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Quantifying and minimizing uncertainty is vital for simulating technically and economically successful geothermal reservoirs. To this end, we apply a stochastic modelling sequence, a Monte Carlo study, based on (i) creating an ensemble of possible realizations of a reservoir model, (ii) forward simulation of fluid flow and heat transport, and (iii) constraining post-processing using observed state variables. To generate the ensemble, we use the stochastic algorithm of Sequential Gaussian Simulation and test its potential fitting rock properties, such as thermal conductivity and permeability, of a synthetic reference model and—performing a corresponding forward simulation—state variables such as temperature. The ensemble yields probability distributions of rock properties and state variables at any location inside the reservoir. In addition, we perform a constraining post-processing in order to minimize the uncertainty of the obtained distributions by conditioning the ensemble to observed state variables, in this case temperature. This constraining post-processing works particularly well on systems dominated by fluid flow. The stochastic modelling sequence is applied to a large, steady-state 3-D heat flow model of a reservoir in The Hague, Netherlands. The spatial thermal conductivity distribution is simulated stochastically based on available logging data. Errors of bottom-hole temperatures provide thresholds for the constraining technique performed afterwards. This reduce the temperature uncertainty for the proposed target location significantly from 25 to 12 K (full distribution width) in a depth of 2300 m. Assuming a Gaussian shape of the temperature distribution, the standard deviation is 1.8 K. To allow a more comprehensive approach to quantify uncertainty, we also implement the stochastic simulation of boundary conditions and demonstrate this for the basal specific heat flow in the reservoir of The Hague. As expected, this results in a larger distribution width and hence, a larger, but more realistic uncertainty estimate. However, applying the constraining post-processing the uncertainty is again reduced to the level of the post-processing without stochastic boundary simulation. Thus, constraining post-processing is a suitable tool for reducing uncertainty estimates by observed state variables.
Objectives
Interest in cardiovascular magnetic resonance (CMR) at 7 T is motivated by the expected increase in spatial and temporal resolution, but the method is technically challenging. We examined the feasibility of cardiac chamber quantification at 7 T.
Methods
A stack of short axes covering the left ventricle was obtained in nine healthy male volunteers. At 1.5 T, steady-state free precession (SSFP) and fast gradient echo (FGRE) cine imaging with 7 mm slice thickness (STH) were used. At 7 T, FGRE with 7 mm and 4 mm STH were applied. End-diastolic volume, end-systolic volume, ejection fraction and mass were calculated.
Results
All 7 T examinations provided excellent blood/myocardium contrast for all slice directions. No significant difference was found regarding ejection fraction and cardiac volumes between SSFP at 1.5 T and FGRE at 7 T, while volumes obtained from FGRE at 1.5 T were underestimated. Cardiac mass derived from FGRE at 1.5 and 7 T was larger than obtained from SSFP at 1.5 T. Agreement of volumes and mass between SSFP at 1.5 T and FGRE improved for FGRE at 7 T when combined with an STH reduction to 4 mm.
Conclusions
This pilot study demonstrates that cardiac chamber quantification at 7 T using FGRE is feasible and agrees closely with SSFP at 1.5 T.
Bacterial lipopolysaccharides (endotoxins) show strong biological effects at very low concentrations in human beings and many animals when entering the blood stream. These include affecting structure and function of organs and cells, changing metabolic functions, raising body temperature, triggering the coagulation cascade, modifying hemodynamics and causing septic shock. Because of this toxicity, the removal of even minute amounts is essential for safe parenteral administration of drugs and also for septic shock patients' care. The absence of a general method for endotoxin removal from liquid interfaces urgently requires finding new methods and materials to overcome this gap. Nanostructured carbonized plant parts is a promising material that showed good adsorption properties due to its vast pore network and high surface area. The aim of this study was comparative measurement of endotoxin- and blood proteins-related adsorption rate and adsorption capacity for different carboneous materials produced at different temperatures and under different surface modifications. As a main surface modificator, positively cbarged polymer, polyethileneimine (PEl) was used. Activated carbon materials showed good adsorption properties for LPS and some proteins used in the experiments. During the batch experiments, several techniques (dust removal, autoclaving) were used and optimized for improving the material's adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics. Modification of the surface apparently has not affected hemoglobin binding to the adsorbent's surface. Obtained adsorption isotherms can be used as a powerful tool for designing of future column-based setups for blood purification from LPS, which is especially important for septic shock treatment.