Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-24124220150501Separating Well Log Data to Train Support Vector Machines for Lithology Prediction in a Heterogeneous Carbonate Reservoir114958810.22050/ijogst.2015.9588ENMohammad Ali SebtosheikhDepartment of Petroleum Exploration, Petroleum University of Technology, Abadan, IranReza MotafakkerfardDepartment of Petroleum Exploration, Petroleum University of Technology, Abadan, IranMohammad Ali RiahiUniversity of Tehran, Geophysics Institute, Tehran, Iran0000-0002-3827-4467Siyamak MoradiDepartment of Petroleum Exploration, Petroleum University of Technology, Abadan, IranJournal Article20130716The prediction of lithology is necessary in all areas of petroleum engineering. This means that to design a project in any branch of petroleum engineering, the lithology must be well known. Support vector machines (SVM’s) use an analytical approach to classification based on statistical learning theory, the principles of structural risk minimization, and empirical risk minimization. In this research, SVM classification method is used for lithology prediction from petrophysical well logs based on petrographic studies of core lithology in a heterogeneous carbonate reservoir in southwestern Iran. Data preparation including normalization and attribute selection was performed on the data. Well by well data separation technique was used for data partitioning so that the instances of each well were predicted against training the SVM with the other wells. The effect of different kernel functions on the SVM performance was deliberated. The results showed that the SVM performance in the lithology prediction of wells by applying well by well data partitioning technique is good, and that in two data separation cases, radial basis function (RBF) kernel gives a higher lithology misclassification rate compared with polynomial and normalized polynomial kernels. Moreover, the lithology misclassification rate associated with RBF kernel increases with an increasing training set size.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-24124220150501Evaluation of the Effects of Nanoclay Addition on the Corrosion Resistance of Bituminous Coating1526959010.22050/ijogst.2015.9590ENHamid Reza ZamanizadehDepartment of Technical Inspection, Petroleum University of Technology, Abadan, IranMohammad Reza ShishesazDepartment of Technical Inspection, Petroleum University of Technology, Abadan, IranIman DanaeeDepartment of Technical Inspection, Petroleum University of Technology, Abadan, IranDavood ZaareiTechnical Faculty, South Tehran Branch, Islamic Azad University, Tehran, IranJournal Article20131216In this study, the corrosion resistance of a bituminous coating reinforced with different ratios of nanoclay pigment was studied. To make nanocomposite coatings, 2, 3, and 4 wt.% of clay (Cloisite Na+) were incorporated into water emulsified bitumen. The coatings were applied to steel 37. Optical microscopy and X-ray diffraction (XRD) were used to characterize the nanocomposite structure. In order to investigate the anticorrosion behavior of the coatings, electrochemical impedance spectroscopy (EIS) and direct current polarization techniques were used. The results show that the coatings containing nanoclay have better performance compared to the neat bitumen. Moreover, it was revealed that the corrosion resistance of the nanocomposite increased as the clay loading increased up to 4 wt.%.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-24124220150501An Improvement in Temporal Resolution of Seismic Data Using Logarithmic Time-frequency Transform Method2739958710.22050/ijogst.2015.9587ENAmin Roshandel KahooSchool of Mining, Petroleum and Geophysics Engineering, University of Shahrood, Shahrood, IranSaman GholtashiSchool of Mining, Petroleum and Geophysics Engineering, University of Shahrood, Shahrood, IranJournal Article20141205The improvement in the temporal resolution of seismic data is a critical issue in hydrocarbon exploration. It is important for obtaining more detailed structural and stratigraphic information. Many methods have been introduced to improve the vertical resolution of reflection seismic data. Each method has advantages and disadvantages which are due to the assumptions and theories governing their issues. In this paper, we improve the temporal resolution of reflection seismic data using the logarithmic time-frequency transform method. This method has minimum user-defined parameters. The algorithm uses valuable properties of both the time-frequency transform and the cepstrum to extend the frequency band at each translation of the spectral decomposing window. In this method, the displacement of amplitude spectrum by its logarithm is the basic idea of the algorithm. We tested the mentioned algorithm on both synthetic and real data. The results of the both tests show that the introduced method can increase the temporal resolution of seismic data.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-24124220150501Developing a Fuzzy Logic Model to Predict Asphaltene Precipitation during Natural Depletion based on Experimental Data4049959110.22050/ijogst.2015.9591ENMobina MohammadiDepartment of Petroleum Engineering, Petroleum University of Technology, Ahwaz, IranRiyaz KharratDepartment of Petroleum Engineering, Petroleum University of Technology, Ahwaz, IranAbdonabi HashemiDepartment of Petroleum Engineering, Petroleum University of Technology, Ahwaz, IranJournal Article20131005Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-24124220150501Comparison of Simulated Annealing, Genetic, and Tabu Search Algorithms for Fracture Network Modeling5067959210.22050/ijogst.2015.9592ENSaeed MahmoodpourDepartment of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, IranMohsen MasihiDepartment of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, IranSajjad GholinejhadDepartment of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, IranJournal Article20140223The mathematical modeling of fracture networks is critical for the exploration and development of natural resources. Fractures can help the production of petroleum, water, and geothermal energy. They also greatly influence the drainage and production of methane gas from coal beds. Orientation and spatial distribution of fractures in rocks are important factors in controlling fluid flow. The objective function recently developed by Masihi et al. 2007 was used herein to generate fracture models that incorporate field observations. To extend this method, simulated annealing, genetic, and tabu search algorithms were employed in the modeling of fracture networks. The effectiveness of each algorithm was compared and the applicability of the methodology was assessed through a case study. It is concluded that the fracture model generated by simulated annealing is better compared to those generated by genetic and tabu search algorithms.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-24124220150501Organizational Silence, from Roots to Solutions: A Case Study in Iran Petroleum Industry6883959310.22050/ijogst.2015.9593ENMehdi Afkhami ArdakaniFaculty member of RIPI, HRM PhD Student, Tehran University, Tehran, IranEhsan MehrabanfarHRM & System Analyst Expert at RIPI, Tehran, IranJournal Article20140907Organizational silence is defined as the lack of effective interactions among staff and it stands opposite to the concept of organizational voice. In the present research, the purpose is to measure the silence behavior among the Research Institute of Petroleum Industry (RIPI) staff before and after the implementation of a comprehensive suggestion system. A suggestion system is an internal structure easily accessed by all the staff to state their suggestions in a pre-structured format. The roots of silence behavior are studied based on a deep literature review to find out possible solutions to improve organizational voice. To conduct the research, a self-structured questionnaire has been developed and distributed among all the staff. A quasi-experimental methodology has been adopted to compare pretest and post-test results of silence status before and after implementing the suggestion system. The results show that the silence behavior has been meaningfully reduced. This is based on a simple t-test performed by SPSS software, where there is a meaningful difference between the silence status of pre-test and post-test. In other words, a suggestion system could be a communication opportunity to encourage staff to provide suggestions and to cooperate for promoting the organization, which will finally reduce the organization silence. A major gap within the studies of Iranian scholars about organizational silence is the failure to introduce effective solutions to reduce it. However, this research is innovative in the sense that it fills the mentioned gap. This research shows that large scale organizations like RIPI need to consider methods like suggestion systems to break bureaucratic obstacles so that their staff can easily find open routes to share their ideas and suggestions in a prestructured format. This cooperating will lead to mutual benefits for both parts, since suggestions could be used to enhance organizational structure and performance and the staff could also witness their impact on organizational improvements.