TOUGH+CO2: A multiphase fluid-flow simulator for CO2 geologic sequestration in saline aquifers

TOUGH+CO₂ is a new simulator for modeling of CO₂ geologic sequestration in saline aquifers. It is a member of TOUGH+, the successor to the TOUGH2 family of codes for multicomponent, multiphase fluid and heat flow simulation. The code accounts for heat and up to 3 mass components, which are partitioned into three possible phases. In the code, the thermodynamics and thermophysical properties of H₂O-NaCl-CO₂ mixtures are determined based on system status and subdivided into six different phase combinations. By solving coupled mass and heat balance equations, TOUGH+CO₂ can model non-isothermal or isothermal CO₂ injection, phase behavior and flow of fluids and heat under typical conditions of temperature, pressure and salinity in CO₂ geologic storage projects. The code takes into account effects of salt precipitation on porosity and permeability changes, and the wettability phenomena. The new simulator inherits all capabilities of TOUGH2 in handling fractured media and using unstructured meshes for complex simulation domains. The code adds additional relative permeability and capillary pressure functions. The FORTRAN 95 OOP architecture and other new language features have been extensively used to enhance memory use and computing efficiency. In addition, a domain decomposition approach has been implemented for parallel simulation. All these features lead to increased computational efficiency, and allow applicability of the code to multi-core/processor parallel computing platforms with excellent scalability.     

TOUGHREACT Version 2.0: A simulator for subsurface reactive transport under non-isothermal multiphase flow conditions

TOUGHREACT is a numerical simulation program for chemically reactive non-isothermal flows of multiphase fluids in porous and fractured media, and was developed by introducing reactive chemistry into the multiphase fluid and heat flow simulator TOUGH2 V2. The first version of TOUGHREACT was released to the public through the U.S. Department of Energy's Energy Science and Technology Software Center (ESTSC) in August 2004. It is among the most frequently requested of ESTSC's codes. The code has been widely used for studies in CO₂ geological sequestration, nuclear waste isolation, geothermal energy development, environmental remediation, and increasingly for petroleum applications. Over the past several years, many new capabilities have been developed, which were incorporated into Version 2 of TOUGHREACT. Major additions and improvements in Version 2 are discussed here, and two application examples are presented: (1) long-term fate of injected CO₂ in a storage reservoir and (2) biogeochemical cycling of metals in mining-impacted lake sediments.     

Generating candidate networks for optimization: The CO2 capture and storage optimization problem

We develop a new framework for spatially optimizing infrastructure for CO₂ capture and storage (CCS). CCS is a complex and challenging problem: domestically deploying CCS at a meaningful scale will require linking hundreds of coal-fired power plants with CO₂ sequestration reservoirs through a dedicated and extensive (many tens-of-thousands of miles) CO₂ pipeline network. We introduce a unique method for generating a candidate network from scratch, from which the optimization model selects the optimal set of arcs to form the pipeline network. This new generation method can be applied to any network optimization problem including transmission line, roads, and telecommunication applications. We demonstrate the model and candidate network methodology using a real example of capturing CO₂ from coal-fired power plants in the US Midwest and storing the CO₂ in depleted oil and gas fields. Results illustrate the critical need to balance CCS investments with generating a candidate network of arcs.     

Development of SAW-based multi-gas sensor for simultaneous detection of CO2 and NO2

A 440 MHz wireless and passive surface acoustic wave (SAW)-based multi-gas sensor integrated with a temperature sensor was developed on a 41° YX LiNbO₃ piezoelectric substrate for the simultaneous detection of CO₂, NO₂, and temperature. The developed sensor was composed of a SAW reflective delay lines structured by an interdigital transducer (IDT), ten reflectors, a CO₂ sensitive film (Teflon AF 2400), and a NO₂ sensitive film (indium tin oxide). Teflon AF 2400 was used for the CO₂ sensitive film because it provides a high CO₂ solubility, with good permeability and selectivity. For the NO₂ sensitive film, indium tin oxide (ITO) was used. Coupling of mode (COM) modeling was conducted to determine the optimal device parameters prior to fabrication. Using the parameters determined by the simulation results, the device was fabricated and then wirelessly measured using a network analyzer. The measured reflective coefficient S₁₁ in the time domain showed high signal/noise (S/N) ratio, small signal attenuation, and few spurious peaks. The time positions of the reflection peaks were well matched with the predicted values from the simulation. High sensitivity and selectivity were observed at each target gas testing. The obtained sensitivity was 2.12°/ppm for CO₂ and 51.5°/ppm for NO₂, respectively. With the integrated temperature sensor, temperature compensation was also performed during gas sensitivity evaluation process.     

Sensing of CO2 at room temperature using work function readout of (hetero-)polysiloxanes sensing layers

Organically modified silicates based on primary amino groups are known to be CO₂ sensitive, as they can undergo a reversible acid base reaction. In order to generate detectable CO₂ signals and to limit the cross-sensitivity to humidity, some sources suggest that these materials should be operated at higher temperatures (50-70 °C). In this paper, a new variant of CO₂ sensing is to be presented, namely a combination of work function readout and organically modified silicates, which yields CO₂ detection even at room temperature. Kelvin probe measurements are used for work function readout. The layers are intended to be used in a “Floating Gate Field Effect Transistors” (FGFETs) sensing platform (mySens) by Micronas. The reversible interaction of CO₂ with spin-coated heteropolysiloxane sensitive layers results in changes of the work function with typical signal heights of 15-20 mV (change from 400 to 4000 ppm CO₂) and response times of only a few minutes. Also, results will be presented regarding variations in the chemical nature of the films. The findings summarized in this paper point towards the possibility of a new room temperature CO₂ sensor, which comprises fast response times and sufficient sensitivity for ambient CO₂ variations.     

基于TDLAS的二氧化碳检测技术综述

精确检测CO_(2)气体浓度、控制CO_(2)气体排放是治理大气温室效应过程中最重要的部分。可调谐半导体激光吸收光谱(TDLAS)因具有高灵敏度和高可靠性的特点,广泛应用于在线监测、微量气体检测等方面。分析了TDLAS测量气体浓度的基本原理,重点介绍了直接吸收法和波长调制法并比较了两种方法的优缺点,随后介绍了近几十年来国内外应用TDLAS技术在气体检测方面取得的研究进展。最后总结了基于TDLAS的二氧化碳气体检测技术,并对其未来应用进行了展望。     

Designing cyclic pressure pulsing in naturally fractured reservoirs using an inverse looking recurrent neural network

In this paper, an inverse looking approach is presented to efficiently design cyclic pressure pulsing (huff ‘n’ puff) with N₂ and CO₂, which is an effective improved oil recovery method in naturally fractured reservoirs. A numerical flow simulation model with compositional, dual-porosity formulation is constructed. The model characteristics are from the Big Andy Field, which is a depleted, naturally fractured oil reservoir in Kentucky. A set of cyclic pulsing design scenarios is created and run using this model. These scenarios and corresponding performance indicators are fed into the recurrent neural network for training. In order to capture the cyclic, time-dependent behavior of the process, recurrent neural networks are used to develop proxy models that can mimic the reservoir simulation model in an inverse looking manner. Two separate inverse looking proxy models for N₂ and CO₂ injections are constructed to predict the corresponding design scenarios, given a set of desired performance characteristics. Predictive capabilities of developed proxy models are evaluated by comparing simulation outputs with neural-network outputs. It is observed that networks are able to accurately predict the design parameters, such as the injection rate and the duration of injection, soaking and production periods.     

Room-temperature CO2 sensing using metal-insulator-semiconductor capacitors comprising atomic-layer-deposited La2O3 thin films

Room temperature detection of CO₂ using metal-insulator-silicon (MIS) devices is reported. These devices comprise atomic layer deposited La₂O₃ thin films as the gas-sensitive dielectric layer and Pt, Pt/Ta and Al as the electrodes. Physical mechanisms that lead to the detection of CO₂ at room temperature are discussed.     

HCO-TERNARY: A FORTRAN code for calculating P–V–T–X properties and liquid vapor equilibria of fluids in the system H2O–CO2–CH4

The equation of state (EOS) for the system H₂O–CO₂–CH₄ was programmed in a FORTRAN code which allows for its utilization in several modes. In one mode, specifically designed for mathematical modeling of two-phase, two-component flow, the code accepts as independent variables (1) pressure and (2) the composition of the gas phase. Other modes allow for the calculation of phase equilibria and/or the molar volumes of H₂O and binary mixtures, with pressure and temperature as the input variables (just pressure in the case of H₂O). Another mode is used to calculate phase equilibria for ternary mixtures, with pressure, temperature and the mole fraction of water in the gas phase as input variables. The algorithms for automatic convergence utilized in each mode are described.The code was tested extensively against experimental data from the literature. Some of these data were applied in the development of the EOS, and others were published subsequently. Analyses of the performance of the code and EOS for the modes described above, in the range 50–1000°C, 0–1000 bar, are presented. P–T–X regions of best applicability of the code and EOS are also identified.     

Tidal breathing model describing end-tidal, alveolar, arterial and mixed venous CO2 and O2

Thermodilution is the current standard for determination of cardiac output. The method is invasive and constitutes a risk for the patient. As an alternative CO₂ rebreathing allows non-invasive cardiac output estimation using Ficks principle. The method relies on estimation of arterial CO₂ partial pressure from end-tidal CO₂ pressure and estimation of mixed venous CO₂ partial pressure from end-tidal CO₂ during rebreathing. Presumably the oxygenation of blood in the lung capillaries increases lung capillary CO₂ pressure due to the Haldane effect, which during rebreathing may result in overestimation of the mixed venous CO₂ pressure. However, the Haldane effect is not discussed in the current literature describing cardiac output estimation using CO₂ rebreathing. The purpose of this study is to construct and verify a compartmental tidal breathing lung model to investigate the physiological mechanisms that influence the CO₂ rebreathing technique. The model simulations show agreement with previous studies describing end-tidal to arterial differences in CO₂ pressure and rebreathing with high and low O₂ fractions in the rebreathing bag. In conclusion the simulations show that caution has to be taken when using end-tidal measurements to estimate CO₂ pressures, especially during rebreathing where the Haldane effect causes mixed venous CO₂ partial pressure to be substantially overestimated.     

Development of a linear predictive model for carbon dioxide sequestration in deep saline carbonate aquifers

CO₂ injection into deep saline aquifers is a preferred method for mitigating CO₂ emission. Although deep saline aquifers are found in many sedimentary basins and provide very large storage capacities, several numerical simulations are needed before injection to determine the storage capacity of an aquifer. Since numerical simulations are expensive and time-consuming, using a predictive model enables quick estimation of CO₂ storage capacity of a deep saline aquifer. In order to create a predictive model, the ranges of variables that affect the CO₂ storage capacity were determined from published literature data. Correlations found in literature were used for other important parameters such as pore volume compressibility and density of brine. Latin hypercube space filling design was used to construct 100 simulation cases prepared using CMG STARS. The simulation period covered a total of 300 years of CO₂ storage. By using a least-squares method, linear and nonlinear predictive models were developed to estimate CO₂ storage capacity of deep saline carbonate aquifers. Numerical dispersion effects were considered by decreasing the grid dimensions. It was observed that a dimensionless linear predictive model is better than the nonlinear. The sensitivity analyses showed that the most important parameter that affects CO₂ storage capacity is depth. Most of the (up to 90%) injected gas dissolved into the formation water and a negligible amount of CO₂ reacted with carbonate.     

Status of the TOUGH-FLAC simulator and recent applications related to coupled fluid flow and crustal deformations

This paper presents recent advancement in and applications of TOUGH-FLAC, a simulator for multiphase fluid flow and geomechanics. The TOUGH-FLAC simulator links the TOUGH family multiphase fluid and heat transport codes with the commercial FLAC^3D geomechanical simulator. The most significant new TOUGH-FLAC development in the past few years is a revised architecture, enabling a more rigorous and tight coupling procedure with improved computational efficiency. The applications presented in this paper are related to modeling of crustal deformations caused by deep underground fluid movements and pressure changes as a result of both industrial activities (the In Salah CO₂ Storage Project and the Geysers Geothermal Field) and natural events (the 1960s Matsushiro Earthquake Swarm). Finally, the paper provides some perspectives on the future of TOUGH-FLAC in light of its applicability to practical problems and the need for high-performance computing capabilities for field-scale problems, such as industrial-scale CO₂ storage and enhanced geothermal systems. It is concluded that despite some limitations to fully adapting a commercial code such as FLAC^3D for some specialized research and computational needs, TOUGH-FLAC is likely to remain a pragmatic simulation approach, with an increasing number of users in both academia and industry.     

A new equation of state and Fortran 77 program to calculate vapor–liquid phase equilibria of CH4–H2O system at low temperatures

A new equation of state (EOS) and the corresponding computer program package VLEWM are developed to calculate vapor–liquid phase equilibria and volumetric properties of CH₄–H₂O system at low temperatures. The EOS can predict vapor–liquid equilibria and volumetric properties of CH₄–H₂O system accurately at temperatures 273–383 K, and at pressures 0–1000 bar. The program package VLEWM is written in FORTRAN 77. It provides two main functions: (1) to calculate the composition in vapor phase and liquid phase of CH₄–H₂O system at equilibrium and (2) to judge the phase and to calculate molar volume of CH₄–H₂O mixture.     

Improved crystalline structure and H2S sensing performance of CuO-Au-SnO2 thin film using SiO2 additive concentration

In situ SiO₂-doped SnO₂ thin films were successfully prepared by liquid phase deposition. The influence of SiO₂ additive as an inhibitor on the surface morphology and the grain size for the thin film has been investigated. These results show that the morphology of SnO₂ film changes significantly by increasing the concentration of H₂SiF₆ solution which decreases the grain size of SnO₂. The stoichiometric analysis of Si content in the SnO₂ film prepared from various Si/Sn molar ratios has also been estimated. For the sensing performance of H₂S gas, the SiO₂-doped Cu-Au-SnO₂ sensor presents better sensitivity to H₂S gas compared with Cu-Au-SnO₂ sensor due to the fact that the distribution of SiO₂ particles in grain boundaries of nano-crystallines SnO₂ inhibited the grain growth (<6 nm) and formed a porous film. By increasing the Si/Sn molar ratio, the SiO₂-doped Cu-Au-SnO₂ gas sensors (Si/Sn = 0.5) exhibit a good sensitivity (S = 67), a short response time (t_90% < 3 s) and a good gas concentration characteristic (α = 0.6074). Consequently, the improvement of the nano-crystalline structures and high sensitivity for sensing films can be achieved by introducing SiO₂ additive into the SnO₂ film prepared by LPD method.     

Gas sensing properties of SnO2 nanowires on micro-heater

The SnO₂ nanowires (NWs) network gas sensors were fabricated on a micro-electrode and heater suspended in a cavity. The sensors showed selective detection to C₂H₅OH at a heater power during sensor operation as low as 30-40 mW. The gas response and response speed of the SnO₂ NWs sensor to 100 ppm C₂H₅OH were 4.6- and 4.7-fold greater, respectively, than those of the SnO₂ nanoparticles (NPs) sensor with the same electrode geometry. The reasons for these enhanced gas sensing characteristics are discussed in relation to the sensing materials and sensor structures.     

Mid-IR source based on a free-standing microhotplate for autonomous CO2 sensing in indoor applications

The measurement of CO₂ by Non-Dispersive InfraRed absorption (NDIR) is often used as a tracer of human occupancy in confined living spaces. The major constraint of commercial sensors comes from the power consumption of the IR source, which makes them unsuitable for autonomous operation.This paper reports the fabrication and the characterization of a black-body IR source based on a microhotplate micromachined in Si and suitable to work above 650 °C. The use of state-of-the-art MEMS technologies allows to lower the power consumption below 50 mW while ensuring a lifetime well beyond 10 years.The radiance of the microhotplate in the spectral range where CO₂ adsorption takes place indicated that the device works as a quasi-perfect blackbody source providing enough power to drive an autonomous NDIR system for CO₂ detection.     

Optical CO2 sensor with the combination of colorimetric change of α-naphtholphthalein and internal reference fluorescent porphyrin dye

A new optical CO₂ sensor based on the overlay of the CO₂ induced absorbance change of pH indicator dye α-naphtholphthalein with the fluorescence of tetraphenylporphyrin (TPP) was developed. The observed luminescence intensity from TPP at 655 nm increased with increasing the CO₂ concentration. The ratio I₁₀₀/I₀ values of the sensing films consisting of α-naphtholphthalein in ethyl cellulose layer and TPP in polystyrene layer, where I₀ and I₁₀₀ represent the detected luminescence intensities from a layer exposed to 100% nitrogen and 100% CO₂, respectively, that the sensitivity of the sensor, are more than 53.9. The response and recovery times of the sensing films consisting of α-naphtholphthalein in ethyl cellulose layer and TPP in polystyrene layer were less than 5 s for switching from nitrogen to CO₂, and for switching from CO₂ to nitrogen. The signal changes were fully reversible and no hysterisis was observed during the measurements. The highly sensitive optical CO₂ sensor based on fluorescence intensity changes of TPP due to the absorption change of α-naphtholphthalein with CO₂ was achieved.     

A route to high sensitivity and rapid response Nb2O5-based gas sensors: TiO2 doping, surface embossing, and voltage optimization

We report a novel route for the fabrication of highly sensitive and rapidly responding Nb₂O₅-based thin film gas sensors. TiO₂ doping of Nb₂O₅ films is carried out by co-sputtering without the formation of secondary phases and the surface area of TiO₂-doped Nb₂O₅ films is increased via the use of colloidal templates composed of sacrificial polystyrene beads. The gas sensitivity of Nb₂O₅ films is enhanced through both the TiO₂ doping and the surface embossing. An additional enhancement on the gas sensitivity is obtained by the optimization of the bias voltage applied between interdigitated electrodes beneath Nb₂O₅-based film. More excitingly, such a voltage optimization leads to a substantial decrease in response time. Upon exposure to 50 ppm CO at 350 °C, a gas sensor based on TiO₂-doped Nb₂O₅ film with embossed surface morphology exhibits a very high sensitivity of 475% change in resistance and a rapid response time of 8 s under 3 V, whereas a sensor based on plain Nb₂O₅ film shows a 70% resistance change and a response time of 65 s under 1 V. Thermal stability tests of our Nb₂O₅-based sensor reveal excellent reliability which is of particular importance for application as resistive sensors for a variety gases.     

Hydrogen sensing and mechanism of M-doped SnO2 (M = Cr, Cu and Pd) nanocomposite

The microstructure of M-doped SnO₂ (M = Cr³⁺, Cu²⁺ and Pd²⁺) prepared by the sol–gel method and their gas-sensing performance were investigated. In particular, we focus on the effects of metallic ions on the hydrogen sensing behavior of the SnO₂-based sensor. It is found that hydrogen gas response of SnO₂ can be enhanced evidently by adding Pd²⁺, while such effect from Cr³⁺ and Cu²⁺ exhibits somewhat slight. A theoretical study based on first principles calculation shows that SnO₂–Pd (1 1 0) surface enable adsorb more H₂ gas and receive larger electrons from adsorbed H₂ molecule, thereby holding the potential for the improvement of gas response to hydrogen.