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ENGINEERING (1199 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 19)
AAPG Bulletin     Full-text available via subscription   (Followers: 5)
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: 217)
Acta Geotechnica     Hybrid Journal   (Followers: 6)
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: 10)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 5)
Advanced Science     Open Access   (Followers: 4)
Advanced Science Focus     Free   (Followers: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 5)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
Advances in Artificial Neural Systems     Open Access   (Followers: 4)
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: 14)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 9)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 19)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
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: 40)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 35)
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: 28)
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: 27)
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: 8)
Applied Clay Science     Hybrid Journal   (Followers: 4)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 3)
Applied Nanoscience     Open Access   (Followers: 7)
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: 2)
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: 7)
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: 7)
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: 3)
Batteries     Open Access   (Followers: 3)
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: 3)
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: 9)
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: 16)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 31)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 8)
Biomedical Science and Engineering     Open Access   (Followers: 3)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 1)
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     Full-text available via subscription   (Followers: 13)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 40)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 7)
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: 5)
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: 9)
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: 4)
Coatings     Open Access   (Followers: 2)
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: 23)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 252)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 177)
Composites Part B : Engineering     Hybrid Journal   (Followers: 223)
Composites Science and Technology     Hybrid Journal   (Followers: 165)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 12)
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: 25)
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: 8)
Computing and Visualization in Science     Hybrid Journal   (Followers: 6)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 25)
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: 8)
Control Engineering Practice     Hybrid Journal   (Followers: 41)
Control Theory and Informatics     Open Access   (Followers: 7)
Corrosion Science     Hybrid Journal   (Followers: 24)
CT&F Ciencia, Tecnologia y Futuro     Open Access  
CTheory     Open Access  

        1 2 3 4 5 6 | Last

Journal Cover Computational Geosciences
  [SJR: 1.477]   [H-I: 43]   [12 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  [2329 journals]
  • Evaluation concepts to compare observed and simulated deposition areas of
           mass movements
    • Authors: M. Heiser; C. Scheidl; R. Kaitna
      Pages: 335 - 343
      Abstract: Abstract The simulation of geophysical mass flows, including debris flows, rock and snow avalanches, has become an important tool in engineering hazard assessment. Especially the runout and deposition behaviour of observed and expected mass flows are of interest. When being confronted with the evaluation of model performance and sensitivity, there are no standard, objective approaches. In this contribution, we review methods that have been used in literature and outline a new approach to quantitatively compare 2D simulations of observed and simulated deposition pattern. Our proposed method is based on the comparison of normalized partial areas which can be plotted in a ternary diagram to visualize the degree of over- and under-estimation. Results can be summed up by a single metric between -1 (no fit) and 1 (perfect fit). This study shall help developers and end-users of simulation models to better understand model behaviour and provides a possibility for comparison of model results, independent of simulation platform and type of mass flow.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-016-9609-9
      Issue No: Vol. 21, No. 3 (2017)
  • A multi-domain decomposition-based Fourier finite element method for the
           simulation of 3D marine CSEM measurements
    • Authors: Shaaban A. Bakr; David Pardo
      Pages: 345 - 357
      Abstract: Abstract We introduce a multi-domain decomposition Fourier finite element (MDDFFE) method for the simulation of three-dimensional (3D) marine controlled source electromagnetic measurement (CSEM). The method combines a 2D finite element (FE) method in two spatial dimensions with a hybrid discretization based on a Fourier FE method along the third dimension. The method employs a secondary field formulation rather than the total field formulation. We apply the MDDFFE method to several synthetic marine CSEM examples exhibiting bathymetry and/or multiple 3D subdomains. Numerical results show that the use of the MDDFFE method reduces the problem size by as much as 87 % in terms of the number of unknowns, without any sacrifice in accuracy.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9615-6
      Issue No: Vol. 21, No. 3 (2017)
  • Nearly perfectly matched layer boundary conditions for operator upscaling
           of the acoustic wave equation
    • Authors: Chen Lai; Susan E. Minkoff
      Pages: 359 - 372
      Abstract: Abstract Acoustic imaging and sensor modeling are processes that require repeated solution of the acoustic wave equation. Solution of the wave equation can be computationally expensive and memory intensive for large simulation domains. One scheme for speeding up solution of the wave equation is the operator-based upscaling method. The algorithm proceeds in two steps. First, the wave equation is solved for fine grid unknowns internal to coarse blocks assuming the coarse blocks do not need to communicate with neighboring blocks in parallel. Second, these fine grid solutions are used to form a new problem which is solved on the coarse grid. Accurate and efficient wave propagation schemes also must avoid artificial reflections off of the computational domain edges. One popular method for preventing artificial reflections is the nearly perfectly matched layer (NPML) method. In this paper, we discuss applying NPML to operator upscaling for the wave equation. We show that although we only apply NPML to the first step of this two step algorithm (directly affecting the fine grid unknowns only), we still see a significant reduction of reflections back into the domain. We describe three numerical experiments (one homogeneous medium experiment and two heterogeneous media examples) in which we validate that the solution of the wave equation exponentially decays in the NPML regions. Numerical experiments of acoustic wave propagation in two dimensions with a reasonable absorbing layer thickness resulted in a maximum pressure reflection of 3–8%. While the coarse grid acceleration is not explicitly damped in our algorithm, the tight coupling between the two steps of the algorithm results in only 0.1–1% of acceleration reflecting back into the computational domain.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9616-5
      Issue No: Vol. 21, No. 3 (2017)
  • Process-based forward numerical ecological modeling for carbonate
           sedimentary basins
    • Authors: Roger Clavera-Gispert; Òscar Gratacós; Ana Carmona; Raimon Tolosana-Delgado
      Pages: 373 - 391
      Abstract: Abstract Nowadays, numerical modeling is a common tool used in the study of sedimentary basins, since it allows to quantify the processes simulated and to determine interactions among them. One of such programs is SIMSAFADIM-CLASTIC, a 3D forward-model process-based code to simulate the sedimentation in a marine basin at a geological time scale. It models the fluid flow, siliciclastic transport and sedimentation, and carbonate production. In this article, we present the last improvements in the carbonate production model, in particular about the usage of Generalized Lotka-Volterra equations that include logistic growth and interaction among species. Logistic growth is constrained by environmental parameters such as water depth, energy of the medium, and depositional profile. The environmental parameters are converted to factors and combined into one single environmental value to model the evolution of species. The interaction among species is quantified using the community matrix that captures the beneficial or detrimental effects of the presence of each species on the other. A theoretical example of a carbonate ramp is computed to show the interaction among carbonate and siliciclastic sediment, the effect of environmental parameters to the modeled species associations, and the interaction among these species associations. The distribution of the modeled species associations in the theoretical example presented is compared with the carbonate Oligocene-Miocene Asmari Formation in Iran and the Miocene Ragusa Platform in Italy.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9617-4
      Issue No: Vol. 21, No. 3 (2017)
  • Downscaling the 2D Bénard convection equations using continuous data
    • Authors: M. U. Altaf; E. S. Titi; T. Gebrael; O. M. Knio; L. Zhao; M. F. McCabe; I. Hoteit
      Pages: 393 - 410
      Abstract: Abstract We consider a recently introduced continuous data assimilation (CDA) approach for downscaling a coarse resolution configuration of the 2D Bénard convection equations into a finer grid. In this CDA, a nudging term, estimated as the misfit between some interpolants of the assimilated coarse-grid measurements and the fine-grid model solution, is added to the model equations to constrain the model. The main contribution of this study is a performance analysis of CDA for downscaling measurements of temperature and velocity. These measurements are assimilated either separately or simultaneously, and the results are compared against those resulting from the standard point-to-point nudging approach (NA). Our numerical results suggest that the CDA solution outperforms that of NA, always converging to the true solution when the velocity is assimilated as has been theoretically proven. Assimilation of temperature measurements only may not always recover the true state as demonstrated in the case study. Various runs are conducted to evaluate the sensitivity of CDA to noise in the measurements, the size, and the time frequency of the measured grid, suggesting a more robust behavior of CDA compared to that of NA.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9619-2
      Issue No: Vol. 21, No. 3 (2017)
  • A least squares approach for efficient and reliable short-term versus
           long-term optimization
    • Authors: Lasse Hjuler Christiansen; Andrea Capolei; John Bagterp Jørgensen
      Pages: 411 - 426
      Abstract: Abstract The uncertainties related to long-term forecasts of oil prices impose significant financial risk on ventures of oil production. To minimize risk, oil companies are inclined to maximize profit over short-term horizons ranging from months to a few years. In contrast, conventional production optimization maximizes long-term profits over horizons that span more than a decade. To address this challenge, the oil literature has introduced short-term versus long-term optimization. Ideally, this problem is solved by a posteriori multi-objective optimization methods that generate an approximation to the Pareto front of optimal short-term and long-term trade-offs. However, such methods rely on a large number of reservoir simulations and scale poorly with the number of objectives subject to optimization. Consequently, the large-scale nature of production optimization severely limits applications to real-life scenarios. More practical alternatives include ad hoc hierarchical switching schemes. As a drawback, such methods lack robustness due to unclear convergence properties and do not naturally generalize to cases of more than two objectives. Also, as this paper shows, the hierarchical formulation may skew the balance between the objectives, leaving an unfulfilled potential to increase profits. To promote efficient and reliable short-term versus long-term optimization, this paper introduces a natural way to characterize desirable Pareto points and proposes a novel least squares (LS) method. Unlike hierarchical approaches, the method is guaranteed to converge to a Pareto optimal point. Also, the LS method is designed to properly balance multiple objectives, independently of Pareto front’s shape. As such, the method poses a practical alternative to a posteriori methods in situations where the frontier is intractable to generate.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9620-9
      Issue No: Vol. 21, No. 3 (2017)
  • Smart Interpretation – automatic geological interpretations based on
           supervised statistical models
    • Authors: Mats Lundh Gulbrandsen; Knud Skou Cordua; Torben Bach; Thomas Mejer Hansen
      Pages: 427 - 440
      Abstract: Abstract A method that infers a statistical model, which describes a relation between the knowledge of a geologist (quantified by geological interpretations) and the available information (such as geophysical data, well log data, etc.) that a geologist uses when he/she interprets is proposed and tested. The statistical model is then used to perform automatic geological interpretations wherever the same kinds of information, as used for the initial interpretations, are available. This methodology is named Smart Interpretation (SI). In this study, we look at two different approaches to infer such a model, and we demonstrate the applicability of the model to predict the depth to a low resistivity subsurface layer, based on interpretations from a geological expert, using a 19-layered resistivity model obtained from inversion of airborne electromagnetic (AEM) data. This study shows that SI is capable of making predictions with great accuracy. The method is fast and is able to handle large amounts of data of different origin, which suggest that the method may become a very useful approach to assist in geological modeling based on increasingly large amounts of data of different nature.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9621-8
      Issue No: Vol. 21, No. 3 (2017)
  • A multiresolution ensemble Kalman filter using the wavelet decomposition
    • Authors: Kyle S. Hickmann; Humberto C. Godinez
      Pages: 441 - 458
      Abstract: Abstract We present a method of using classical wavelet-based multiresolution analysis to separate scales in model and observations during data assimilation with the ensemble Kalman filter. In many applications, the underlying physics of a phenomena involve the interaction of features at multiple scales. Blending of observational and model error across scales can result in large forecast inaccuracies since large errors at one scale are interpreted as inexact data at all scales due to the misrepresentation of observational error. Our method uses a partitioning of the range of the observation operator into separate observation scales. This naturally induces a transformation of the observation covariance and we put forward several algorithms to efficiently compute the transformed covariance. Another advantage of our multiresolution ensemble Kalman filter is that scales can be weighted independently to adjust each scale’s affect on the forecast. To demonstrate feasibility, we present applications to a one-dimensional Kuramoto-Sivashinsky (K–S) model with scale-dependent observation noise and an application involving the forecasting of solar photospheric flux. The solar flux application uses the Air Force Data Assimilative Photospheric Transport (ADAPT) model which has model and observation error exhibiting strong scale dependence. Results using our multiresolution ensemble Kalman filter show significant improvement in solar forecast error compared to traditional ensemble Kalman filtering.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9622-7
      Issue No: Vol. 21, No. 3 (2017)
  • Robustness of statistical algorithms for location of microseismic sources
           based on surface array data
    • Authors: A. Kushnir; A. Varypaev
      Pages: 459 - 477
      Abstract: Abstract Here, we present a statistical simulation study of several array data processing techniques used for the location of sources of elastic waves. The source location problem arises in such engineering applications as radio-communications, acoustics, sonar, meteorology, astrophysics, seismology, etcetera. Recently, this problem has become important for applied geophysics in connection with the modern technology of hydrocarbon production based on the hydraulic fracturing of the surface layers of the Earth’s environment. These techniques are required for the monitoring of hydraulic fracturing through the location of sources of numerous microearthquakes that occur during cracking of crustal rocks. We have established theoretical connections among several location algorithms. In particular, two different theoretical interpretations were proposed for the phase alignment location algorithm, recently proposed for the seismic array data processing. The robustness properties of the phase alignment location algorithm and the adaptive maximum likelihood location algorithm were demonstrated through Monte Carlo simulation in regard to variations of those noise statistical features, which are typical under monitoring of microseismicity at the hydrocarbon production sites. In the framework of the Monte Carlo modeling, we also compared the two mentioned location algorithms with the so-called emission tomography algorithm that is developed for the location of microseismic sources during the monitoring of hydraulic fracturing.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9623-6
      Issue No: Vol. 21, No. 3 (2017)
  • Multiple shooting applied to robust reservoir control optimization
           including output constraints on coherent risk measures
    • Authors: Andrés Codas; Kristian G. Hanssen; Bjarne Foss; Andrea Capolei; John Bagterp Jørgensen
      Pages: 479 - 497
      Abstract: Abstract The production life of oil reservoirs starts under significant uncertainty regarding the actual economical return of the recovery process due to the lack of oil field data. Consequently, investors and operators make management decisions based on a limited and uncertain description of the reservoir. In this work, we propose a new formulation for robust optimization of reservoir well controls. It is inspired by the multiple shooting (MS) method which permits a broad range of parallelization opportunities and output constraint handling. This formulation exploits coherent risk measures, a concept traditionally used in finance, to bound the risk on constraint violation. We propose a reduced sequential quadratic programming (rSQP) algorithm to solve the underlying optimization problem. This algorithm exploits the structure of the coherent risk measures, thus a large set of constraints are solved within sub-problems. Moreover, a variable elimination procedure allows solving the optimization problem in a reduced space and an iterative active-set method helps to handle a large set of inequality constraints. Finally, we demonstrate the application of constraints to bound the risk of water production peaks rather than worst-case satisfaction.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9625-4
      Issue No: Vol. 21, No. 3 (2017)
  • A new method for the construction and optimization of quadrangular
           adaptive well pattern
    • Authors: Kai Zhang; Hao Zhang; Liming Zhang; Ping Li; Xiaoming Zhang; Jun Yao
      Pages: 499 - 518
      Abstract: Abstract A proper well pattern will have considerable effects on the oil field production, with the ultimate recovery of hydrocarbon enhanced and the water production rate reduced. Comparing with triangular well pattern, quadrangular well pattern has more advantages in some cases and has broader application prospects. However, constructing an optimal quadrangular well pattern is more complicated and has not gain enough research. Facing this situation, a new method of constructing quadrangular adaptive well pattern is proposed in this paper. This quadrangular adaptive well pattern is generated using frontal Delaunay quad-mesh generation method. Boundaries, faults, and existing wells can be constrained and treated as control variables to determine the well spacing, a gradient-based algorithm coupled with reservoir numerical simulator is used to optimize the well pattern. Comparing to conventional regular well pattern, the new well pattern will adjust its shape according to the heterogeneity in different parts of the reservoir, achieving the optimal effect using fewest wells. Two different examples are applied to demonstrate the proposed methodology. The results show that the method proposed can be successfully applied to the construction and optimization of well pattern for large-scale reservoirs and improve the ultimate recovery significantly.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9626-3
      Issue No: Vol. 21, No. 3 (2017)
  • Sketching the temperature history of geological samples: analyses of
           diffusion profiles using multilayer perceptrons
    • Authors: Laura Donatella Campisi
      Pages: 519 - 531
      Abstract: Abstract A method using multilayer perceptrons for analysing diffusion profiles and sketching the temperature history of geological samples is explored. Users of this method can intuitively test and compare results thinking in terms of analytical solutions of the diffusion equation whilst the bulk of the work is made computationally. Being neither completely analytical nor numerical, the method is a hybrid and represents an ideal man-machine interaction. The approach presented in this paper should be preferred when the retrieval of the diffusion coefficients from concentration profiles using dimensionless parameters is not possible and/or there is more than one unknown parameter in the analytical solution of the diffusion equation. Its versatility is a key factor for extending the potential of Dodson’s formulation. The case of a species produced by a radiogenic source and diffusing in a cooling system is therefore discussed. Both the classical change of variable for diffusion coefficients depending on time and an alternative approach decomposing the overall effect of diffusion into a sum of effects due to smaller events could be used to tackle this problem. As multilayer perceptrons can approximate any function, none of the assumptions originally stated by Dodson are necessary.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9628-1
      Issue No: Vol. 21, No. 3 (2017)
  • Bayesian model selection for complex geological structures using
           polynomial chaos proxy
    • Authors: Hamid Bazargan; Mike Christie
      Pages: 533 - 551
      Abstract: Abstract Different interpretation of sedimentary environments lead to “scenario uncertainty” where the prior reservoir model has a high level of discrete uncertainty. In a real field application, the scenario uncertainty has a considerable effect on flow response uncertainty and makes the uncertainty quantification problem highly nonlinear. We use clustering methods to address the scenario uncertainty. Our approach to cluster analysis is based on the posterior probabilities of models, known as “Bayesian model selection.” Accordingly, we integrate overall possible parameters in each scenario with respect to their corresponding priors to give the measure of how well a model is supported by observations. We propose a cluster-based reduced terms polynomial chaos proxy to efficiently estimate the posterior probability density function under each cluster and calculate the posterior probability of each model. We demonstrate that the convergence rate of the reduced terms polynomial chaos proxy is significantly improved under each cluster comparing to the non-clustered case. We apply the proposed cluster-based polynomial chaos proxy framework to study the plausibility of three training images based on different geological interpretation of the second layer of synthetic Stanford VI reservoir. We demonstrate that the proposed workflow can be efficiently used to calculate the posterior probability of each scenario and also sample from the posterior facies models within each scenario.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9629-0
      Issue No: Vol. 21, No. 3 (2017)
  • History matching of dual continuum reservoirs—preserving consistency
           with the fracture model
    • Authors: Pål Næverlid Sævik; Martha Lien; Inga Berre
      Pages: 553 - 565
      Abstract: Abstract Ensemble- and optimization-based parameter estimation is commonly used to calibrate simulation models of fractured reservoirs to measured data. Traditionally, statistical data on small-scale fractures are upscaled to a dual continuum model in a single step, and the subsequent history matching procedure makes adjustments to the upscaled parameters. In this paper, we show that the resulting reservoir models may be inconsistent with the initial fracture description, meaning that the reservoir parameters do not correspond to a physically valid combination of fracture parameters. A number of numerical examples is provided, which illustrate why and when the problem occurs. We utilize an invertible analytical fracture upscaling method, and deviations from the fracture model can thus be quantified in each case. We show that consistency with the fracture model is preserved if fracture parameters are history matched directly, if the relation between inversion variables and fracture parameters is linear, or if an unbiased Bayesian sampling method is used. We also show that preserving consistency is less important if the uncertainty of the fracture upscaling method is large.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9632-5
      Issue No: Vol. 21, No. 3 (2017)
  • Modeling core-scale permeability anisotropy in highly bioturbated “tight
           oil” reservoir rocks
    • Authors: Nisael A. Solano; Mohammad Soroush; Chris R. Clarkson; Federico F. Krause; Jerry L. Jensen
      Pages: 567 - 593
      Abstract: Abstract A high-resolution simulation model of a heterogeneous low-permeability rock sample is used to investigate the effects of physical and biogenic sedimentary structures on scaling and anisotropy of absolute permeability at the core scale. Several simulation sub-samples with random locations and volumes were also selected for evaluation of the effects of scale and lithological composition on the calculated permeability. Vertical and horizontal permeability values (from whole core simulation) are in good agreement with routine core analysis (RCA) measurements from offsetting cores. Despite relatively good reservoir quality associated with geobodies of biogenic and relic bedding structures, results from the full diameter core simulation demonstrate that their limited volumetric abundance and restricted connectivity prevent these features from controlling fluid flow in these rocks. In fact, permeability seems to be dominated by the tighter encasing matrix, which exhibits average permeability values very close to those reported from RCA. Geometric averaging offers a better representation for the upscaling of horizontal permeability datasets; whereas, both geometric and harmonic averaging work similarly well for the vertical measurements. The methodology used in this work is particularly applicable to the detailed characterization of reservoir rocks with a high degree of heterogeneity caused by biological reworking and diagenesis.
      PubDate: 2017-06-01
      DOI: 10.1007/s10596-017-9635-2
      Issue No: Vol. 21, No. 3 (2017)
  • Modeling wetting-phase relative permeability hysteresis based on subphase
    • Authors: Karim Khayrat; Patrick Jenny
      Abstract: Abstract A recently introduced subphase framework for modeling the nonwetting phase relative permeability is extended to the wetting phase. Within this framework, the wetting phase is divided into four subphases, which are distinguished by their connectivity; backbone, dendritic, isolated and corner-film subphases. The subphase saturations evolve according to inter-subphase volume transfer terms, which require modeling. An advantage of distinguishing the subphases is that wetting phase relative permeability relations as functions of these constituent subphases can be developed. In order to develop models for the inter-subphase volume transfer and the wetting phase relative permeability in a strongly wetted system, quasi-static flow simulations in pore networks were conducted to analyze the evolution of the wetting subphases during drainage and imbibition. The simulation results suggest that hysteresis trends apparent in experimentally obtained wetting phase relative permeability curves for Berea sandstone may be explained by accounting for corner-film flow.
      PubDate: 2017-05-24
      DOI: 10.1007/s10596-017-9655-y
  • Intrusive uncertainty quantification for hyperbolic-elliptic systems
           governing two-phase flow in heterogeneous porous media
    • Authors: M. Köppel; I. Kröker; C. Rohde
      Abstract: Abstract We model random locations of spatial interfaces of heterogeneities in porous media by means of the hybrid stochastic Galerkin (HSG) approach. This approach extends the concept of the generalized polynomial chaos (PC) expansion for a multi-element decomposition of the multidimensional stochastic space. In this way, the physically two-dimensional hyperbolic-elliptic fractional flow formulation for two-phase flow in heterogeneous porous media is transformed from a random partial differential equation into a deterministic system for the coefficients of the PC expansion of the primary unknown saturation, total velocity, and global pressure. The hyperbolic part is discretized based on a central-upwind finite volume scheme along with a mixed finite element method for the elliptic part. The latter partly uses the tensor product structure of the saddle point system together with appropriate preconditioning to speed up the computations. Since we use the sequential implicit pressure explicit saturation (IMPES) approach, the elliptic part is solved in every time step. The proposed method is particularly well-suited for parallel computations and allows for the consideration of a huge variety of complex flow problems. We illustrate the power of the method by means of several striking numerical examples of different complexities including their numerical convergence analysis.
      PubDate: 2017-05-23
      DOI: 10.1007/s10596-017-9662-z
  • Comparison of linear reconstructions for second-order finite volume
           schemes on polyhedral grids
    • Authors: Robert Klöfkorn; Anna Kvashchuk; Martin Nolte
      Abstract: Abstract Improved and enhanced oil recovery methods require sophisticated simulation tools to predict the injected flow pass together with the chemical reactions inside it. One approach is application of higher-order numerical schemes to avoid excessive numerical diffusion that is very typical for transport processes. In this work, we provide a first step towards higher-order schemes applicable on general polyhedral and corner-point grids typically used in reservoir simulation. We compare three possible approaches of linear reconstruction and slope limiting techniques on a variety of different meshes in two and three spatial dimensions and discuss advantages and disadvantages.
      PubDate: 2017-05-20
      DOI: 10.1007/s10596-017-9658-8
  • Compositional dual mesh method for single phase flow in heterogeneous
           porous media—application to CO 2 storage
    • Authors: Dominique Guérillot; Jérémie Bruyelle
      Abstract: Abstract Numerical simulation of fluid flow coupled with chemical reactions has been an active field in the hydrogeology community and many formulations have been programmed into different software. In recent years, this subject has attracted increasing interest in the reservoir simulation community, partly for the application of chemical methods for hydrocarbon extraction but also for research on the geological sequestration of CO2. In this paper, an extension to the concept of dual mesh for reactive transport modeling is presented. This approach involves two meshes, a low-resolution mesh to resolve the pressure equation and a high-resolution mesh to transport the species and to calculate the geochemical equilibrium. The main objective is to preserve the fine scale heterogeneities to reach a more accurate field behavior simulation than conventional approach which consist in performing simulations on a coarser mesh. The method is applied to a simulation of CO2 storage in the SPE10 model that keep a high resolution of the heterogeneities.
      PubDate: 2017-05-19
      DOI: 10.1007/s10596-017-9645-0
  • Data assimilation method for fractured reservoirs using mimetic finite
           differences and ensemble Kalman filter
    • Authors: Jing Ping; Omar Al-Hinai; Mary F. Wheeler
      Abstract: Abstract Optimal management of subsurface processes requires the characterization of the uncertainty in reservoir description and reservoir performance prediction. For fractured reservoirs, the location and orientation of fractures are crucial for predicting production characteristics. With the help of accurate and comprehensive knowledge of fracture distributions, early water/CO 2 breakthrough can be prevented and sweep efficiency can be improved. However, since the rock property fields are highly non-Gaussian in this case, it is a challenge to estimate fracture distributions by conventional history matching approaches. In this work, a method that combines vector-based level-set parameterization technique and ensemble Kalman filter (EnKF) for estimating fracture distributions is presented. Performing the necessary forward modeling is particularly challenging. In addition to the large number of forward models needed, each model is used for sampling of randomly located fractures. Conventional mesh generation for such systems would be time consuming if possible at all. For these reasons, we rely on a novel polyhedral mesh method using the mimetic finite difference (MFD) method. A discrete fracture model is adopted that maintains the full geometry of the fracture network. By using a cut-cell paradigm, a computational mesh for the matrix can be generated quickly and reliably. In this research, we apply this workflow on 2D two-phase fractured reservoirs. The combination of MFD approach, level-set parameterization, and EnKF provides an effective solution to address the challenges in the history matching problem of highly non-Gaussian fractured reservoirs.
      PubDate: 2017-05-19
      DOI: 10.1007/s10596-017-9659-7
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