perISPGمجله زمین شناسی نفت ایران 2251-87382251-87382018-11714118articleKioumars Taherikio.taheri@yahoo.com1Mohammad Reza Rasaeimrasaei@ut.ac.ir2Abbas Ashjaei98.8.4@yahoo.com3M.Sc. in Petroleum Engineering Exploration, Department of Mining and Metallurgical Engineering, Yazd University, Yazd, IranAssociate Professor, Institute of Petroleum Engineering, School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, IranHead of Design and Planning, Manager Assistance -Exploitation Geological, National Iranian South Oil Fields Company, Ahwaz, IranUnderstanding of oil and gas reservoirs is of great help in maximizing hydrocarbon recovery. In the study of the characteristics of oil structures, the study of fractures of reservoir rock in the stages of production and development of the field is very necessary. Nowadays, the use of mud loss modeling and image logs in helping accomplish this task is of great assistance to oil geologists. Since the most of Iran's reservoirs are carbonate kind, investigating and identifying fractures, the degree of fissures opening and porosity distribution in the Asmari reservoir field of study, It is one of the most effective factors in the production of hydrocarbons from this field. One of the best ways to identify and interpret geology in the well, using of the FMI image log is, which can create high quality images from the well. With the help of the images provided, can determine the types of fractures, porosity, the distribution of diagenetic porous spaces and the estimation of permeability trend. In this article, first, structure and Functionality of the FMI image log and then drilling and production problems were evaluated in Asmari reservoir. In the following, the functional role of the log in interpreting and determining the degree of fissures opening, porosity distribution and permeability level in 8 wells in Asmari reservoir, has been evaluated. In this study, identification of Asmari reservoir fractures and how to expand these fractures in the reservoir By using mud loss modeling, interpretation of the FMI image log and the effect of these fractures was on the porosity and permeability of the reservoir. In this study, it has been determined that, fractures identified in wells very good matching with drilling mud loss maps with rock basement faults at the has anticline of the Asmari reservoir.http://journal.ispg.ir/Article/33847Fractures Asmari Reservoir FMI Image Log Porosity Distribution Mud Loss Map perISPGمجله زمین شناسی نفت ایران 2251-87382251-87382018-117147492articleAlireza Ghazanfaria.ghazanfari@aut.ac.ir1Abdolrahim Javaherianjavaherian@aut.ac.ir2Mojtaba Seddigh Arabanimojtabased@yahoo.com3Channels are one of the most important stratigraphic and morphological events. If channels place in a suitable position such as enclosed in impermeable place can make suitable oil and gas reservoir; So identifying channels are crucial. Different tools such as filters, seismic attributes, artificial neural networks, and meta-attributes have played an important role in this regard. In this paper dip-steering cube, dip-steer median filter, dip-steer diffusion filter, and fault enhancement filter, have been used. Then, various seismic attributes such as similarity, texture, spectral decomposition, energy and polar dip have been defined and studied. Therefore, work on F3 real seismic data of Dutch part of the North sea for detecting channels has been started by detecting suitable attributes. For identifying the channel in data, it has been used from compilation and combination of seismic attributes using supervised ANN (multi-layer perceptron), and development of mata-attributes, then recombine meta-attributes created along the channel, and using different interpretation point, for eliminating the impact of facies and lithology changes along the channel. Among the advantages and the reasons for using this kind of neural network (supervised), which increases the effect of the neural network and improves the result, is the ability to train the network by specifying the channel and non-channel points used in this paper. Finally, using the above methods, the identification of the channel examined in the above seismic data has been improved, and the channel has been properly detected and extracted throughout its entire length.http://journal.ispg.ir/Article/33848Channel Detection Seismic Attributes Artificial Neural Network Meta AttributesperISPGمجله زمین شناسی نفت ایران 2251-87382251-87382018-117143548articleAli reza BashariA_bashari@yahoo.com1شرکت ملی نفت ایران The Kimmerigian-Tithonian) Arab Zone are the prolific hydrocarbon bearing resrvoirs in the eastern part of the Persian Gulf,offshore,Iran.They were deposited in an arid climate which dominate during late Jurassic. The Berriasian to Thitonian Hith formation wich overlies the Arab reservoir constitutes the cap rock,wich just to the east gradually pinches out and form a N-S feather adge. The study reveals that Arab zones form a massive to interbedded anhydrite with varying proportion of limestone and dolomite and generally have regressive units which was deposited on a broad carbonate platform .This formations are thick in center (Salman field) and mostly consist of intertidal pack/grainstones with high porosity/permeability,good cap rock and also close to the source rock,which has the most hydrocarbon potential, but towards east the layers getting thinner with unsuitable cap rock and are away from source rock ,so as a result Arab formation in this part of the Persian Gulf doesn,t seem to be attractive. This study reveals that there is still some undrilled structure within this area which could be attractive for further Exploration drilling. http://journal.ispg.ir/Article/33849Persian Gulf Arab Fm Surmeh Fm facies Petrography Reservoir characterization Salman Reshadat Resalat fields Persian Gulf Arab Fm. Surmeh Fm. facies Petrography Reservoir characterization Salman Reshadat Resalat fields Persian Gulf Arab Fm. Surmeh Fm. facies Petrography Reservoir characterization Salman Reshadat Resalat fields Persian Gulf Arab Fm. Surmeh Fm. facies Petrography Reservoir characterization Salman Reshadat Resalat fields perISPGمجله زمین شناسی نفت ایران 2251-87382251-87382018-117141934articleReza Khoshnevis Zadehrezakhoshnevispg@gmail.com1Alireza Hajiandralirezahajian@gmail.com2Ehsan Larkiehsan58larki@gmail.com3Islamic Azad UniversityIslamic Azad UniversityThe elastic parameters of the rock include the Young modulus, the Poisson ratio, the bulk modulus and the shear modulus. Young modulus with the unconfined compressive strength of rock, are two key parameters in the definition of intact rock. Elastic modulus represents the amount of rock rigidity and is known as the stress-strain chart slope. These parameters represent of rock strength to failure, are important parameters for the stability analysis of wellbore stability. According to the unavailability and cost of core data, and also attended to this fact that the data from the core are not continuous and not available at all points in the well, the uses of DSI logs is one of the best methods for calculating elastic modules. Using these logs, you can also study elastic moduli continuously in a well. In this study, elastic dynamic parameters were calculated using the DSI and density logs for the Dalan Formation. Attention to the fact that the calculated parameters using the velocity of the sound waves are of the type of dynamic parameters, these parameters were have converted to the static modules using appropriate empirical relationships. The rock strength Parameters were calculated using the experimental relationships commonly used in the oil industry to determine rock strength parameters. These parameters were calculated according to static elastic modulus as well as porosity and shale volume. Comparing the values of elastic modulus and rock strength parameters with porosity showed that porosity with elastic modulus and rock strength parameters has an inverse relationship, so that with increases the porosity, the elastic modulus and rock strength parameters have been reduced.http://journal.ispg.ir/Article/33850Elastic modulus Rock strength parameters DSI tool Dalan formation.perISPGمجله زمین شناسی نفت ایران 2251-87382251-87382018-117144973articleMeysam Barari KharkeshiMeysamomeysam.org@gmail.com1Ali Seyrafianseyrafia@sci.ui.ac.ir2Hossein Vaziri-Moghaddamhvaziri@sci.ui.ac.ir3Roohollah ShabafroozR.shab2003@Gmail.com4The Asmari Formation at the Lar anticline, located 77 km northeast of Gachsaran city, comprised 361 meters in thickness. In the present study, biostratigraphy and microfacies of the Asmari Formation at the Lar anticline (northeast of Gachsaran city) is investigated. Based on foraminiferal distribution, 25 genera and 21 species have been identified and four biozones: 1. Lepidocyclina – Operculina – Ditrupa assemblage zone, 2. Archaias asmaricus – Archaias hensoni – Miogypsinoides complanatus assemblage zone, 3. Indeterminate zone, 4. Borelis melo curdica – Borelis melo melo assemblage zone, representing Oligocene (Chattian) to Early Miocene (Aquitanian - Burdigalian) are introduced, respectively. 12 microfacies related to an open marine and lagoon (semi-closed and closed) environments of homoclinal ramp setting are present.http://journal.ispg.ir/Article/33856Asmari Formation Oligocene – Miocene Lar anticline Biostratigraphy Microfacies Benthic foraminiferaperISPGمجله زمین شناسی نفت ایران 2251-87382251-87382018-1171493110articleAlireza Ashouriashouri@um.ac.ir1Samira Rahimisamirarahimi28@gmail.com2Abass Sadeghia-sadeghi@sbu.ac.ir3Abbas Ghaderiaghaderi@um.ac.ir4Ferdosi UniversityFerdosi UniversityFerdowsi University of MashhadIn this research, biostratigraphy of the Gurpi Formation in Jahangirabad section, SW Iran, has been studied .The thickness of the Gurpi Formation in this section is 263 and consists mainly of argillaceous limestone and limestone. The lower boundary with the Ilam Formation is comformable with sharp lithology and upper boundary with the Pabdeh Formation is gradational. In this study, 76 species belong to 17 genera and 8 biozones of planktonic foraminifera were recognized. The biozones consist of Globotruncana ventricosa Zone, Radotruncana calcarata Zone, Globotruncanella havanensis Zone, Globotruncana aegyptica Zone, Gansserina gansseri Zone, Contusotruncana contuosa Zone, Abathomphalus mayaroensis Zone and Pseudoguembelina hariaensis. The age of the Gurpi Formation in this section based on these biozones is Middle Campanian to Late Maastrichtian in this section.http://journal.ispg.ir/Article/33859 Biostratigraphy Planktonic foraminifera Jahangirabad section Middle Campanian to Late Maastrichtian