A mathematical model earlier proposed has been improved to predict the kinetics of multicomponent reactions in the hot metal pretreatment through the injection of reactive fluxes. It is assumed that there are two reaction zones along the flux injection operation: a transitory reaction between the rising particles and the bulk metal, and the permanent reaction between the metal and the top slag. A criterion to estimate the fraction of solids which will react with molten iron in a three‐phase jet (gas‐solid‐liquid) was considered; this fraction of solids carries out the transitory reaction. The model also takes into account the thermodynamic changes produced in the metal and slag due to the chemical reactions. Calculated results of the model are in good agreement with experimental results for the desulfurization of hot metal through the injection of CaO‐SiO2‐CaF2‐FeO‐Na2O reagents at 1400 ‐ 1450 °C. Two kinds of hot metal were tested, one with a low carbon mass content of 3 % and the other with a high carbon mass content of 4.5 %.
One of the great challenges facing our industry is accurate prediction of well inflow. Conventional methods have been too cumbersome and imprecise and have suffered from a lack of accuracy and clarity. Informed use of computational fluid dynamics, fine scale modelling and improved computing power enable far more accurate prediction of the impact of formation damage and thus of well performance. The accurate prediction of well performance helps with appraisal of development prospects, well planning and reliable prediction of true well and field value. If we know what the outcome of our actions and of our well designs will be, then we can make sensible and informed choices on damage impact and mitigation. Results from laboratory simulations of drilling and completion operations were generated from "standard" return permeability testing. The detailed data obtained, and its millimetre scale resolution was incorporated in to a well specific model. The damaged and undamaged states were examined using flow rate predictive computational fluid dynamics. The impact on flow in a single and dual permeability reservoir interval were calculated. In a specific example presented, the case for underbalance drilling was clearly made as the impact of overbalance drilling was predicted to have a severe impact on well productivity. The results of accurate and detailed laboratory simulation of formation damage have been translated using innovative software applications to give a prediction of well performance. This is the first time that computational fluid dynamics has been employed to predict well performance based on high quality laboratory testing. In future the laboratory tests will be designed to yield data most useful for the model and the model and grid scale will continue to be adjusted based on the specific challenge and objective. The detailed workflow used to achieve more accurate well performance prediction will be outlined in the paper. Introduction Modeling of permeability, pressure drops and formation damage in the near wellbore is an art that has suffered from lack of input and lack of tools in the past. The input deficit has largely been driven by poor or incomplete measurement and knowledge of formation damage mechanisms. These are not very often identified or quantified and some of the basic assumptions and rules of thumb for damage are simply incorrect. Even when properly understood and measured, existing industry software, inflow performance relationship models are inadequate tools to capture the detail and complexity of damage distribution. They generally accept only a very simple input of damage magnitude and thickness. Often data is altered in order to match the model. This is entirely the wrong way around. In building the workflows to model and understand damage, our guiding principal was that the model must alter to capture the damage rather than the other way around. Previous authors have attempted to model damage and create near wellbore inflow models which incorporate flow restrictions to a fine scale (Bennion et al 1996, Burton et al 1997, Han et al 2005, Yildiz 2004, Qutob and Ferreira 2005). These could be termed very near wellbore models of damage, most of which are numerical 2D models. Our objective here is to create a process through which complex very near and very, very near well inflow models can be created in 2D, 3D and 4D. The overriding objective is accurate prediction of well productivity and injectivity which will enable thorough well and completion designs and enable focus on real production barriers rather than speculation and heresay.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.