Direct finite element method for nonlinear earthquake analysis of concrete dams: Simplification,modeling, and practical application

A direct finite element (FE) method for nonlinear response history analysis of semi-unbounded dam-water-foundation systems has recently been presented. The analysis procedure employs standard viscous-damper absorbing boundaries to model the semi-unbounded foundation and fluid domains and specifies the seismic input as effective earthquake forces—determined from a control motion defined at the foundation surface—at these boundaries. Presented in this paper are several simplifications to this direct FE method that greatly facilitates its implementation in commercial FE software. Also addressed is the modeling of the principal nonlinear mechanisms for concrete dams, calibration of damping in the numerical model to ensure consistency with values measured at actual dams, and practical procedures for implementation of the direct FE method with a commercial FE program.     

CO2 saturation estimates at Sleipner (North Sea) from seismic tomography and rock physics inversion

CO₂ saturations are estimated at Sleipner using a two-step imaging workflow. The workflow combines seismic tomography (full-waveform inversion) and rock physics inversion and is applied to a two-dimensional seismic line located near the injection point at Sleipner. We use baseline data (1994 vintage, before CO₂ injection) and monitor data that was acquired after 12 years of CO₂ injection (2008 vintage). P-wave velocity models are generated using the Full waveform inversion technology and then, we invert selected rock physics parameters using an rock physics inversion methodology. Full waveform inversion provides high-resolution P-wave velocity models both for baseline and monitor data. The physical relations between rock physics properties and acoustic wave velocities in the Utsira unconsolidated sandstone (reservoir formation) are defined using a dynamic rock physics model based on well-known Biot–Gassmann theories. For data prior to injection, rock frame properties (porosity, bulk and shear dry moduli) are estimated using rock physics inversion that allows deriving physically consistent properties with related uncertainty. We show that the uncertainty related to limited input data (only P-wave velocity) is not an issue because the mean values of parameters are correct. These rock frame properties are then used as a priori constraint in the monitor case. For monitor data, the Full waveform inversion results show nicely resolved thin layers of CO₂–brine saturated sandstones under intra-reservoir shale layers. The CO₂ saturation estimation is carried out by plugging an effective fluid phase in the rock physics model. Calculating the effective fluid bulk modulus of the brine–CO₂ mixture (using Brie equation in our study) is shown to be the key factor to link P-wave velocity to CO₂ saturation. The inversion tests are done with several values of Brie/patchiness exponent and show that the CO₂ saturation estimates are varying between 0.30 and 0.90 depending on the rock physics model and the location in the reservoir. The uncertainty in CO₂ saturation estimation is usually lower than 0.20. When the patchiness exponent is considered as unknown, the inversion is less constrained and we end up with values of exponent varying between 5 and 20 and up to 33 in specific reservoir areas. These estimations tend to show that the CO₂–brine mixing is between uniform and patchy mixing and variable throughout the reservoir.     

A least squares approach for efficient and reliable short-term versus long-term optimization

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.     

Successful application of multiscale methods in a real reservoir simulator environment

For the past 10 years or so, a number of so-called multiscale methods have been developed as an alternative approach to upscaling and to accelerate reservoir simulation. The key idea of all these methods is to construct a set of prolongation operators that map between unknowns associated with cells in a fine grid holding the petrophysical properties of the geological reservoir model and unknowns on a coarser grid used for dynamic simulation. The prolongation operators are computed numerically by solving localized flow problems, much in the same way as for flow-based upscaling methods, and can be used to construct a reduced coarse-scale system of flow equations that describe the macro-scale displacement driven by global forces. Unlike effective parameters, the multiscale basis functions have subscale resolution, which ensures that fine-scale heterogeneity is correctly accounted for in a systematic manner. Among all multiscale formulations discussed in the literature, the multiscale restriction-smoothed basis (MsRSB) method has proved to be particularly promising. This method has been implemented in a commercially available simulator and has three main advantages. First, the input grid and its coarse partition can have general polyhedral geometry and unstructured topology. Secondly, MsRSB is accurate and robust when used as an approximate solver and converges relatively fast when used as an iterative fine-scale solver. Finally, the method is formulated on top of a cell-centered, conservative, finite-volume method and is applicable to any flow model for which one can isolate a pressure equation. We discuss numerical challenges posed by contemporary geomodels and report a number of validation cases showing that the MsRSB method is an efficient, robust, and versatile method for simulating complex models of real reservoirs.     

Modeling core-scale permeability anisotropy in highly bioturbated “tight oil” reservoir rocks

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.     

Overview of groundwater sources and water-supply systems,and associated microbial pollution,in Finland,Norway and Iceland

The characteristics of groundwater systems and groundwater contamination in Finland, Norway and Iceland are presented, as they relate to outbreaks of disease. Disparities among the Nordic countries in the approach to providing safe drinking water from groundwater are discussed, and recommendations are given for the future. Groundwater recharge is typically high in autumn or winter months or after snowmelt in the coldest regions. Most inland aquifers are unconfined and therefore vulnerable to pollution, but they are often without much anthropogenic influence and the water quality is good. In coastal zones, previously emplaced marine sediments may confine and protect aquifers to some extent. However, the water quality in these aquifers is highly variable, as the coastal regions are also most influenced by agriculture, sea-water intrusion and urban settlements resulting in challenging conditions for water abstraction and supply. Groundwater is typically extracted from Quaternary deposits for small and medium municipalities, from bedrock for single households, and from surface water for the largest cities, except for Iceland, which relies almost entirely on groundwater for public supply. Managed aquifer recharge, with or without prior water treatment, is widely used in Finland to extend present groundwater resources. Especially at small utilities, groundwater is often supplied without treatment. Despite generally good water quality, microbial contamination has occurred, principally by norovirus and Campylobacter, with larger outbreaks resulting from sewage contamination, cross-connections into drinking water supplies, heavy rainfall events, and ingress of polluted surface water to groundwater.     

How Well Does Chlorophyll Explain the Seasonal Variation in Phytoplankton Activity?

The seasonal variation in phytoplankton activity is determined by analysing 1385 primary production (PP) profiles, chlorophyll a (Chl) concentration profiles and phytoplankton carbon biomass concentrations (C) from the period 1998–2012. The data was collected at six different stations in the Baltic Sea transition zone (BSTZ) which is a location with strong seasonal production patterns with light as the key parameter controlling this productivity. We show that the use of Chl as a proxy for phytoplankton activity strongly overestimates the contribution from the spring production to annual pelagic carbon flow. Spring (February and March) Chl comprised 16–30% of the total annual Chl produced, whereas spring C was much lower (8–23%) compared to the annual C. Spring PP accounted for 10–18% of the total annual PP, while the July–August production contributed 26–33%, i.e. within the time frame when zooplankton biomass and grazing pressure are highest. That is, Chl failed in this study to reflect the importance of the high summer PP. A better proxy for biomass may be C, which correlated well with the seasonal pattern of PP (Pearson correlation, p < 0.05). Thus, this study suggests to account for the strong seasonal pattern in C/Chl ratios when considering carbon flow in coastal systems. Seasonal data for PP were fitted to a simple sinusoidal wave model describing the seasonal distribution of PP in the BSTZ and were proposed to present a better parameterizaton of PP in shallow stratified temperate regions than more commonly applied proxies.     

Spatial constrained inverse rock physics modelling

Predicting reservoir parameters, such as porosity, lithology, and saturations, from geophysical parameters is a problem with non‐unique solutions. The variance in solutions can be extensive, especially for saturation and lithology. However, the reservoir parameters will typically vary smoothly within certain zones—in vertical and horizontal directions. In this work, we integrate spatial correlations in the predicted parameters to constrain the range of predicted solutions from a particular type of inverse rock physics modelling method. Our analysis is based on well‐log data from the Glitne field, where vertical correlations with depth are expected. It was found that the reservoir parameters with the shortest depth correlation (lithology and saturation) provided the strongest constraint to the set of solutions. In addition, due to the interdependence between the reservoir parameters, constraining the predictions by the spatial correlation of one parameter also reduced the number of predictions of the other two parameters. Moreover, the use of additional constraints such as measured log data at specific depth locations can further narrow the range of solutions.