Highlights• T2Well-EWASG, a coupled wellbore-reservoir numerical simulator for geothermal systems.• Interpretation of geothermal well-tests.• Application of T2Well-EWASG on a short well-test performed on a well of the Wotten Waven geothermal field (Dominica).
AbstractIn the geothermal sector, being able to simulate production tests by combining surface and downhole measurements can be extremely useful, improving data interpretation and reducing the impact of unavailable field data. This is possible with T2Well, a coupled wellbore-reservoir simulator. We plugged the EWASG equation of state for high enthalpy geothermal reservoirs into T2Well and extended the function to analytically compute the heat exchange between wellbore and formation at the short times. Changes to the analytical heat exchange function were verified by comparison with wellbore-formation heat exchange numerically simulated. T2Well-EWASG was validated by reproducing the flowing pressure and temperature logs taken from literature, and by using the software for the interpretation of a short production test. Simulation results indicate that T2Well-EWASG can be effectively used to improve the interpretation of production tests performed in geothermal wells.
Dissolution dynamic nuclear polarization allows in vivo studies of metabolic flux using 13 C-hyperpolarized tracers by enhancing signal intensity by up to four orders of magnitude. The T 1 for in vivo applications is typically in the range of 10-50 s for the different 13 C-enriched metabolic substrates; the exponential loss of polarization due to various relaxation mechanisms leads to a strong reduction of the signal-to-noise ratio (SNR). A common solution to the problem of low SNR is the accumulation/averaging of consecutive spectra. However, some limitations related to long delays between consecutive scans occur: in particular, following biochemical kinetics and estimate apparent enzymatic constants becomes time critical when measurement scans are repeated with the typical delay of about 3 T 1 . Here we propose a method to dramatically reduce the noise, and therefore also the acquisition times, by computing, via truncated singular value decomposition, a low-rank approximation to the individual complex time-domain signals. Moreover, this approach has the additional advantage that the phase correction can be applied to the spectra already denoised, thus greatly reducing phase correction errors. We have tested the method on (1) simulated data;(2) performing dissolution of hyperpolarized 1-13 C-pyruvate in standard conditions and (3) in vivo data sets, using a porcine model injected with hyperpolarized Na-1-13 C-acetate. It was shown that the presented method reduces the noise level in all the experimental data sets, allowing the retrieval of signals from highly noisy data without any prior phase correction pre-processing. The effects of the proposed approach on the quantification of metabolic kinetics parameters have to be shown by full quantification studies.
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