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ENGINEERING (1206 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 19)
AAPG Bulletin     Hybrid Journal   (Followers: 6)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
ACS Nano     Full-text available via subscription   (Followers: 234)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 6)
Advanced Science     Open Access   (Followers: 5)
Advanced Science Focus     Free   (Followers: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 7)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 15)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 10)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 21)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 28)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 12)
Advances in Polymer Science     Hybrid Journal   (Followers: 41)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 37)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 1)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 4)
AIChE Journal     Hybrid Journal   (Followers: 30)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access  
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 9)
American Journal of Environmental Engineering     Open Access   (Followers: 16)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Regional Science     Hybrid Journal   (Followers: 7)
Annals of Science     Hybrid Journal   (Followers: 7)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 6)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 15)
Applied Clay Science     Hybrid Journal   (Followers: 5)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Network Science     Open Access  
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 3)
Applied Sciences     Open Access   (Followers: 2)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 7)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 3)
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 1)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 8)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Avances en Ciencias e Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Batteries     Open Access   (Followers: 4)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 23)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 3)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access  
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 10)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 31)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 39)
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription  
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 14)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 3)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 14)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 41)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Thermal Engineering     Open Access   (Followers: 3)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 8)
Catalysis Science and Technology     Free   (Followers: 6)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 8)
CEAS Space Journal     Hybrid Journal  
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal   (Followers: 1)
CFD Letters     Open Access   (Followers: 6)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 21)
Clay Minerals     Full-text available via subscription   (Followers: 10)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 5)
Coatings     Open Access   (Followers: 3)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 1)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 13)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 26)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 258)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 180)
Composites Part B : Engineering     Hybrid Journal   (Followers: 236)
Composites Science and Technology     Hybrid Journal   (Followers: 215)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 14)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Science and Engineering     Open Access   (Followers: 17)
Computers & Geosciences     Hybrid Journal   (Followers: 28)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 5)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 4)
Computers and Geotechnics     Hybrid Journal   (Followers: 10)
Computing and Visualization in Science     Hybrid Journal   (Followers: 5)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 30)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 6)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 9)
Control Engineering Practice     Hybrid Journal   (Followers: 42)
Control Theory and Informatics     Open Access   (Followers: 8)
Corrosion Science     Hybrid Journal   (Followers: 25)
CT&F Ciencia, Tecnologia y Futuro     Open Access  
CTheory     Open Access  
Current Applied Physics     Full-text available via subscription   (Followers: 4)
Current Science     Open Access   (Followers: 58)

        1 2 3 4 5 6 7 | Last

Journal Cover Computational Geosciences
  [SJR: 1.477]   [H-I: 43]   [14 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1573-1499 - ISSN (Online) 1420-0597
   Published by Springer-Verlag Homepage  [2353 journals]
  • A simplified enhanced MPFA formulation for the elliptic equation on
           general grids
    • Authors: Wenjuan Zhang; Mohammed Al Kobaisi
      Pages: 621 - 643
      Abstract: Abstract Multi-point flux approximation (MPFA) has proven to be a powerful tool for discretizing the diffusion equation on general grids with heterogeneous anisotropic permeability tensors and hence, removing the O(1) error introduced by two-point flux approximation (TPFA) for non-K-orthogonal grids. However, it is well known that the classical MPFA-O suffers from monotonicity issues and strong unphysical oscillations can be present for highly anisotropic media. Enriched MPFA (EMPFA) and MPFA with full pressure support (FPS) have been proposed in the literature to reduce the strength of the oscillations. In this work, we present a simplified enhanced MPFA formulation (eMPFA) on general grids in 2D. Similar to the MPFA-O method, our formulation starts with an interaction region formed around the vertex of control volumes. Potential at the vertex is introduced as an auxiliary unknown in addition to potential at the centroids of the control volume faces. The original EMPFA and FPS solve the diffusion equation on a small volume around the vertex to close the local system of equations. To simplify the formulation, we propose an average technique to approximate potential at the vertex. Utilizing the potential value at the vertex, full potential continuity can be imposed on control volume faces to construct a more accurate flux across control volume faces. Extensive numerical experiments are conducted to test the eMPFA formulation. Specifically, we compare eMPFA with MPFA-O and two variants of EMPFA in detail. The results show that our average technique is quite robust even for highly distorted quadrilateral grids with large permeability anisotropy ratios and solutions of our formulation are in excellent agreement with EMPFA using bilinear pressure support. The new scheme also reproduces linear potential solutions and has comparable, and in some cases even better, convergence properties to those of the MPFA-O method. Finally, we generalize the formulation to include structured and unstructured triangular and polygonal grids and present the results.
      PubDate: 2017-08-01
      DOI: 10.1007/s10596-017-9638-z
      Issue No: Vol. 21, No. 4 (2017)
  • Flow-based dissimilarity measures for reservoir models: a spatial-temporal
           tensor approach
    • Authors: Edwin Insuasty; Paul M. J. Van den Hof; Siep Weiland; Jan-Dirk Jansen
      Pages: 645 - 663
      Abstract: Abstract In reservoir engineering, it is attractive to characterize the difference between reservoir models in metrics that relate to the economic performance of the reservoir as well as to the underlying geological structure. In this paper, we develop a dissimilarity measure that is based on reservoir flow patterns under a particular operational strategy. To this end, a spatial-temporal tensor representation of the reservoir flow patterns is used, while retaining the spatial structure of the flow variables. This allows reduced-order tensor representations of the dominating patterns and simple computation of a flow-induced dissimilarity measure between models. The developed tensor techniques are applied to cluster model realizations in an ensemble, based on similarity of flow characteristics.
      PubDate: 2017-08-01
      DOI: 10.1007/s10596-017-9641-4
      Issue No: Vol. 21, No. 4 (2017)
  • Applying soft computing methods to predict the uniaxial compressive
           strength of rocks from schmidt hammer rebound values
    • Authors: Hadi Fattahi
      Pages: 665 - 681
      Abstract: Abstract The uniaxial compressive strength (UCS) of rock is widely used in designing underground and surface rock structures. The testing procedure of this rock strength is expensive and time consuming. In addition, it requires well-prepared rock cores. Therefore, indirect tests are often used to estimate the UCS, such as the Schmidt hammer test. This test is very easy to carry out because it necessitates less or no sample preparation and the testing equipment is less sophisticated. In addition, it can be used easily in the field. As a result, comparing with uniaxial compression test, indirect test is simpler, faster, and more economical. In this paper, the application of soft computing methods for data analysis named support vector regression (SVR) optimized by artificial bee colony algorithm (ABC) and adaptive neuro-fuzzy inference system-subtractive clustering method (ANFIS-SCM) to estimate the UCS of rocks from Schmidt hammer rebound values is demonstrated. The estimation abilities offered using SVR-ABC and ANFIS-SCM were presented by using experimental data given in open-source literatures. In these models, the Schmidt hammer rebound values (T1–T3, R1–R4) were utilized as the input parameters, while the UCS was the output parameter. Various statistical performance indexes were utilized to compare the performance of those estimation models. The results achieved indicate that the ANFIS-SCM model has strong potential to indirect estimation of the UCS of rocks from the Schmidt hammer rebound values with high degree of accuracy and robustness.
      PubDate: 2017-08-01
      DOI: 10.1007/s10596-017-9642-3
      Issue No: Vol. 21, No. 4 (2017)
  • Image-oriented distance parameterization for ensemble-based seismic
           history matching
    • Authors: Yanhui Zhang; Olwijn Leeuwenburgh
      Pages: 713 - 731
      Abstract: Abstract Time-lapse (4D) seismic data provides spatial information about dynamic changes in a reservoir. This information can be used in combination with production data from wells to adjust reservoir models through a history matching procedure. However, quantitative use of 4D seismic data for history matching is generally challenging. This is partly because of the high dimensionality and the large uncertainty associated with the seismic data. To circumvent these difficulties, some methods have been proposed with a focus on reparameterization of seismic attributes and reformulation of seismic objective functions so that the integration of 4D seismic data is more robust and efficient. A distance parameterization of seismic anomalies due to saturation effects was previously proposed to history match reservoir models in combination with the ensemble Kalman filter (EnKF). Because the parameterization reduces both nonlinearity and the effective number of data, an improved functioning of the EnKF could be achieved. The distances measured from simulated fronts to observed fronts were used as innovations in the EnKF such that the same number of simulated measurements is obtained for each simulated model realization. However, it turns out that this definition is not always an effective measure of the actual differences between simulated and observed fronts as we demonstrate through the experiments in this paper. Using concepts from the field of image analysis, we generalize the defined innovations as a directed local Hausdorff distance, providing a one-directional dissimilarity measure (from simulated to observed fluid fronts, or in a broader sense, to detected features in 4D seismic data). A more robust distance parameterization approach is proposed based on the full local Hausdorff distance that measures the distances between observed and simulated fronts in both directions. Additionally, a comparison is made between contour-based and area-based characterizations of the differences between images that are commonly used for shape matching within the field of image analysis. Numerical experiments in a synthetic 2D case and realistic synthetic 3D case based on the Norne field are presented in which improved functioning of the proposed method is demonstrated.
      PubDate: 2017-08-01
      DOI: 10.1007/s10596-017-9652-1
      Issue No: Vol. 21, No. 4 (2017)
  • Engineering applications of 2D and 3D finite element mesh generation in
           hydrogeology and water resources
    • Authors: Lu Sun; Gour-Tsyh Yeh; Xinwu Ma; FangPang Lin; Guoqun Zhao
      Pages: 733 - 758
      Abstract: Abstract This paper develops an automatic density-controlled 2-D and 3-D finite element mesh generation system to solve practical engineering applications in geology, hydraulics, hydrology, water resources, etc. The Delaunay triangulation method is adopted to create triangular meshes based on the required density specified by users. A triangle-to-quadrilateral conversion method is used to generate quadrilateral meshes adaptively. Density control algorithms of adaptive 2-D mesh generation are presented to satisfy the various requirements of the overland and subsurface hydrogeology and water resources in the actual target area. According to the alignment of boundary edges and distribution of surface nodes, this paper proposes the main algorithm and basic criteria to generate supplementary triangle and quadrilateral meshes for filling the water regions of river reaches and junctions with storage. A stretch mode is proposed to generate triangular prism and hexahedral meshes by stretching the 2-D mesh into 3-D space based on the materials of geometric regions. The 1-D/2-D/3-D correspondence between the finite element mesh and the river reaches, junctions with and without storage, ponds, lakes, control structures and fractures is established. Finally, practical 2-D and 3-D meshing applications are provided to demonstrate the accuracy and effectiveness of the finite element mesh generator developed in this paper.
      PubDate: 2017-08-01
      DOI: 10.1007/s10596-017-9654-z
      Issue No: Vol. 21, No. 4 (2017)
  • Adaptive dynamic/quasi-static pore network model for efficient multiphase
           flow simulation
    • Authors: Mohamed Regaieg; Arthur Moncorgé
      Pages: 795 - 806
      Abstract: Abstract Pore-scale simulation is increasingly used to study various phenomena that cannot be reproduced by conventional Darcy-based simulators. Direct numerical simulation on systems larger than a few millimeters is too computationally demanding. Pore network modeling (PNM) is a practical way to study the flow at pore scale for a representative elementary volume (REV) in a reasonable time. Pore network models can be divided into dynamic and quasi-static models. Dynamic models explicitly consider the competition between capillary and viscous forces. As they require pressure gradient calculation, they can be computationally expensive. Quasi-static models assume that the flow is only driven by capillary forces and avoids the need for pressure computations. Although they are very computationally efficient, the usage of these models is limited to capillary-dominated flow regimes obtained generally at low capillary numbers. We propose to combine the two approaches in an adaptive model, taking advantage of the speed of a quasi-static algorithm when the flow is governed by capillary forces, and that can simulate viscous effects when they are significant. We propose a criterion to localize the pressure solution in important areas to enhance the computational efficiency of the algorithm even in viscous dominated regimes. In this paper, we first describe our adaptive pore network model. Then, we show that using the capillary number as a switching criterion is not good enough to characterize the domain where the flow is controlled by capillary forces. Therefore, we present a newly defined criterion to switch between the dynamic and quasi-static flow regimes. Finally, we present several test cases where we show that the adaptive algorithm can considerably improve the computational performance of the pore network simulator without losing accuracy of the solution by treating large regions of models with the quasi-static algorithm. For capillary-dominated regimes, the observed speed-up can reach 16,000 for one million-node 3D networks. For viscous dominated regimes, the speed-up can reach 43 for one million-node 3D networks.
      PubDate: 2017-08-01
      DOI: 10.1007/s10596-017-9661-0
      Issue No: Vol. 21, No. 4 (2017)
  • Ensemble clustering for efficient robust optimization of naturally
           fractured reservoirs
    • Authors: Zhe Liu; Fahim Forouzanfar
      Abstract: Abstract In the development of naturally fractured reservoirs (NFRs), the existence of natural fractures induces severe fingering and breakthrough. To manage the flooding process and improve the ultimate recovery, we propose a numerical workflow to generate optimal production schedules for smart wells, in which the inflow control valve (ICV) settings can be controlled individually. To properly consider the uncertainty introduced by randomly distributed natural fractures, the robust optimization would require a large ensemble size and it would be computationally demanding. In this work, a hierarchical clustering method is proposed to select representative models for the robust optimization in order to avoid redundant simulation runs and improve the efficiency of the robust optimization. By reducing the full ensemble of models into a small subset ensemble, the efficiency of the robust optimization algorithm is significantly improved. The robust optimization is performed using the StoSAG scheme to find the optimal well controls that maximize the net-present-value (NPV) of the NFR’s development. Due to the discrete property of a natural fracture field, traditional feature extraction methods such as model-parameter-based clustering may not be directly applicable. Therefore, two different kinds of clustering-based optimization methods, a state-based (e.g., s w profiles) clustering and a response-based (e.g., production rates) clustering, are proposed and compared. The computational results show that the robust clustering optimization could increase the computational efficiency significantly without sacrificing much expected NPV of the robust optimization. Moreover, the performance of different clustering algorithms varies widely in correspondence to different selections of clustering features. By properly extracting model features, the clustered subset could adequately represent the uncertainty of the full ensemble.
      PubDate: 2017-09-18
      DOI: 10.1007/s10596-017-9689-1
  • A new insight into onset of inertial flow in porous media using network
           modeling with converging/diverging pores
    • Authors: Maziar Veyskarami; Amir Hossein Hassani; Mohammad Hossein Ghazanfari
      Abstract: Abstract The network modeling approach is applied to provide a new insight into the onset of non-Darcy flow through porous media. The analytical solutions of one-dimensional Navier-Stokes equation in sinusoidal and conical converging/diverging throats are used to calculate the pressure drop/flow rate responses in the capillaries of the network. The analysis of flow in a single pore revealed that there are two different regions for the flow coefficient ratio as a function of the aspect ratio. It is found that the critical Reynolds number strongly depends on the pore geometrical properties including throat length, average aspect ratio, and average coordination number of the porous media, and an estimation of such properties is required to achieve more reliable predictions. New criteria for the onset of non-Darcy flow are also proposed to overcome the lack of geometrical data. Although the average aspect ratio is the main parameter which controls the inertia effects, the effect of tortuosity on the onset of non-Darcy flow increases when the coordination number of media decreases. In addition, the higher non-Darcy coefficient does not essentially accelerate the onset of inertial flow. The results of this work can help to better understand how the onset of inertial flow may be controlled/changed by the pore architecture of porous media.
      PubDate: 2017-09-14
      DOI: 10.1007/s10596-017-9695-3
  • Surrogate combining harmonic decomposition and polynomial chaos for
           seismic shear waves in uncertain media
    • Abstract: Abstract A polynomial chaos (PC) surrogate is proposed to reconstruct seismic time series in one-dimensional (1D) uncertain media. Our approach overcomes the deterioration of the PC convergence rate during long time integration. It is based on a double decomposition of the signal: a damped harmonic decomposition combined with a polynomial chaos expansion of the four coefficients of each harmonic term (amplitude, decay constant, pulsation, and phase). These PC expansions are obtained through the least squares method which requires the solution of nonlinear least squares problems for each sample point of the stochastic domain. The use of the surrogate is illustrated on vertically incident plane waves traveling in 1D layered, vertically stratified, isotropic, viscoelastic soil structure with uncertainties in the geological data (geometry, wave velocities, quality factors). Computational tests show that the stochastic coefficients can be efficiently represented with a low-order PC expansion involving few evaluations of the direct model. For the test cases, a global sensitivity analysis is performed in time and frequency domains to investigate the relative impact of the random parameters.
      PubDate: 2017-09-07
      DOI: 10.1007/s10596-017-9677-5
  • Higher resolution total velocity Vt and Va finite-volume formulations on
           cell-centred structured and unstructured grids
    • Authors: Ya-wei Xie; Michael G. Edwards
      Abstract: Abstract Novel cell-centred finite-volume formulations are presented for incompressible and immiscible two-phase flow with both gravity and capillary pressure effects on structured and unstructured grids. The Darcy-flux is approximated by a control-volume distributed multipoint flux approximation (CVD-MPFA) coupled with a higher resolution approximation for convective transport. The CVD-MPFA method is used for Darcy-flux approximation involving pressure, gravity, and capillary pressure flux operators. Two IMPES formulations for coupling the pressure equation with fluid transport are presented. The first is based on the classical total velocity Vt fractional flow (Buckley Leverett) formulation, and the second is based on a more recent Va formulation. The CVD-MPFA method is employed for both Vt and Va formulations. The advantages of both coupled formulations are contrasted. The methods are tested on a range of structured and unstructured quadrilateral and triangular grids. The tests show that the resulting methods are found to be comparable for a number of classical cases, including channel flow problems. However, when gravity is present, flow regimes are identified where the Va formulation becomes locally unstable, in contrast to the total velocity formulation. The test cases also show the advantages of the higher resolution method compared to standard first-order single-point upstream weighting.
      PubDate: 2017-09-05
      DOI: 10.1007/s10596-017-9669-5
  • Comparison between cell-centered and nodal-based discretization schemes
           for linear elasticity
    • Authors: Halvor M. Nilsen; Jan Nordbotten; Xavier Raynaud
      Abstract: Abstract In this paper, we study newly developed methods for linear elasticity on polyhedral meshes. Our emphasis is on applications of the methods to geological models. Models of subsurface, and in particular sedimentary rocks, naturally lead to general polyhedral meshes. Numerical methods which can directly handle such representation are highly desirable. Many of the numerical challenges in simulation of subsurface applications come from the lack of robustness and accuracy of numerical methods in the case of highly distorted grids. In this paper, we investigate and compare the Multi-Point Stress Approximation (MPSA) and the Virtual Element Method (VEM) with regard to grid features that are frequently seen in geological models and likely to lead to a lack of accuracy of the methods. In particular, we look at how the methods perform near the incompressible limit. This work shows that both methods are promising for flexible modeling of subsurface mechanics.
      PubDate: 2017-09-04
      DOI: 10.1007/s10596-017-9687-3
  • Assisted history matching for the inversion of fractures based on discrete
    • Authors: Kai Zhang; Xiaoming Zhang; Liming Zhang; Lixin Li; Hai Sun; Zhaoqin Huang; Jun Yao
      Abstract: Abstract Accurate prediction of fracture distribution in fractured reservoirs is important in the development process. Considering that assisted history matching technology is an effective method for the inversion of reservoir parameters, the technology can also be applied for the inversion of fractures. Because applying assisted history matching technology for the inversion of fractures has an inherent defect of multiplicity of solution, it is therefore necessary to alleviate the multiplicity for the success of inversion. Although there are many factors affecting the multiplicity, the paper focuses on the study of the inversion results of different combinations of inversion parameters which are all representative parameters of fractures and determine the distribution of fractures. Firstly, we simulate the flow behavior in fractured media based on the discrete fracture matrix (DFM) module of Matlab Reservoir Simulation Toolbox (MRST) to explicitly describe the effect of fractures on flow behavior. Secondly, history matching objective function is established based on Bayesian theory and different kinds of representative parameters of fractures are chosen as inversion parameters. Thirdly, simultaneous perturbation stochastic approximation (SPSA) algorithm is adopted to minimize the objective function to achieve the inversion of fractures corresponding to different inversion parameters. Finally, theoretical cases verify that the inversion method is effective for the accurate prediction of fracture distribution and proper inversion parameters are crucial to the success of fracture inversion.
      PubDate: 2017-08-26
      DOI: 10.1007/s10596-017-9690-8
  • Truncated conjugate gradient and improved LBFGS and TSVD for history
    • Authors: Flávio Dickstein; Paulo Goldfeld; Gustavo T. Pfeiffer; Renan V. Pinto
      Abstract: Abstract We propose a new algorithm for solving the history matching problem in reservoir simulation, truncated conjugate gradient (TCG), which involves a model reparameterization based on the factorization of the prior covariance matrix, C M = L L T . We also revisit the LBFGS algorithm, framing it into the same reparametrization, introducing M-LBFGS. We present numerical evidence that this reparameterization has an important regularizing impact on the solution process. We show how TCG and M-LBFGS, as well as TSVD, can be implemented without the need of actually computing the factor L. Our numerical experiments, including the PUNQ-S3 and the Brugge cases, indicate that TCG and M-LBFGS are effective schemes for history matching.
      PubDate: 2017-08-23
      DOI: 10.1007/s10596-017-9694-4
  • A model for non-Newtonian flow in porous media at different flow regimes
    • Authors: Arild Lohne; Oddbjørn Nødland; Arne Stavland; Aksel Hiorth
      Abstract: Abstract Polymeric liquids are of great practical importance for porous media flow as they can be used to improve the sweep of water in the reservoir and therefore improve the recovery of oil. Due to the non-Newtonian behavior of these liquids, they are extremely challenging to model. In this paper, we present a model that is capable of describing the most commonly observed flow regimes in porous media: (i) Newtonian, (ii) Shear thinning, (iii) Shear thickening, and (iv) Mechanical degradation. The novel feature of our model is that the time constants for the shear thinning and shear thickening behavior are related to variations in reservoir properties and conditions, thus making it possible to translate lab results to larger scale without introducing new fitting parameters. Furthermore, we present a way to estimate polymer mechanical degradation in porous media. In our model, the polymer degradation rate is linked to the effective pore radius (using a Kozeny-Carman type equation), shear stress, and polymer molecular weight, M w . The degradation results in a lower M w , while the polymer volumetric concentration is unaffected. The model is applied to a series of laboratory core flood experiments conducted with partially hydrolyzed polyacrylamide, HPAM, of different initial M w ranging from 5 to 20 MDa in seawater, and core permeability varied from 137 to 2019 mD. The flow rate is varied approximately three orders of magnitude and covers the shear thinning, shear thickening, and degradation flow regimes. We show that our model is able to reproduce experimental rate-dependent flow resistance, as well as viscosity of effluent samples. An important aspect supporting the use of the model as a predictive tool is that all the simulations with a given brine have made use of a single set of input parameters to describe the observed shear thickening and degradation behavior. Simulation of a second experimental series using low salinity brine required a separate set of input parameters for the shear thickening and shear degradation. The onset of shear thickening was not affected while shear thickening was reduced and degradation appeared to be slower.
      PubDate: 2017-08-18
      DOI: 10.1007/s10596-017-9692-6
  • Adaptive POD model reduction for solute transport in heterogeneous porous
    • Authors: Calogero B. Rizzo; Felipe P. J. de Barros; Simona Perotto; Luca Oldani; Alberto Guadagnini
      Abstract: Abstract We study the applicability of a model order reduction technique to the solution of transport of passive scalars in homogeneous and heterogeneous porous media. Transport dynamics are modeled through the advection-dispersion equation (ADE) and we employ Proper Orthogonal Decomposition (POD) as a strategy to reduce the computational burden associated with the numerical solution of the ADE. Our application of POD relies on solving the governing ADE for selected times, termed snapshots. The latter are then employed to achieve the desired model order reduction. We introduce a new technique, termed Snapshot Splitting Technique (SST), which allows enriching the dimension of the POD subspace and damping the temporal increase of the modeling error. Coupling SST with a modeling strategy based on alternating over diverse time scales the solution of the full numerical transport model to its reduced counterpart allows extending the benefit of POD over a prolonged temporal window so that the salient features of the process can be captured at a reduced computational cost. The selection of the time scales across which the solution of the full and reduced model are alternated is linked to the Péclet number (P e), representing the interplay between advective and dispersive processes taking place in the system. Thus, the method is adaptive in space and time across the heterogenous structure of the domain through the combined use of POD and SST and by way of alternating the solution of the full and reduced models. We find that the width of the time scale within which the POD-based reduced model solution provides accurate results tends to increase with decreasing P e. This suggests that the effects of local-scale dispersive processes facilitate the POD method to capture the salient features of the system dynamics embedded in the selected snapshots. Since the dimension of the reduced model is much lower than that of the full numerical model, the methodology we propose enables one to accurately simulate transport at a markedly reduced computational cost.
      PubDate: 2017-08-17
      DOI: 10.1007/s10596-017-9693-5
  • Convergence and error analysis of fully discrete iterative coupling
           schemes for coupling flow with geomechanics
    • Authors: T. Almani; K. Kumar; M. F. Wheeler
      Abstract: Abstract In this paper, we consider an iterative coupling scheme for solving a fully discretized Biot system based on the fixed-stress split coupling algorithm. Specifically, we derive a priori error estimates for quantifying the error between the solution obtained at any iterate and the true solution. Our approach is based on studying the equations satisfied by the difference of iterates and utilizing a Banach contraction argument to show that the corresponding scheme is a fixed point iteration. Obtained contraction results are then used to derive theoretical convergence error estimates for the single rate iterative coupling scheme. We compare our numerical computations against the theoretically derived contraction estimates and show a good agreement with theory.
      PubDate: 2017-08-16
      DOI: 10.1007/s10596-017-9691-7
  • An application of Green’s function technique for computing well inflow
           without radial flow assumption
    • Authors: A. V. Novikov; V. S. Posvyanskii; D. V. Posvyanskii
      Abstract: Abstract Well modeling plays an important role in numerical reservoir simulation. The main difficulty in well modeling is the difference in scale between the wellbore radius and well gridblock dimension used in the simulation. The Peaceman equation is widely used in reservoir simulation to match gridblock pressure to the local solution of the diffusivity equation describing the flow near the well. However, this approach was developed under the assumption of radial flow. At the same time, the well inflow equation can be solved within the Green’s function (GF) formalism which allows the solution to be obtained without the assumption of radial flow. The GF solution can be presented as a series over the eigenvalues of the Laplace differential operator. However, this series converges conditionally and its direct summation is time-consuming. In Posvyanskii et al. (2008), a method for fast summation of such a series was proposed and successfully applied for analyzing the pressure build up curves. In this paper, we adopt the same technique for calculating the well indices for horizontal, slanted and partially penetrated wells. Additionally, the role of different boundary conditions is considered. The semi-analytical expressions for well indices are obtained and compared to the solution of the Peaceman equation. It is shown that in some cases, the difference between these solutions can be significant. The use of the obtained expression in numerical flow simulation allows well inflow to be modeled with high accuracy even on a coarse grid.
      PubDate: 2017-08-10
      DOI: 10.1007/s10596-017-9684-6
  • An upscaling approach using adaptive multi-resolution upgridding and
           automated relative permeability adjustment
    • Authors: Niloofar Misaghian; Mehdi Assareh; MohammadTaqi Sadeghi
      Abstract: Abstract The upscaling process of a high-resolution geostatistical reservoir model to a dynamic simulation grid model plays an important role in a reservoir study. Several upscaling methods have been proposed in order to create balance between the result accuracy and computation speed. Usually, a high-resolution grid model is upscaled according to the heterogeneities assuming single phase flow. However, during injection processes, the relative permeability adjustment is required. The so-called pseudo-relative permeability curves are accepted, if their corresponding coarse model is a good representation of the fine-grid model. In this study, an upscaling method based on discrete wavelet transform (WT) is developed for single-phase upscaling based on the multi-resolution analysis (MRA) concepts. Afterwards, an automated optimization method is used in which evolutionary genetic algorithm is applied to estimate the pseudo-relative permeability curves described with B-spline formulation. In this regard, the formulation of B-spline is modified in order to describe the relative permeability curves. The proposed procedure is evaluated in the gas injection case study from the SPE 10th comparative solution project’s data set which provides a benchmark for upscaling problems [1]. The comparisons of the wavelet-based upscaled model to the high-resolution model and uniformly coarsened model show considerable speedup relative to the fine-grid model and better accuracy relative to the uniformly coarsened model. In addition, the run time of the wavelet-based coarsened model is comparable with the run time of the uniformly upscaled model. The optimized coarse models increase the speed of simulation up to 90% while presenting similar results as fine-grid models. Besides, using two different production/injection scenarios, the superiority of WT upscaling plus relative permeability adjustment over uniform upscaling and relative permeability adjustment is presented. This study demonstrates the proposed upscaling workflow as an effective tool for a reservoir simulation study to reduce the required computational time.
      PubDate: 2017-08-04
      DOI: 10.1007/s10596-017-9688-2
  • Erratum to: Parallel vertex approximate gradient discretization of hybrid
           dimensional Darcy flow and transport in discrete fracture networks
    • Authors: Feng Xing; Roland Masson; Simon Lopez
      PubDate: 2017-06-06
      DOI: 10.1007/s10596-017-9653-0
  • Seismic iterative migration velocity analysis: two strategies to update
           the velocity model
    • Authors: Emmanuel Cocher; Hervé Chauris; René-Édouard Plessix
      Abstract: Abstract The objective of seismic imaging is to recover properties of the Earth from surface measurements recorded during active seismic surveys. Migration Velocity Analysis techniques aim at determining a background velocity model (smooth part of the pressure wave velocity model) using the redundancy of seismic data and consist of solving a nested optimisation problem. In the inner loop, an extended reflectivity model (detailed part of the model) is determined from recorded primary reflections through a data-fitting procedure depending on a given background model. In the outer loop, a coherency criterion defined on the extended reflectivity assesses the quality of the background model. The inner problem is usually solved with a single iteration of gradient optimisation, leading to artefacts in the velocity updates. We study the benefits of further iterating on the reflectivity in the inner loop, which also allows the introduction of multiple reflections in the procedure. We propose two strategies for the computation of the gradient of the outer objective function. In the first case, we compute the exact numerical gradient by taking care of the background dependency of all inner iterations. In the second case, we derive an approximate gradient by assuming the optimal reflectivity has been obtained. Both methods are compared on their computational merits and through simple numerical examples on 2D synthetic data sets. The examples illustrate that regularisation of the inner problem is essential to obtain coherent velocity updates. The second approach displays a smaller sensitivity to regularisation and is simpler to implement.
      PubDate: 2017-06-03
      DOI: 10.1007/s10596-017-9656-x
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