Papers by M, Hossein Shahsavari
Construction and Building Materials, 2022
Space constructions require unique materials suitable for the harsh conditions in space. Sulfur c... more Space constructions require unique materials suitable for the harsh conditions in space. Sulfur concrete (SC) is one of the most promising materials for such applications. However, the behavior of sulfur concrete in a vacuum, microgravity, and different temperature conditions and its chemical changes has not been well established yet. This study investigated the effect of vacuum, sulfur content, and compaction (trowel effect) on mechanical and hydro-mechanical properties. Moreover, this study assesses the impact of chemical reactions of aluminum and iron oxides with molten sulfur on the sulfur concrete's mechanical properties via X-ray diffraction analysis (XRD), scanning electron microscopy (SEM-EDS), and Fourier-transform infrared spectroscopy (FTIR). The predictions from this research show that the sublimation rate under vacuum conditions at very low temperature (− 60 • C) can be reduced nearly 8000 times compared with that at 20 • C according to the vapor pressure-sublimation rate relationship. In addition, mechanical experimental tests show that a slight increase in sulfur content dramatically reduces the permeability of sulfur concrete. On the other hand, the porosity is not much affected by the sulfur content. Moreover, sample compaction leads to a significant reduction and increment of the hydro-mechanical and mechanical strength, respectively, indicating the trowel's positive effect. Chemically, sulfur dioxide reacts with alumina and iron oxide via chemical adsorption, and then reaction with molecular oxygen produces SO 2− 4 confirmed by SEM-EDS, XRD, and FTIR results. The presence of alumina increases the sample porosity, although, together with iron oxide, another mineral, namely Al 2 Fe 2 (SO 4) 6 (H 2 O) 12 .6H 2 O (Aluminocoquimbite), is formed resulting in a lower porosity. To conclude, we have shed light on sulfur concrete properties and preparation processes in unconventional environments and we have shown how different unknown parameters affect the mechanical and chemical properties of the sulfur binder.
Journal of Petroleum Science and Engineering
In this day and age, the performance of oil and gas wells is severely affected by downhole and re... more In this day and age, the performance of oil and gas wells is severely affected by downhole and reservoir geomechanical problems. The key factor in predicting and solving these problems is a detailed study of the various aspects of the compressive and tensile behavior of the reservoir rock. In this study, the influence of mean sand grain size distribution as an important parameter influencing the petrophysical and geomechanical properties of the rock has been investigated using synthetic sandstone core samples. The results show that increasing the grain size range from 0.1 to 0.2 mm to 0.1-0.8 mm would result in a 23% and 64% decrease in rock porosity and permeability, respectively. However, such an unfavorable trend would be mitigated by the removal of fine particles from the rock composition. According to the results, there is a critical range of sand grains (i.e., 0.2-0.6 mm) above which rock permeability would be severely affected by a change in grain size. At the same compressive stress, the fine sandstones showed a more compressive deformation compared to the coarse specimens. In this regard, a direct relationship between rock compressive strength/Young's modulus and sand grain size was found. The results also indicate that fracture in the fine specimen initiates at lower stress conditions than in the coarse sample. This implies that the weakest grain to grain boundary (GGB) is weaker in the fine-grained samples than in the coarse-grained specimens.
Journal of Petroleum Science and Engineering, 2018
The design of an optimal sand control method and production management is a complex problem due t... more The design of an optimal sand control method and production management is a complex problem due to the simultaneous influence of various factors. Typical effective variables for choosing an optimum sand control method include geological, technical, economical, and expert's experience on similar projects. Some technical factors, which affect the optimum method, are the type of exclusion, gravel size of gravel pack and pre-packed screen, slot width and liner slot length, and productivity index reduction. The situation could be more complicated due to the uncertainty associated with various contributing factors. Therefore, it is crucial to develop a novel approach in order to select the best sand control method with a maximum level of confidence. In this study, to select an optimal sand control method, Multi Criteria Decision Matrix (MCDM) techniques including Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and, ELimination and Choice Expressing REality (ELECTRE) are used. To simulate fluid flow, an integrated model of reservoir, well, and surface facility is used based on actual oil field data collected from the south of Iran. Then, Design of Experiment (DOE) and Response Surface Methodology (RSM) are applied to optimize the controllable variables of the best selected sand control method by MCDM. Finally, Monte Carlo Simulation (MCS) is applied to perform sensitivity and uncertainty analysis in order to determine the crucial factors that control net present value (NPV). The results show that the best sand control method based on AHP, TOPSIS, and ELECTRE is the slotted liner. After that, three different methods of pre-packed, gravel pack, and wire wrapped are respectively the most efficient sand control methods based on an average score of all the MCDM techniques. The results also indicate that although the pre-packed screen has the highest NPV, it is not the best sand control method due to the influence of other efficient criteria. The result of sensitivity analysis using MCS in terms of contribution to total variance shows that slot width, slot density, and slot height controls 60.5%, 38.8%, and 0.7% of the NPV variation within the range of factors, respectively.
Journal of Petroleum Science and Engineering, 2022
In this day and age, the performance of oil and gas wells is severely affected by downhole and re... more In this day and age, the performance of oil and gas wells is severely affected by downhole and reservoir geomechanical problems. The key factor in predicting and solving these problems is a detailed study of the various aspects of the compressive and tensile behavior of the reservoir rock. In this study, the influence of mean sand grain size distribution as an important parameter influencing the petrophysical and geomechanical properties of the rock has been investigated using synthetic sandstone core samples. The results show that increasing the grain size range from 0.1 to 0.2 mm to 0.1-0.8 mm would result in a 23% and 64% decrease in rock porosity and permeability, respectively. However, such an unfavorable trend would be mitigated by the removal of fine particles from the rock composition. According to the results, there is a critical range of sand grains (i.e., 0.2-0.6 mm) above which rock permeability would be severely affected by a change in grain size. At the same compressive stress, the fine sandstones showed a more compressive deformation compared to the coarse specimens. In this regard, a direct relationship between rock compressive strength/Young's modulus and sand grain size was found. The results also indicate that fracture in the fine specimen initiates at lower stress conditions than in the coarse sample. This implies that the weakest grain to grain boundary (GGB) is weaker in the fine-grained samples than in the coarse-grained specimens.
The design of an optimal sand control method and production management is a complex problem due t... more The design of an optimal sand control method and production management is a complex problem due to the simultaneous influence of various factors. Typical effective variables for choosing an optimum sand control method include geological, technical, economical, and expert's experience on similar projects. Some technical factors, which affect the optimum method, are the type of exclusion, gravel size of gravel pack and pre-packed screen, slot width and liner slot length, and productivity index reduction. The situation could be more complicated due to the uncertainty associated with various contributing factors. Therefore, it is crucial to develop a novel approach in order to select the best sand control method with a maximum level of confidence. In this study, to select an optimal sand control method, Multi Criteria Decision Matrix (MCDM) techniques including Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and, ELimination and Choice Expressing REality (ELECTRE) are used. To simulate fluid flow, an integrated model of reservoir, well, and surface facility is used based on actual oil field data collected from the south of Iran. Then, Design of Experiment (DOE) and Response Surface Methodology (RSM) are applied to optimize the controllable variables of the best selected sand control method by MCDM. Finally, Monte Carlo Simulation (MCS) is applied to perform sensitivity and uncertainty analysis in order to determine the crucial factors that control net present value (NPV). The results show that the best sand control method based on AHP, TOPSIS, and ELECTRE is the slotted liner. After that, three different methods of pre-packed, gravel pack, and wire wrapped are respectively the most efficient sand control methods based on an average score of all the MCDM techniques. The results also indicate that although the pre-packed screen has the highest NPV, it is not the best sand control method due to the influence of other efficient criteria. The result of sensitivity analysis using MCS in terms of contribution to total variance shows that slot width, slot density, and slot height controls 60.5%, 38.8%, and 0.7% of the NPV variation within the range of factors, respectively.
Sand production is one of the main research topics in the petroleum industry. This problematic ph... more Sand production is one of the main research topics in the petroleum industry. This problematic phenomenon is related to the mechanical and hydrodynamic behavior and reservoir specifications. Sand production often leads to equipment damage and significant losses. This is usually studied by experimental and numerical methods. This study first gives a brief overview of the methods used to predict sand production in terms of experimental tests, numerical simulation, and field data. The main objective of this research is to highlight the shortcomings of these methods. In addition, experimental hollow cylinder test data and widely used continues numerical simulation are used to investigate these shortcomings. This study is performed by scrutinizing the most important and basic parameters in numerical modeling including two constitutive models (Mohr-Coulomb elastic-perfectly plastic and Mohr-Coulomb cohesion softening/friction hardening failure criteria) and various element sizes and shapes. Since most studies use continuum approaches, it was decided to use a finite difference program. Further, to reduce the undesirable influencing factors the fracture energy regularization method was implemented to diminish mesh dependency related to energy dissipation. In addition, a mesh size sensitivity analysis was performed to show the effects of size, shape and pattern of mesh on the results and cumulative probability distribution versus absolute relative error diagrams were applied to compare the accuracy of the models. After all, the best model of prediction was selected to simulate a real sand production in an oil well with 50 • inclination and 6 SPF in North Sea Reservoir. Review of experimental papers shows that these tests usually have several hypotheses for simplification. Rock strength, stress state, fluid flow properties, test duration, and sample dimensions are the most important parameters in sand production tests. Researchers usually focus on only one or two of these parameters, which may lead to many errors in contrast to reality. In addition, numerical methods have some deficiencies such as mesh size problems, lack of critical-state-based constitutive models, sanding criteria, and lack of sufficient research for the calibration procedure in the DEM model. A small change in both the numerical simulation input data and the experimental procedure leads to different results. Indeed, the experimental test of sand production with multiple hypotheses can qualitatively simulate the steps and shape of well or perforation failure not the exact sand production rate. Also, numerical simulation results are very sensitive due to uncertainties and errors of the model and input data. It has been shown that the results are highly dependent on every simple parameter such as the shape of the elements. The differences between experimental results and numerical modeling in only one perforation can be 2 to 10 times. Despite all errors and uncertainties in both the laboratory and modeling studies, the simulation of a real sand production in North Sea Reservoir with same sized element was relatively acceptable. This level of accuracy of the model can be very helpful in subsequent decision making and sand control management.
Sand production is one of the main research topics in the petroleum industry. This problematic ph... more Sand production is one of the main research topics in the petroleum industry. This problematic phenomenon is related to the mechanical and hydrodynamic behavior and reservoir specifications. Sand production often leads to equipment damage and significant losses. This is usually studied by experimental and numerical methods. This study first gives a brief overview of the methods used to predict sand production in terms of experimental tests, numerical simulation, and field data. The main objective of this research is to highlight the shortcomings of these methods. In addition, experimental hollow cylinder test data and widely used continues numerical simulation are used to investigate these shortcomings. This study is performed by scrutinizing the most important and basic parameters in numerical modeling including two constitutive models (Mohr-Coulomb elastic-perfectly plastic and Mohr-Coulomb cohesion softening/friction hardening failure criteria) and various element sizes and shape...
A B S T R A C T The design of an optimal sand control method and production management is a compl... more A B S T R A C T The design of an optimal sand control method and production management is a complex problem due to the simultaneous influence of various factors. Typical effective variables for choosing an optimum sand control method include geological, technical, economical, and expert's experience on similar projects. Some technical factors, which affect the optimum method, are the type of exclusion, gravel size of gravel pack and pre-packed screen, slot width and liner slot length, and productivity index reduction. The situation could be more complicated due to the uncertainty associated with various contributing factors. Therefore, it is crucial to develop a novel approach in order to select the best sand control method with a maximum level of confidence. In this study, to select an optimal sand control method, Multi Criteria Decision Matrix (MCDM) techniques including Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and, ELimination and Choice Expressing REality (ELECTRE) are used. To simulate fluid flow, an integrated model of reservoir, well, and surface facility is used based on actual oil field data collected from the south of Iran. Then, Design of Experiment (DOE) and Response Surface Methodology (RSM) are applied to optimize the controllable variables of the best selected sand control method by MCDM. Finally, Monte Carlo Simulation (MCS) is applied to perform sensitivity and uncertainty analysis in order to determine the crucial factors that control net present value (NPV). The results show that the best sand control method based on AHP, TOPSIS, and ELECTRE is the slotted liner. After that, three different methods of pre-packed, gravel pack, and wire wrapped are respectively the most efficient sand control methods based on an average score of all the MCDM techniques. The results also indicate that although the pre-packed screen has the highest NPV, it is not the best sand control method due to the influence of other efficient criteria. The result of sensitivity analysis using MCS in terms of contribution to total variance shows that slot width, slot density, and slot height controls 60.5%, 38.8%, and 0.7% of the NPV variation within the range of factors, respectively.
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Papers by M, Hossein Shahsavari