A Fully Implicit, Three-Dimensional, Three-Phase Simulator With Automatic History-Matching Capability

Tan, T.B.; Kalogerakis, Nicolas

doi:10.2118/21205-ms

Cited by 32 publications

(12 citation statements)

References 12 publications

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“…Sequential method can be considered as another variation of IMPES, where all equations are solved in an implicit fashion without a full coupling of the system. It is believed that the most stable scheme for subsurface multi-phase flow is the fully implicit method [1,15,16,44,53], which is also known as the simultaneous solution method in reservior simulation community, or simply the SS method. All the coupled nonlinear equations are solved simultaneously and implicitly in the SS method, usually using a Newton-type approach.…”

Section: Introductionmentioning

confidence: 99%

Nonlinearly preconditioned semismooth Newton methods for variational inequality solution of two-phase flow in porous media

Yang

Sun

Yang

2017

Journal of Computational Physics

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Section: Introductionmentioning

confidence: 99%

Nonlinearly preconditioned semismooth Newton methods for variational inequality solution of two-phase flow in porous media

Yang

Sun

Yang

2017

Journal of Computational Physics

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“…to find the nearest optimum near any point in the search space which produces results close to an acceptable solution. In general gradient methods have proven to be quite successful in this domain [1][2][3] . In addition, sensitivity analyses based on gradient methods can be used to determine model parameters which are most sensitive to the results in the vicinity of any point in the search space for which the gradients are calculated 4 .…”

Section: Methodsmentioning

confidence: 99%

“…In many engineering applications, simulations are based on a multidimensional solution space which generally contains a number of local optima. For reservoir characterizations a number of previous works have concentrated on local gradient based optimization strategies [1][2][3][4][5] . Gómez et al 6 have coupled a gradient method to a tunneling method with global optimization features.…”

Section: Introductionmentioning

confidence: 99%

Optimization Methods for History Matching of Complex Reservoirs

Schulze-Riegert¹,

Axmann²,

Haase³

et al. 2001

All Days

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractConventional direct optimization methods and Evolutionary Algorithms are applied to the problem of history matching in reservoir engineering. For the optimization of complex reservoir models the potential of parallel computing is investigated. Methods to improve the convergence of Evolutionary Algorithms by introducing expert knowledge is discussed. An interface program has been developed which links an industry standard reservoir simulator to an optimization software package designed as a multipurpose environment for parallel optimization. Permeabilities, fault transmissibilities as well as relative permeabilites and barrier locations have been included in the optimization. Results are presented for synthetic and real reservoirs with up to 30 wells and 40 design parameters. The potential and the area of applicability of the optimization method to the problem of reservoir modeling in various modeling phases are discussed. The improvement of performance based on parallelism in a network environment is evaluated. In conclusion, results suggest that Evolution Strategies can be successfully applied for generating possible solutions in the early modeling phase. The introduction of expert knowledge to the optimization methods is essential for reducing the multidimensional search space and improving convergence.

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“…The corresponding review of applied objective functions is presented in different papers, for instance, [20,25]. The most popular methods for optimization were Gauss-Newton type, based on sensitivity matrix [33][34][35]. Though adopted by the industry [36], they have shown poor computational efficiency for large problems typical for reservoir simulation.…”

Section: Introductionmentioning

confidence: 99%

Optimal Control of Field Development in a Closed Loop

Zakirov

Indrupskiy

et al. 2015

All Days

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The problem of optimum field development management has been always important, but for the recent years it acquired a special practical value. Intelligent field control systems, ЉsmartЉ wells and other technical achievements open up new possibilities for maximizing recovery without any additional costs for drilling and changes in development system. This task is of special relevance for hard-to-recover hydrocarbons -deposits with low-permeable heterogeneous reservoirs, high water-cut fields, heavy oil reservoirs, remaining reserves of low-pressure gas fields, gas condensate deposits, oil rims, etc.Today field development management is known more as a technical problem of operating and measuring hardware implementation, while scientific aspects are insufficiently developed. The most accurate definition of this problem, representing its practical value, consists in the management of development in the closed loop, when assimilation of data from various sources is continiuosly followed by production optimization based on the history-matched 3D model. Production dynamics forecasting for the set of production/injection controls on wells or separate intervals of ЉsmartЉ wells is carried out in multiphase non-stationary statement on a sector or full-scale 3D model. To incorporate permanently incoming field information, the automated adaptation (history matching) of a 3D model to the actual well operation and testing data is carried out periodically.Authors have implemented a geologically consistent algorithm for automated 3D model history matching, based on the effective modern methods of the optimum control theory. In contrast to traditional approaches, not individual properties of reservoir zones are adjusted in the history matching procedure, but rather initial parameters of anisotropic geostatistical fields and petrophysical relations, taking into account the facial model of the reservoir. The hhistory-matched 3D model is used for searching at each time step for the optimal well operating controls maximizing an integral quality criterion -e.g., discounted oil production or given criterion of economic efficiency for the forecast period. Field surface facilities group limitations on fluids production/injection volumes and individual limitations of wells on operating pressures are considered. The efficiency of optimization algorithm is as well granted by use of the modern optimum control theory methods.The developed algorithms for soluton of field development management problems in the closed loop are implemented in the authors' in-house software SimMatch®. Within the forward problem solution it implements the extended black oil model and is comparable in functionality to the main modules of commercial simulators. As an example of the implementation of the proposed approach, several cases of geologically consistent history matching and optimum waterflooding control for deposits with highly heterogeneous anisotropic fields of reservoir properties (both flow and capacity parameters) are presented in the paper.For the fir...

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A Fully Implicit, Three-Dimensional, Three-Phase Simulator With Automatic History-Matching Capability

Cited by 32 publications

References 12 publications

Nonlinearly preconditioned semismooth Newton methods for variational inequality solution of two-phase flow in porous media

Nonlinearly preconditioned semismooth Newton methods for variational inequality solution of two-phase flow in porous media

Optimization Methods for History Matching of Complex Reservoirs

Optimal Control of Field Development in a Closed Loop

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