbwe Formation at Sakangyi- Thayat area,Magway Region are investigated geochemically by using Siemens SRS- X Ray 303 AS XRF Spectrometer. Major and some trace element concentrations have been determined to achieve their provenance, tectonic setting ,paleoweathering , paleoclimate and sedimentation characteristics. The geochemistry of sediments is particularly valuable in the study of fine-grained rocks that are difficult to characterize through petrographic studies. Geochemical data revealed that the felsic granitic plutonic provenance of moderate relief of arc massif exposed on tectonically calm continental margin which is probably the Shan- Thai continental block eastern and northeastern Myanmar . Average values of both Chemical Index of weathering (CIW) and Chemical Index of Alteration (CIA) ( 77.4 and 67.3 respectively ) suggest a moderately chemical weathering condition prevailed during transportation and deposition on passive shallow margin as progressive mature sediments.

Mashhad city, the second most populous metropolis of Iran, with a population of more than three million, lies between two seismically active regions of Binalood and Kopet-Dagh. In recent years, the city has grown around the South Mashhad (SM) fault zone in the south. Given the vital role of the SM fault in influencing the seismic risk of the city, this study is aimed at the evaluation of the fault’s characteristics and activity. The overall trend of the fault and evidence of its activities are investigated by morphotectonic studies, and the situation of fault zone was explored by different geophysical methods including resistivity, magnetic and microtremor array. Morphology studies have shown that SM fault results in the deviation of the river channels, replacement, and deformation of alluvial fans. The geoelectric studies have shown three segments of the fault, F1, F2, and F3, with the notable normal displacement. Magnetometry and microtremor array studies across F1 confirmed the normal displacement of the fault. It is concluded that SM fault is an active right-lateral and normal fault system that had a significant role in the development of Mashhad Valley.

Pattern recognition on seismic data is a useful technique for generating seismic facies maps that capture changes in the geological depositional setting. Seismic facies analysis can be performed using the supervised and unsupervised pattern recognition methods. Each of these methods has its own advantages and disadvantages. In this paper, we compared and evaluated the capability of two unsupervised methods Fuzzy c-means (FCM) and Gustafson Kessel (GK) and one supervised method Adaptive Neuro-Fuzzy Inference Systems (ANFIS) at revealing the presence of a channel system. The process is performed in an interactive scheme in the SeisART software to obtain the best output. The seismic facies analysis was conducted on a 3D seismic data set acquired at North Sea block F3. Based on the results, the GK method outperformed the other two methods in delineating the channel pattern.

Dasycladales are relatively abundant in the bedded limestones of the Bidestan and Howz-e Khan members of the Late Triassic Nayband Formation in central Iran. In a locality south of the town of Naybandan (northwest of Dig-e Rostam), several Rhaetian dasycladacean algae were found in thin sections. The following taxa are described: Diplopora phanerospora Pia, Naybandoporella rhaetica nov. gen. nov. sp., Naybandoporella cf. rhaetica.
The species Probolocuspis sarmeikensis Senowbari-Daryan is replaced and attributed to the genus Naybandoporella. The microfacies characteristics of the limestones as well as the associated organisms are mentioned.

The current study proposes a two-step approach for pore facies characterization in the carbonate reservoirs with an example from the Kangan and Dalan
formations in the South Pars gas field. In the first step, pore facies were determined based on Mercury Injection Capillary Pressure (MICP) data incorporation with the Hierarchical Clustering Analysis (HCA) method. In the next step, polynomial meta-models were established based on the evolved Group Method of Data Handling (GMDH) neural networks for the purpose of pore facies identification from well log responses. In this way, the input data table used for training GMDH-type neural network consists of CALI, GR , CGR , SGR, DT, NPHI, RHOB, PEF, PHIE and VDL logs. The MICP-HCA derived pore facies were considered as the desired outputs. Moreover, multi-objective genetic algorithms (GAs) are used to the evolutionary design of GMDH-type neural networks. Training error and prediction error of neural network have been considered as conflicting objectives for Pareto multi-objective optimization. The results of this study indicate the successful implementation of GMDH neural networks for classification of pore facies in the heterogeneous gas bearing carbonate rocks of South Pars gas field.

An important method in oil and gas exploration is vertical seismic profile (VSP) to estimate rock properties in drilling well. Quality factor is also the crucial point of seismic attenuate in VSP data. In the present study, this factor was used to evaluate the hydrocarbon potential of Kangan Formation in one of the Persian Gulf oil fields using VSP zero offset method. Quality factor was estimated using VSP spectral ratio method. Density and porosity logs are also used to determine lithology and reservoir fluid types. Analysing Vp/Vs ratio changes is a useful tool to detect hydrocarbon accumulation. These points marked by high amplitude energy in seismograms in correlation with petrophysical logs. According to Vp/Vs plots and geological logs of the field revealed that Vp/Vs ratio is increased at depths indicating hydrocarbon presence. Data are showing good correlation to petrophysical logs. Therefore, VSP method can be applied as a suitable alternative method to find hydrocarbon reserves in those boreholes without petrophysical logs.

Rock typing is known as the best way in heterogeneous reservoirs characterization. The rock typing methods confine to various aspects of the rocks such as multi-scale and multi-modal pore types and size, rock texture, diagenetic modifications and integration of static/dynamic data. Integration of static and dynamic behavior of rocks and their sedimentary features are practiced in this study. Porosity, permeability and pore size distributions are investigated as the static and capillary pressure, water saturation and irreducible water saturation as dynamic behavior of the rocks. Results from core data analysis in some intervals and continuously NMR data through the whole well are also involved. Initially, based on Flow Zone Index method, while considering geological attributes, 7 rock types are determined. The petrophysical properties of the rock types including Pc, SW and SWir are combined into the rock types. Afterward, pore types, facies characteristics, texture and diagenetic overprints are involved in the rock type’s classification to capture spatial trends and relationships. Eventually, the rock types are defined in the cored intervals by these parameters and predicted in non-cored intervals by NMR. The rock types are established to provide a clue on the high and low permeable zones and accurate reservoir zonation.

Petrophysical evaluation of petroleum reservoirs is one of the most challenging tasks for hydrocarbon reserve determination. One critical petrophysical parameter is the water saturation which is normally calculated from Archie’s equation. Carbonate reservoirs, however, due to their complex mineralogy are not good candidates for Archie’s equation because Archie’s parameters are strongly dependent on pore pattern distribution, type and distribution of clay content, wettability and mineralogical properties. In the present study, Magnetic Resonance Image Logging (MRIL) was used to determine water and hydrocarbon volumes using Time Domain Analysis (TDA) technique. The results of TDA technique indicated that the water and oil peaks are well separated in the light oil zones and the calculated volumes of hydrocarbon and water by using TDA were in agreement with water and oil saturation calculated from conventional logging measurements. Moreover, values of reservoir oil viscosities were estimated to be less than 10 cps by intrinsic T1. This study shows that MRIL-based interpretation models are easy to apply because they require fewer unknowns as inputs and because MRIL response is not influenced by the resistivity model’s parameters, water salinity, etc.

Numerous post-ophiolite intrusions exposed into the late Cretaceous–Paleocene Sabzevar ophiolite belt, northeast Iran. The intrusions consist of calc-alkaline intermediate to felsic rocks with metaluminous to peraluminous in nature and adakitic affinities. Based on U-Th-Pb dating on separated zircons by SHRIMP Ⅱ, the emplacement age of these rocks into the ophiolite zone is constrained to ~45 Ma. All intrusions show similar MORB –like initial Nd and Sr values of 0.512911 to 0512846 and 0.704758 to 0.703790, respectively, with positive εNd (45 Ma) values of .26 to .45 implying their cogenetic nature. These isotopic signatures combined with geochemical evidences are corresponding to parental adakitic magmas derived from wet partial melting of a garnet-amphibolite source from Sabzevar subducted oceanic lithosphere. After emplacement in the deep magma storage region (equal to 700-900 MPa), this magma evolved to intensify adakitic signatures via amphibole–dominated magma fractionation.

In this paper, correlation between rock types and Cu mineralization obtained by Concentration-Number (C-N) fractal model calculated in Kushk-e-Bahram Cu deposit, Central Iran. This deposit is located in the Urumieh-Dokhtar magmatic arc (UDMA). The main subject in this study was determination of relation between the Cu grade populations and rock types based on subsurface data using logratio matrix. The C–N log–log plot reveals six geochemical populations which defined by Cu.