Robust optimisation of CO2 sequestration strategies under geological uncertainty using adaptive sparse grid surrogates     

Kurt R. Petvipusit  Ahmed H. Elsheikh  Tara C. Laforce  Peter R. King  Martin J. Blunt 《Computational Geosciences》2014,18(5):763-778

Geologic CO₂ sequestration in deep saline aquifers is a promising technique to mitigate the effect of greenhouse gas emissions. Designing optimal CO₂ injection strategy becomes a challenging problem in the presence of geological uncertainty. We propose a surrogate assisted optimisation technique for robust optimisation of CO₂ injection strategies. The surrogate is built using Adaptive Sparse Grid Interpolation (ASGI) to accelerate the optimisation of CO₂ injection rates. The surrogate model is adaptively built with different numbers of evaluation points (simulation runs) in different dimensions to allow automatic refinement in the dimension where added resolution is needed. This technique is referred to as dimensional adaptivity and provides a good balance between the accuracy of the surrogate model and the number of simulation runs to save computational costs. For a robust design, we propose a utility function which comprises the statistical moment of the objective function. Numerical testing of the proposed approach applied to benchmark functions and reservoir models shows the efficiency of the method for the robust optimisation of CO₂ injection strategies under geological uncertainty.  相似文献   

Using Discriminant Analysis and Logistic Regression in Mapping Quaternary Sediments     

Kurt Heil  Urs Schmidhalter 《Mathematical Geosciences》2014,46(3):361-376

Mapping the occurrence and thickness of layers within a soil profile is a prerequisite for soil characterization. The objective of this paper is to compare the applicability of two statistical methods—discriminant analysis (DA) and logistic regression (LR)—used to calculate the thickness of Quaternary sediments in a formal way and to identify parameters controlling the occurrence of these sediments. The investigations were carried out in southern Bavaria in an area of about 150 ha presenting a large variability in relief and parent material (Tertiary material, Pleistocene loess, colluvial/alluvial sediments). Comparisons between the two statistical methods were carried out with a training dataset and an evaluation dataset. The results show that DA was preferable under the assumptions of normality and equal variance/covariance matrices. The analyses produced models with 80 % and 79 % correctly reclassified assignments and a canonical correlation coefficient of approximately 0.60. From the simulations, it was found (i) that the determining predictors were altitude, slope, and upslope catchment area (partly expressed as topographical wetness index), SAGA wetness index and specific catchment area; and (ii) that a disadvantage of LR was that trial and error was frequently necessary to find the optimal composition of variables. In this study, a hierarchical combination of binary and ordinal LR was used and revealed (iii) that when the probabilities in LR between adjacent categories were similar, the possibility of incorrect calculations increased and (iv) that visual inspections as well as RMSE showed that DA with weighted depths (5 cm-stepwise DA) provided the best prediction accuracy. This information can help improve soil surveys and the predictability of the spatial heterogeneity in landscapes.  相似文献   

Gamma-Ray and High-Energy-Neutron Measurements on CORONAS-F during the Solar Flare of 28 October 2003     

Sergei N. Kuznetsov  Victoria G. Kurt  Boris Y. Yushkov  Karel Kudela  Vladimir I. Galkin 《Solar physics》2011,268(1):175-193

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Deciphering factors controlling trace element distribution in the soils of Karaduvar industrial-agricultural area (Mersin,SE Turkey)   总被引：1，自引：0，他引：1  

Cüneyt Güler  Musa Alpaslan  Mehmet Ali Kurt  Abidin Temel 《Environmental Earth Sciences》2010,60(1):203-218

In this study, 30 topsoil samples were collected from Karaduvar area (Mersin, SE Turkey) where at present various industrial and agricultural activities are occurring. Using a five-step ultrasound-assisted sequential extraction (UASE) procedure, trace elements in soil samples were partitioned into the following: (1) soluble-exchangeable; (2) bound to carbonates; (3) bound to Fe- and Mn-oxides; (4) bound to organic matter and sulfide compounds, and (5) residual fraction. Concentrations of 11 trace elements in the extracts were determined using ICP-MS. Total concentrations ranged between (in mg kg⁻¹) 3.35 and 7.26 for As; 1.18 and 3.96 for Cd; 10.76 and 20.26 for Co; 37.99 and 63.48 for Cr; 18.55 and 243.1 for Cu; 338.7 and 565.6 for Mn; 4.42 and 6.44 for Mo; 148 and 279.3 for Ni; 10.12 and 73.71 for Pb; 17.93 and 36.55 for V, and 25.46 and 331.7 for Zn. Factor analysis was applied to dataset in order to discriminate between natural and anthropogenic pollution sources and factors controlling the spatial distribution of trace elements in the area. Results suggest that distributions of Co, Cr, Mn, and Ni are mainly controlled by lithological factors, whereas, distributions of Cu, Pb, and Zn can be attributed to agricultural activities such as pesticide/herbicide use and fertilizer application, as well as irrigation with petroleum hydrocarbon-contaminated groundwater. Highest concentrations of Cd and Mo are generally observed around the diesel-fired thermal power plant and ATAŞ refinery. Highest concentrations of As and V are generally observed at the NW sector of the area; however, no definitive source can be designated for both of these elements.  相似文献