فهرست مطالب

Oil & Gas Science and Technology - Volume:10 Issue: 4, Autumn 2021

Iranian Journal of Oil & Gas Science and Technology
Volume:10 Issue: 4, Autumn 2021

  • تاریخ انتشار: 1400/10/30
  • تعداد عناوین: 7
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  • Mohammad Ashrafi, Seyyed Alireza Tabatabaei-Nejad *, Elnaz Khodapanah Pages 1-13

    Challenges on rock absolute permeability prediction from tiny sample when laboratory apparatus is not applicable and without pore network modelling is remarkable. This prediction using the characterization of micro-computed tomography images have been studied in this paper. Twenty series of 2D micro computed tomography rock binary images have been collected, each of them was considered as a 3D binary image. Their geometric measures in 2D and 3D for measuring image properties have been considered using Minkowski functionals and available functions, developing a regression model, absolute permeabilities have been evaluated. Some 2D and 3D geometric properties are considered. The area, the perimeter and the 2D Euler number are 2D binary images properties. The volume, the surface area, the mean breadth also known as integral of the mean curvature, and the 3D Euler Number are 3D binary images properties. Porosity and number of objects also have been considered as parameters of a regression model.To perform linear regression, twenty-four parameters were evaluated and some of them were chosen to be used. An equation is proposed based on the extensive study conducted which can predict rock permeability. This equation has two sets of parameter coefficients, one set predicts high permeability rocks (above two Darcy) and the other for low and medium permeability (less than two Darcy) which can be used for carbonated rock. Average absolute relative error for conducted cases is 0.06.

    Keywords: Absolute Permeability, Euler Number, Minkowski Functions, 2D Binary Image, 3D Image
  • Hamidreza Mousavi *, Mehdi Shahbazian Pages 14-30

    Auto-associative neural network (AANN) has been recently used in sensor fault diagnostics. In this paper we introduce a new AANN based algorithm named Improved AANN (I-AANN) for sensor single-fault diagnosis. The algorithm is two-aimed approach which estimates the correct value of the faulty sensor as isolates the source of the fault simultaneously. Performance of the algorithm is compared with the so called Enhanced AANN (E-AANN) via computational time and fault reconstruction accuracy and is shown that I-AANN has higher performance, it can isolate the source of fault very quickly and also accurately. A Dimerization process model is used as a case study to test and compare performance of algorithms. Results demonstrate that I-AANN has superior performance.

    Keywords: Auto-Associative Neural Networks, sensor fault diagnostic, Reconstruction Algorithm
  • Mahammad Laribaghal *, Mehdi Torfi, Mehdi Khorasanian, Seyyed Reza Alavi Zaree Pages 31-42

    Fin-pass rolls are the latest series of rolls at ERW pipe production lines that are forming the sheets to tubular shape and adjusting the edges of the sheet for welding. The rolls (made of AISI 8622 steel) lose their useful function after about ten years of operation due to severe wear and change of their original surface profile. To repair these rolls, the worn portions were removed by grinding and replaced by a ring of AISI D2 high carbon steel. After a short time of service (about one year), the edge of the repair-ring exposed to severe spalling and fracture. The present study investigated the causes of rapid failure of the AISI D2 repair-ring and proposed a solution to the problem. The surface morphology, hardness and wear resistance were studied. Also, for closer investigation of the failure mechanism, the stress analysis of fin-pass rolls was studied using ABAQUS 6.14 finite element software. The main cause of spalling was inherent brittleness of the AISI D2 steel and presence of high stress concentration at edges of the repair-ring. To overcome this problem, carburized AISI P20 steel, case hardened AISI 4140 steel, and hard chromium electroplated AISI 4140 steel were replaced and the resulted properties were studied. The highest resistance to spalling and wear occurred with carburized AISI P20 steel because of the high surface hardness and the gradual increase of toughness from the surface to the depth at carburizing process which increases the wear resistance and retarding the growth of fatigue cracks.

    Keywords: Carburizing, Failure mechanism, Finite element simulation, Fin-pass roller, Wear test
  • Mehdi Amiri *, Jafar Gajar, Azim Kalantari Asl Pages 43-57

    Sarvestan and Saadatabad oilfields produce more than 140 bbl/day of wastewater from oil processing. Due to environmental issues, the produced water is injected into a disposal well through an 8 inch, 5 km pipeline. Formation of inorganic scale may accelerate the need for frequent reservoir acid stimulation, restrict flow path, and generally add unpredicted costs for water injection operations. This study presents the predicting scale tendency and scale precipitation at different pressures, temperature, and mixing ratios of injection wastewater with formation water in Sarvestan and Saadatabad oilfields. The experimentally measured chemical analysis of injection water and formation water were used to estimate the amount, type and composition of scale due to mixing and change in thermodynamic conditions. Scale tendency values for eight types of scale (CaCO3 (Calcite), CaSO4 (Anhydrite), CaSO4. 2H2O (Gypsum), FeCO3 (Siderite), Fe(OH)2 (Amorphous), NaCl (Halite), Mg(OH)2 (Pyrochroite) and KCl (Silvite)) are investigated by commercial software packages (OLI ScaleChem and StimCADE). Results show that the main scales are CaCO3 and FeCO3 that can be formed in Sarvestan and Saadatabad oilfields. The formation of these scales can lead to serious problems, such as disrupting equipment and decrease production, thus it is necessary to predict all types of scales before formed. It allows design and planning for chemical inhibitor treatment, and prediction of injectivity problems and acid stimulation.

    Keywords: CaCO3, FeCO3, Produced water, Scaling tendency, Sarvestan, Saadatabad oilfields
  • Borzu Asgari Pirbalouti * Pages 58-67

    In this study, the application of iron oxide nanoparticles has been investigated in the presence of an external magnetic field to control the rheology of drilling fluids. Drilling fluid rheology is one of the most important factors for determining the optimal fluid. On the other hand, polymers in the water-base drilling fluid is used in order to fluid loss controlling. In low density oil-base fluids, where the water content is low, rheological control is generally difficult since there is a limitation in selection of additives. In this study, the ferromagnetic fluid has been generated by adding nanoparticles of Fe3O4 to silicon oil. By adding ferromagnetic fluid to the oil-base mud under the influence of the external magnetic field, we examined the rheological behavior of the oil-base drilling mud. The external magnetic field can be applied in real conditions in the middle of a magnetic drilling string. The results showed that the magnetic nanoparticles improved the drilling mud rheological properties. Also, the viscosity of the oil-base fluid was measured without the presence of nanoparticles of 2 centipoises, which, it increased to 33 centipoises by adding 4% by weight of iron oxide nanoparticles and under the external magnetic field of 0.321 T. The magnetic field was also used for WBM and the results showed that in water-base fluids containing PolyAnionic Cellulose (PAC) polymer, the magnetic field did not have much effect on the rheological properties of the drilling mud compared to OBM. Since water is the main component of the water-based fluid, increasing the magnetic field reduced the viscosity of the water-base fluid. By adding iron oxide nanoparticles to the polymer-based fluid, the magnetic field increased fluid rheology. The viscosity of the water-base fluid containing nanoparticles increased to 850 centipoises under the magnetic field.

    Keywords: drilling fluid rheology, Iron oxide nanoparticle, Magnetic field, ferromagnetic fluid
  • Bahram Habibnia *, Omid Valipour, Majid Alipour Pages 68-84

    The Qale-Nar Oilfield is an asymmetric two-humped anticline located in the northernmost part of the Dezful Embayment, in which the fractured Asmari carbonates are the main reservoir rock. In this study, for the first time, the organic geochemistry of oils produced from the Asmari reservoir are used to investigate the reservoir continuity and possible compartmentalization. For this end, geological information from the studied oilfield were combined with bulk geochemistry (e.g., ˚API gravity) and molecular characteristics (e.g., GC and GCMS data) of produced oils. Two oil samples obtained from well # 6 and well # 10 of the studied oil field indicate significant differences in terms of their bulk and molecular geochemical properties. Accordingly, a scenario was presented to better explain the reservoir charging and compartmentalization in the Qale-Nar Oilfield. In this scenario, low-maturity hydrocarbon pulses first charge the eastern culmination of the Qale-Nar Oilfield. The activity of a fault plane located between well # 6 and well # 10 could induce a barrier between the two wells. Consequently, the late hydrocarbon charges with higher maturity could only charge the compartment belonging to well # 6. Therefore, well # 10 could not receive these high-maturity hydrocarbon pulses due to the lack of lateral connectivity. The information obtained from this study can be of great help in future reservoir studies with important implications for field development projects and enhanced-recovery plans.

    Keywords: Asmari reservoir, Gas chromatography–mass spectrometry (GC–MS), Compartmentalization, Qale-Nar oilfield, Gas chromatography (GC), Reservoir continuity
  • Abdorrahman Mehri Ghahfarrokhi, Hassan Shokrollahzadeh Behbahani*, Ezzatollah Kazemzadeh, Gholam Abbas Safian Pages 85-99

    Nowadays, use of visco-elastic surfactants as the main component of gel diverters is becoming more and more common among well completion engineers, as well as stimulation service companies. Gel diverter, as other kinds of diverters, is used in multi-layered carbonated reservoirs to diver acid into less permeable sublayer. As use of these materials becomes more common, modeling and simulating the gel-acid injection process becomes more required. In this study, a mathematical model is generated to simulate gel-acid injection process, and experimental data is compared with data predicted by the model. The purpose of this study is to investigate the field possibility of injection gel-acid and to generate a model for simulating this process, in order to smart permeability enhancement in Ahwaz oilfield, one of Iranian Southwest oilfields. The solutions predicted by model are in an acceptable correlation with experimental data. The generated model can be used for other multi-layered carbonated oilfields.

    Keywords: Acidizing, Modeling, Multi-layered reservoirs, Stimulation, VES