Institutional Repository of GuangZhou Institute of Energy Conversion, CAS
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Kinetic studies of the secondary hydrate formation in porous media based on experiments in a cubic hydrate simulator and a new kinetic model
No full textThe challenge of secondary hydrate formation (SHF) is frequently encountered in hydrate formation and dissociation experiments. However, there is currently a lack of modeling theory of SHF kinetics in the field and laboratory tests. In this work, the hydrate formation experiments concerning the SHF are carried out in a cubic hydrate simulator (CHS), where the pressure profiles and temperature spatial distributions are measured. A new kinetic model of hydrate formation integrating hydrate pore-scale morphology and SHF characteristics is developed. The newly developed model with unified kinetic parameters is employed in the Tough + hydrate (T + H) simulator to duplicate the experiment processes numerically, which achieves excellent agreement with the experimental data. The results show that the evolutions of the spatial distributions of the temperature and hydrate saturation behave in heterogeneous manners in the hydrate formation processes. This also reveals that the SHF can significantly exacerbate the hydrate heterogeneity in the CHS. Two additional experiments and comparisons with currently available models have validated the feasibility and accuracy of the new model. This work provides a reliable and adaptable model for describing the entire lifecycle of the hydrate formation kinetics in the porous media
An advanced inverse modeling framework for efficient and flexible adjoint-based history matching of geothermal fields
No full textIn this study, we present an efficient and flexible adjoint-based framework for history matching and forecasting geothermal energy extraction at a large scale. In this framework, we applied the Principal Component Analysis to reduce the parameter space for representing the complex geological model. The adjoint method is implemented for gradient calculation to speed up the history-matching iteration process. Operator-based linearization (OBL) used in this framework makes the calculation of the physical state and its derivatives very efficient and facilitates the matrix assembly in the adjoint method. This study primarily focuses on history matching based on combined observation of well production and in-situ electromagnetic measurements to predict the temperature front. However, different types of misfit terms can be added to the objective function based on practical considerations. For example, our history-matching case studies include model misfit terms applied for regularization purposes. The measurement data is extracted from the true model, and realistic measurement errors are considered. Also, in this work, we propose an optimal weighting strategy for the terms of the objective function to balance their sensitivity with respect to the model control variables. The high efficiency of the framework is demonstrated for the geothermal doublet model implemented at the heterogeneous reservoir with multiple realizations. The framework allows for generating posterior Randomized Maximum Likelihood (RML) estimates of the entire ensemble of the realizations with a reasonable computational cost. Results show that the framework can achieve reliable history-matching results based on the doublets production data and the reservoir electromagnetic measurement
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