The Experts below are selected from a list of 24 Experts worldwide ranked by ideXlab platform
Amiya K. Jana - One of the best experts on this subject based on the ideXlab platform.
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ICARCV - A nonlinear exponential observer for a batch distillation
2010 11th International Conference on Control Automation Robotics & Vision, 2010Co-Authors: Amiya K. JanaAbstract:In this contribution, a state observer, namely nonlinear exponential observer (NEO) is proposed for a batch distillation process. This estimation scheme mainly computes the imprecisely known parameter (augmented state) based on the available measurement. For the representative distillation unit, the state predictor is formulated on the basis of only a Component Material Balance equation around the condenser-reflux drum system. It clearly indicates the existence of a process/model mismatch and the effect of this discrepancy is efficiently taken care of by the corrector part of the NEO estimator. Several simulation experiments have been executed to show the observer error convergence ability. The less computational requirements and simple design make the closed-loop observer attractive for online use.
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Nonlinear Exponential Estimator Design for a Distillation Column
Chemical Product and Process Modeling, 2008Co-Authors: Amiya K. JanaAbstract:This article presents the design of an exponential state estimator for a distillation column. The proposed algorithm mainly estimates the imprecisely known parameters based on the available measurements. For the example distillation column, the nonlinear state estimator is formed with two Component Material Balance equations; one is around the condenser-reflux drum system and the other one is around the reboiler-column base system. As a result, there is an excessive process/model mismatch. In this situation, the proposed scheme estimates the augmented states with sufficient accuracy. The simulation experiments have been performed to investigate the convergence ability of the estimator. The less computational requirements and simple design make the estimator attractive for online use.
Faruk Civan - One of the best experts on this subject based on the ideXlab platform.
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Determination of multi-Component gas and water equilibrium and non-equilibrium sorption isotherms in carbonaceous solids from early-time measurements
Fuel, 2006Co-Authors: Hossein Jahediesfanjani, Faruk CivanAbstract:A rapid method is presented for determination of the multi-Component gas and water sorption isotherms on carbonaceous solids from the non-equilibrium sorption data. This approach alleviates the long-time data requirement of the traditional volumetric gas adsorption technique used to construct gas isotherms requiring a series of equilibrium sorption measurements by successive pressure increments, particularly resorted in the coalbed methane industry. This is accomplished by the application of the non-equilibrium thermodynamics, multi-Component Material Balance, gas sorption, and dissolution kinetic considerations for the gas adsorbed by carbonaceous solids and the gas dissolved in water under the effect of pressure, temperature, and grain size. The capabilities of the new technique in reducing the time required for construction of an isotherm are demonstrated by analyzing a series of the non-equilibrium sorption measurements and projecting the results to the equilibrium case. Moreover, it is demonstrated that the present model enables constructing both the equilibrium and non-equilibrium multi-Component gas and water sorption isotherms in any carbonaceous solids and particularly coals simultaneously in relatively shorter time and with higher accuracy.
Kai Liu - One of the best experts on this subject based on the ideXlab platform.
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A General Unstructured-Grid, Equation-of-State-Based, Fully Implicit Thermal Simulator for Complex Reservoir Processes
SPE Journal, 2009Co-Authors: Kai Liu, Ganesan Subramanian, David I. Dratler, Jean-pierre Lebel, Jeffrey A. YerianAbstract:Summary This paper describes a general unstructured-grid, equation-of-state- (EOS) based, fully implicit thermal simulator for complex reservoir processes. Under the unstructured grid framework, the simulator uses Newton's method to solve Component Material-Balance equations, energy-Balance equation, and volume-Balance equation for Component moles, energy, and pressure, where chemical reactions and external heat sources/sinks are treated in source terms. Because of the similarity among Component Material-Balance equations and the energy-Balance equation, energy is treated as a "Component" to achieve a uniform formulation with common code for all simulations (black-oil, compositional, and thermal). The thermal simulator was validated using analytical models and other thermal simulators. The thermal simulator is used to study grid-orientation problems and to design and optimize Cold Lake heavy-oil development. Introduction Modern reservoir management requires a simulator to represent reservoir details accurately using fine-scale geologic features, complex well paths, and modeling of large-scale interactions among multiple fields. Unstructured gridding makes it possible to capture and honor more geologic and engineering detail in reservoir-simulation models with greater exactness than Cartesian-based reservoir grids. However, industry generally has been reluctant to apply this capability to practical reservoir simulation partly because of concerns about potential loss in computational efficiency. Many papers have been published under Cartesian-based framework (Mifflin et al. 1991; Watts 1986; Coats 1980; Watts et al. 2005). Few papers are available to address reservoir simulation issues under general unstructured-grid framework (Naccache 1997; Beckner et al. 2001, 2006; Heinemann et al. 1991; Usadi et al. 2007; Karypis and Kumar 1998).
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A General Unstructured Grid, EOS-Based, Fully Implicit Thermal Simulator for Complex Reservoir Processes
All Days, 2007Co-Authors: Kai Liu, Ganesan Subramanian, David I. Dratler, Jean-pierre Lebel, Jeffrey A. YerianAbstract:Abstract This paper describes a general unstructured grid, EOS-based, fully-implicit thermal simulator for complex reservoir processes. Under the unstructured grid framework, the simulator uses Newton's method to solve Component Material Balance equations, energy Balance equation and volume Balance equation for Component moles, energy and pressure, where chemical reactions and/or external heat sources/sinks are treated in source terms. Because of the similarity among Component Material Balance equations and the energy Balance equation, energy is treated as a "Component" to achieve a uniform formulation with common code for all simulations (black oil, compositional and thermal). The thermal simulator was validated using analytical models as well as other thermal simulators. Application of the thermal simulator includes studies of grid-orientation problems and to design and optimise Cold Lake heavy oil development. Introduction Modern reservoir management requires a simulator to accurately represent reservoir details using fine-scale geologic features, complex well paths, and modeling of large-scale interactions between multiple fields. Unstructured gridding makes it possible to capture and honor more geologic and engineering detail in reservoir simulation models with greater exactness than Cartesian-based reservoir grids. However, industry has been generally reluctant to apply this capability to practical reservoir simulation due in part to concerns about potential loss in computational efficiency. Many papers have been published under Cartesian-based framework1–5. Few papers are available to address reservoir simulation issues under general unstructured grid framework6–11. In 2001, Beckner, et al.6 presented ExxonMobil's new unstructured grid reservoir simulation system, which discussed field examples involving complex geologic features (e.g. non-vertical faults and stratigraphic pinchouts) and multiple reservoirs connected to a common production infrastructure. It was reported that the simulator significantly reduces simulation cycle-time through ease-of-use and integration with geologic models. One example indicated that about 100,000 blocks can represent the equivalent of 1.6 million rectangular grid blocks for achieving accurate geologic features. One of the most important aspects for unstructured reservoir simulator development is the linear solver for solving large linear system created by an unstructured grid which cannot be efficiently solved by conventional solution methods normally applied to simulators using rectangular gridding. Beckner, et al.8 in 2006 reported their collaborative effort on developing an unstructured linear solver library called SparSol, which includes a numerical library of scaling and reordering methods, preconditioners and iterative methods. Results show that SparSol is faster than several popular, freely-available packages for the set of matrices tested. Usadi, et al.9 reported their experiences with parallelizing an unstructured reservoir simulator on SMP machines. Included in their paper are how parallelization is performed at a high level through several variants of data partitioning adapted to the specific algorithmic needs, that solver convergence rate can be strongly dependent on simulator determined data partitioning, and that well management performance can be strongly dependent on the way reservoir engineers have applied their constraints and field production analysis. The next few sections of this paper present an overview of the simulation equations, solution procedures, and some discussions. Examples are given to illustrate simulator results, to demonstrate how the simulator can reduce grid-orientation problems and how the equation of state (EOS) method can be used in thermal simulation. The final section contains the conclusions resulting from this work.
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Reduce the Number of Components for Compositional Reservoir Simulation
All Days, 2001Co-Authors: Kai LiuAbstract:Abstract The need to predict reservoir fluid compositional changes under varying pressures and depletion processes arises because the hydrocarbon recovery of some types of reservoirs is strongly composition-dependent. Since hydrocarbon Component Material Balance equations must be solved in compositional reservoir simulation, both computer memory requirements and simulation run time are greatly increased. This paper presents a series of technologies, including a Fully Automatic Regression Technique, a Best Lumping Scheme, and a Fully Automatic Reservoir Fluid Characterization procedure, to reduce the number of Components needed to characterize a reservoir fluid using an Equation of State (EOS). As a result, the compositional reservoir simulation run time can be greatly reduced without reducing the required accuracy of the match with available laboratory data. Applications indicate that a significant speedup has been achieved using fewer Components to model the reservoir production processes while the predicted reservoir performance is equivalent to that achieved using many more Components. Introduction Compositional simulation models assume that, by nature, reservoir fluid properties are dependent not only upon the reservoir temperature and pressure but also on the composition of the fluids. For each grid block, the principles of Component mass conservation and phase equilibrium criteria are used to calculate the phase pressures, saturations, and compositions at each time step. Compositional simulation is needed to model such reservoir production processes as depletion of volatile oil and gas condensate reservoirs, miscible flooding, and gas cycling. Since compositional simulation models are based on Component mass Balance equations, the number of primary equations per grid block is Nc+1, where Nc is the number of Components in the hydrocarbon system1. The naturally-occuring petroleum deposits that the petroleum engineer encounters are composed of organic chemicals. A typical crude oil contains thousands of different chemical compounds. When a reservoir fluid is represented by a large number of Components, the computer storage requirements are greatly increased while the simulation run time is greatly increased. It is well known that the computer time and core required by compositional models are substantially greater than those need by black oil models. The larger computer requirements of compositional models result from two primary problems:representation of the reservoir fluid as an Nc+1 Component system, i.e. a system of Nc+1 partial differential equations to be solved; andthe nonlinear character of the compositional equations. The nonlinearity of the compositional model equations is more troublesome than that of the black oil model. The number of unknown functions in compositional models may be larger by an order of magnitude than in the case of black oil models because the compositions of each phase must be calculated, in addition to the pressure and saturations. As a result of these many unknown functions, the number of procedures for computing them continues to increase. Therefore, reducing the number of Components has been a prerequisite step for compositional simulation. When reservoir fluid samples are withdrawn and sent to PVT laboratory, some standard procedures are followed to perform PVT analysis, which involve the measurement of the fluid compositions, molecular weight, viscosity, compressibility, saturation pressure, formation volume factor, solubility, differential liberation, constant volume depletion, and constant composition expansion. Depending on anticipated production mechanisms, additional tests may be required, such as swelling test, miscibility test, etc.
Jeffrey A. Yerian - One of the best experts on this subject based on the ideXlab platform.
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A General Unstructured-Grid, Equation-of-State-Based, Fully Implicit Thermal Simulator for Complex Reservoir Processes
SPE Journal, 2009Co-Authors: Kai Liu, Ganesan Subramanian, David I. Dratler, Jean-pierre Lebel, Jeffrey A. YerianAbstract:Summary This paper describes a general unstructured-grid, equation-of-state- (EOS) based, fully implicit thermal simulator for complex reservoir processes. Under the unstructured grid framework, the simulator uses Newton's method to solve Component Material-Balance equations, energy-Balance equation, and volume-Balance equation for Component moles, energy, and pressure, where chemical reactions and external heat sources/sinks are treated in source terms. Because of the similarity among Component Material-Balance equations and the energy-Balance equation, energy is treated as a "Component" to achieve a uniform formulation with common code for all simulations (black-oil, compositional, and thermal). The thermal simulator was validated using analytical models and other thermal simulators. The thermal simulator is used to study grid-orientation problems and to design and optimize Cold Lake heavy-oil development. Introduction Modern reservoir management requires a simulator to represent reservoir details accurately using fine-scale geologic features, complex well paths, and modeling of large-scale interactions among multiple fields. Unstructured gridding makes it possible to capture and honor more geologic and engineering detail in reservoir-simulation models with greater exactness than Cartesian-based reservoir grids. However, industry generally has been reluctant to apply this capability to practical reservoir simulation partly because of concerns about potential loss in computational efficiency. Many papers have been published under Cartesian-based framework (Mifflin et al. 1991; Watts 1986; Coats 1980; Watts et al. 2005). Few papers are available to address reservoir simulation issues under general unstructured-grid framework (Naccache 1997; Beckner et al. 2001, 2006; Heinemann et al. 1991; Usadi et al. 2007; Karypis and Kumar 1998).
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A General Unstructured Grid, EOS-Based, Fully Implicit Thermal Simulator for Complex Reservoir Processes
All Days, 2007Co-Authors: Kai Liu, Ganesan Subramanian, David I. Dratler, Jean-pierre Lebel, Jeffrey A. YerianAbstract:Abstract This paper describes a general unstructured grid, EOS-based, fully-implicit thermal simulator for complex reservoir processes. Under the unstructured grid framework, the simulator uses Newton's method to solve Component Material Balance equations, energy Balance equation and volume Balance equation for Component moles, energy and pressure, where chemical reactions and/or external heat sources/sinks are treated in source terms. Because of the similarity among Component Material Balance equations and the energy Balance equation, energy is treated as a "Component" to achieve a uniform formulation with common code for all simulations (black oil, compositional and thermal). The thermal simulator was validated using analytical models as well as other thermal simulators. Application of the thermal simulator includes studies of grid-orientation problems and to design and optimise Cold Lake heavy oil development. Introduction Modern reservoir management requires a simulator to accurately represent reservoir details using fine-scale geologic features, complex well paths, and modeling of large-scale interactions between multiple fields. Unstructured gridding makes it possible to capture and honor more geologic and engineering detail in reservoir simulation models with greater exactness than Cartesian-based reservoir grids. However, industry has been generally reluctant to apply this capability to practical reservoir simulation due in part to concerns about potential loss in computational efficiency. Many papers have been published under Cartesian-based framework1–5. Few papers are available to address reservoir simulation issues under general unstructured grid framework6–11. In 2001, Beckner, et al.6 presented ExxonMobil's new unstructured grid reservoir simulation system, which discussed field examples involving complex geologic features (e.g. non-vertical faults and stratigraphic pinchouts) and multiple reservoirs connected to a common production infrastructure. It was reported that the simulator significantly reduces simulation cycle-time through ease-of-use and integration with geologic models. One example indicated that about 100,000 blocks can represent the equivalent of 1.6 million rectangular grid blocks for achieving accurate geologic features. One of the most important aspects for unstructured reservoir simulator development is the linear solver for solving large linear system created by an unstructured grid which cannot be efficiently solved by conventional solution methods normally applied to simulators using rectangular gridding. Beckner, et al.8 in 2006 reported their collaborative effort on developing an unstructured linear solver library called SparSol, which includes a numerical library of scaling and reordering methods, preconditioners and iterative methods. Results show that SparSol is faster than several popular, freely-available packages for the set of matrices tested. Usadi, et al.9 reported their experiences with parallelizing an unstructured reservoir simulator on SMP machines. Included in their paper are how parallelization is performed at a high level through several variants of data partitioning adapted to the specific algorithmic needs, that solver convergence rate can be strongly dependent on simulator determined data partitioning, and that well management performance can be strongly dependent on the way reservoir engineers have applied their constraints and field production analysis. The next few sections of this paper present an overview of the simulation equations, solution procedures, and some discussions. Examples are given to illustrate simulator results, to demonstrate how the simulator can reduce grid-orientation problems and how the equation of state (EOS) method can be used in thermal simulation. The final section contains the conclusions resulting from this work.
Hossein Jahediesfanjani - One of the best experts on this subject based on the ideXlab platform.
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Determination of multi-Component gas and water equilibrium and non-equilibrium sorption isotherms in carbonaceous solids from early-time measurements
Fuel, 2006Co-Authors: Hossein Jahediesfanjani, Faruk CivanAbstract:A rapid method is presented for determination of the multi-Component gas and water sorption isotherms on carbonaceous solids from the non-equilibrium sorption data. This approach alleviates the long-time data requirement of the traditional volumetric gas adsorption technique used to construct gas isotherms requiring a series of equilibrium sorption measurements by successive pressure increments, particularly resorted in the coalbed methane industry. This is accomplished by the application of the non-equilibrium thermodynamics, multi-Component Material Balance, gas sorption, and dissolution kinetic considerations for the gas adsorbed by carbonaceous solids and the gas dissolved in water under the effect of pressure, temperature, and grain size. The capabilities of the new technique in reducing the time required for construction of an isotherm are demonstrated by analyzing a series of the non-equilibrium sorption measurements and projecting the results to the equilibrium case. Moreover, it is demonstrated that the present model enables constructing both the equilibrium and non-equilibrium multi-Component gas and water sorption isotherms in any carbonaceous solids and particularly coals simultaneously in relatively shorter time and with higher accuracy.