Production Rate Profiles Research Articles

Changes in chemical properties and microbial communities' composition of a forest litter-based biofertilizer produced through aerated solid-state culture under different oxygen conditions.

Fermented forest litter (FFL) is a bioproduct used as biofertilizer for several decades in Eastern Asia and Latin America. It is locally handcrafted by farmers in anaerobic conditions by fermenting forest litter added with agricultural by-products such as whey, cereal bran, and molasses. The aim of this study was to characterize the FFL process and product through gas and liquid chromatography analyses. It also provides some highlights on the influence of O2 on this solid-state culture. Under anoxic condition, a maximum CO2 production rate (CDPR) of 0.41mL/h∙g dry matter (dm) was reached after 8days. The main volatile organic compounds (VOCs) were ethanol and ethyl acetate, with a production rate profile similar to CDPR. After 21days of culture, no residual sucrose nor lactose was detected. Lactic and acetic acids reached 58.8mg/g dm and 10.2mg/g dm, respectively, ensuring the acidification of the matrix to a final pH of 4.72. A metabarcoding analysis revealed that heterolactic acid bacteria (Lentilactobacillus, Leuconostoc), homolactic acid bacteria (Lactococcus), and yeasts (Saccharomyces, Clavispora) were predominant. Predicted genes in the microbiome confirmed the potential link between detected bacteria and acids and VOCs produced. When O2 was fed to the cultures, final pH reached values up to 8.5. No significant amounts of lactic nor acetic acid were found. In addition, a strong shift in microbial communities was observed, with a predominance of Proteobacteria and molds, among which are potential pathogens like Fusarium species. This suggests that particular care must be brought to maintain anoxic conditions throughout the process.

Photochemical escape of atomic C and N on Mars during the X8.2 solar flare on 10 September 2017

Context. Characterizing the response of the upper Martian atmosphere to solar flares could provide important clues as to the climate evolution of the red planet in the early Solar System, when the extreme ultraviolet and soft X-ray radiation was substantially higher than the present-day level and when these events occurred more frequently. A critical process herein is the Martian atmospheric escape in the form of atomic C and N, as mainly driven by CO2/CO and N2 dissociation. Aims. This study is devoted to evaluating how these escape rates varied on the dayside of Mars during the X8.2 solar flare on 10 September 2017. Methods. The background Martian atmospheric structures, before, during, and after the flare, are constructed from the Neutral Gas and Ion Mass Spectrometer measurements made on board the Mars Atmosphere and Volatile Evolution spacecraft, from which the hot C and N production rate profiles via different photon and photoelectron impact channels and on different flare stages are obtained. They are combined with the respective escape probability profiles computed using a test particle Monte Carlo approach to derive the atomic C and N escape rates on the dayside of Mars. Results. Our calculations indicate that the pre-flare C and N escape rates are (1.3−1.4) × 1024 s−1 over the dayside of Mars. During the event, we find a modest decrease in the C escape rate of 8% about 1 h after the flare peak, followed by a recovery to the pre-flare level several hours later. However, an opposite trend is found for the N escape rate during the same period, which shows an increase of 20% followed by a recovery to the pre-flare level. Conclusions. The distinction between C and N in terms of the variation in the escape rate during the solar flare reflects the competition between two flare-induced effects: enhanced hot atom production via dissociation and enhanced collisional hindrance due to atmospheric expansion.

Characterization of Wormhole Growth and Propagation Dynamics During Cold Heavy Oil Production with Sand (CHOPS) Processes by Integrating Rate Transient Analysis and a Pressure-Gradient-Based Sand Failure Criterion

Summary In this work, theoretical models have been formulated, validated, and applied to characterize the dynamic wormhole growth and propagation dynamics during cold heavy oil production with sand (CHOPS) processes by integrating rate transient analysis (RTA) and a pressure-gradient-based (PGB) sand failure criterion. More specifically, a coupling fluid-solid flow model is proposed by incorporating the recently proposed PGB sand failure criterion with sand production. Then, the source function method is applied to solve the fluid flow problem in the matrix subsystem by considering each generated wormhole segment as a sink source, while the finite difference method is applied to solve the fluid-sand flow problem in the wormhole subsystem. The sand failing at each segment is induced and propagated once the PGB sand failure criterion has been reached. Furthermore, transient-rate-type curves are generated to determine the dynamic wormhole network conditioned to the measured fluids and sand production profiles. Also, effects of the PGB sand failure criterion and reservoir properties on the transient rate behavior for CHOPS wells can be examined and analyzed. A gradual increase in the production rate profile occurs at the early times due to the wormhole growth and propagation. The wormhole network can be dynamically characterized by matching both the sand production rate and transient fluid production rate. The former is found to be greatly affected by the breakdown pressure gradient, while the effective wormhole coverage and intensity dominate the latter. Once the transient rate responses for both static and dynamic wormhole networks are validated with numerical simulation, the newly proposed method has been extended to field applications under various constraints, demonstrating that the fluid and sand production data of CHOPS wells can be integrated to accurately characterize the dynamic wormhole network within a unified, consistent, and efficient framework.

Performance Analysis of Gas Wells Based on the Conventional Decline Parameters and the Flow Integral Equation

The estimation of reserves and performance prediction are two vital tasks for the development of gas reservoirs where the evaluation of gas in place or well-controlled reserves, as the foundation of the performance analysis of gas wells, turns to be exceedingly significant. Advanced production data analysis or modern rate transient analysis (RTA) methods mainly depend on the iterative calculations of material balance quasitime (tca) and type curve fitting, the essence of which is to update the average reservoir pressure data time and again. The traditional Arps’ decline models are of empirical nature despite the convenience and applicability to the constant bottomhole pressure (BHP) condition. In order to avoid the implicit iteration, this paper develops an explicit method for estimating the average reservoir pressure on the basis of dynamic material balance equation (DMBE), termed “flow integral method,” which can be applied to various gas production systems under boundary-dominated flow (BDF). Based on the flow integral method and the decline parameter evaluation, we employ the hyperbolic decline model to model the gas well performance at a constant BHP. The analytical formulations of decline rate and decline exponent are deduced from the DMBE and the static material balance equation (SMBE) considering the elastic compressibilities of rock pore and bound water. The resulting decline parameter method for explicit estimation of gas reserves boasts a solid and rigorous theory foundation that production rate, decline rate, and average reservoir pressure profiles have reference to each other, and its implementation steps are explained in the paper. The SMBE can, combined with the estimated pressure profile by the flow integral method, also be used to determine gas reserves which is not limited to the constant-BHP condition and can calibrate the estimates of the decline parameter method. The proposed methods are proven effective and reliable with several numerical cases at different BHPs and a field example.

Production Forecasting of Tight Oil Reservoirs Using Improved Decline Model

Tight oil formation has become interest for many researchers since less than 10% of the OOIP can be obtained from the primary recovery. Other thinking on how to improve the oil recovery is still done. Decline curve analysis is one of the methods commonly used to estimate the ultimate recovery and the production rate profile of tight oil reservoirs. The present work uses the Duong model to overcome the limitations of Arps’ model. This study compares the observed values from simulation results to the estimated values from Duong model over 30 years. In our previous work, we demonstrated that some key parameters such as reservoir permeability, number of fractures per stage, fracture permeability, CO2 injection rate, CO2 injection time, CO2 soaking time, number of CO2 huff-n-puff cycle have a great effect on the improve of oil recovery of tight oil reservoirs while applying CO2 huff-n-huff. This work also focused on the development of some regression equations that can help to get approximatively the oil recovery factor of any formation, the goal here is to generate a suite of diagnostic plots to estimate oil recovery. These equations have revealed that the best fit is the polynomial regression. Results show the overestimation of oil reserve by Duong model when the flow regime changes from linear flow.

Energy deposition in Saturn’s equatorial upper atmosphere

We construct Saturn equatorial neutral temperature and density profiles of H, H2, He, and CH4, between 10−12 and 1 bar using measurements from Cassini’s Ion Neutral Mass Spectrometer (INMS) taken during the spacecraft’s final plunge into Saturn’s atmosphere on 15 September 2017, combined with previous deeper atmospheric measurements from the Cassini Composite InfraRed Spectrometer (CIRS) and from the UltraViolet Imaging Spectrograph (UVIS). These neutral profiles are fed into an energy deposition model employing soft X-ray and Extreme UltraViolet (EUV) solar fluxes at a range of spectral resolutions (Δλ=4×10−3nm to 1 nm) assembled from TIMED/SEE, from SOHO/SUMER, and from the Whole Heliosphere Interval (WHI) quiet Sun campaign. Our energy deposition model calculates ion production rate profiles through photo-ionisation and electron-impact ionisation processes, as well as rates of photo-dissociation of CH4. The ion reaction rate profiles we determine are important to obtain accurate ion density profiles, meanwhile methane photo-dissociation is key to initiate complex organic chemical processes. We assess the importance of spectral resolution in the energy deposition model by using a high-resolution H2 photo-absorption cross section, which has the effect of producing additional ionisation peaks near 800 km altitude. We find that these peaks are still formed when using low-resolution (Δλ=1nm) or mid-resolution (Δλ=0.1nm) solar spectra, as long as high-resolution cross sections are included in the model.

Computational Fluid Dynamics Study of a Nonpremixed Turbulent Flame Using openfoam: Effect of Chemical Mechanisms and Turbulence Models

Abstract This article presents a study of the influence of chemical mechanisms and turbulence models on Reynolds-averaged Navier–Stokes (RANS) simulations of the CH4/H2/N2-air turbulent diffusion flame, i.e., the so-called DLR-A flame. The first part of this study is focused on the assessment of the influence of four chemical models on predicted profiles of the DLR-A flame. The chemical mechanisms considered are as follows: (i) a C2 compact skeletal mechanism, which is derived from the GRI3.0 mechanism using an improved multistage reduction method, (ii) a C1 skeletal mechanism containing 41 elementary reactions amongst 16 species, (iii) the global mechanism by Jones and Lindstedt, (iv) and a global scheme consisting of the overall reactions of methane and dihydrogen. RANS numerical results (e.g., velocities, temperature, species, or the heat production rate profiles) obtained running the reactingFOAM solver with the four chemical mechanisms as well as the standard k − ɛ model, the partially stirred reactor (PaSR) combustion model, and the P − 1 radiation model indicate that the C2 skeletal mechanism yields the best agreement with measurements. In the second part of this study, four turbulence models, namely, the standard k − ɛ model, the renormalization group (RNG) k − ɛ model, realizable k − ɛ model, and the k − ω shear stress transport (SST) model, are considered to evaluate their effects on the DLR-A flame simulation results obtained with the C2 skeletal mechanism. Results reveal that the predictions obtained with the standard k − ɛ and the RNG k − ɛ models are in very good agreement with the experimental data. Hence, for simple jet flame with moderately high Reynolds number such as the DLR-A flame, the standard k-epsilon can model the turbulence with a very good accuracy.

Impact of a Tapered Design in the Performance of Diffusion Flame Reactors

Several research projects developed processes for precise nanoparticle positioning with high production rates. Among the gas phase manipulation strategies, the study of the inertial properties received special attention for the fabrication of nanostructured systems. In particular, aerodynamic focusing technique has allowed particles concentration onto a single streamline, improving collimated particle beam formation and opening new perspectives for nanoparticles production in the gas phase. In this paper, the influence of the reactor design was investigated, particularly in respect to the gas phase characteristics, aiming to improve the nanoparticles focusing. It was observed that a concentrated beam can be obtained in the new tapered reactor design without significantly affect the production rate and temperature profile. In addition, the coupling of aerodynamic lenses to the tapered reactor was also investigated, showing that the flow can be better focused at the cost of an increase in the average temperature and pressure drop.

Semi-continuous pilot-scale microbial oil production with Metschnikowia pulcherrima on starch hydrolysate

BackgroundHeterotrophic microbial oils are potentially a more sustainable alternative to vegetable or fossil oils for food and fuel applications. However, as almost all work in the area is conducted on the laboratory scale, such studies carry limited industrial relevance and do not give a clear indication of what is required to produce an actual industrial process. Metschnikowia pulcherrima is a non-pathogenic industrially promising oleaginous yeast which exhibits numerous advantages for cost-effective lipid production, including a wide substrate uptake, antimicrobial activity and fermentation inhibitor tolerance. In this study, M. pulcherrima was fermented in stirred tank reactors of up to 350 L with 250-L working volume in both batch and semi-continuous operation to highlight the potential industrial relevance. Due to being food-grade, suitable for handling at scale and to demonstrate the oligosaccharide uptake capacity of M. pulcherrima, enzyme-hydrolysed starch in the form of glucose syrup was selected as fermentation feedstock.ResultsIn batch fermentations on the 2-L scale, a lipid concentration of 14.6 g L−1 and productivity of 0.11 g L−1 h−1 were achieved, which was confirmed at 50 L (15.8 g L−1; 0.10 g L−1 h−1). The maximum lipid production rate was 0.33 g L−1 h−1 (daily average), but the substrate uptake rate decreased with oligosaccharide chain length. To produce 1 kg of dry yeast biomass containing up to 43% (w/w) lipids, 5.2 kg of the glucose syrup was required, with a lipid yield of up to 0.21 g g−1 consumed saccharides. In semi-continuous operation, for the first time, an oleaginous yeast was cultured for over 2 months with a relatively stable lipid production rate (around 0.08 g L−1 h−1) and fatty acid profile (degree of fatty acid saturation around 27.6% w/w), and without contamination. On the 250-L scale, comparable results were observed, culminating in the generation of nearly 10 kg lipids with a lipid productivity of 0.10 g L−1 h−1.ConclusionsThe results establish the importance of M. pulcherrima for industrial biotechnology and its suitability to commercially produce a food-grade oil. Further improvements in the productivity are required to make M. pulcherrima lipid production industrial reality, particularly when longer-chain saccharides are involved.

Dayside nitrogen and carbon escape on Titan: the role of exothermic chemistry

Context. Atmospheric escape has an appreciable impact on the long-term climate evolution on terrestrial planets. Exothermic chemistry serves as an important mechanism driving atmospheric escape and the role of such a mechanism is of great interest for Titan due to its extremely complicated atmospheric and ionospheric composition. Aims. This study is devoted to a detailed investigation of neutral N and C escape on the dayside of Titan, which is driven by exothermic neutral–neutral, ion–neutral, and dissociative recombination (DR) reactions. It was carried out based on the extensive measurements of Titan’s upper atmospheric structure by a number of instruments on board Cassini, along with an improved understanding of the chemical network involved. Methods. A total number of 14 C- and N-containing species are investigated based on 146 exothermic chemical reactions that release hot neutrals with nascent energies above their respective local escape energies. For each species and each chemical channel, the hot neutral production rate profile is calculated, which provides an estimate of the corresponding escape rate when combined with the appropriate escape probability profile obtained from a test particle Monte Carlo model. Results. Our calculations suggest a total N escape rate of 9.0 × 1023 s−1 and a total C escape rate of 4.2 × 1023 s−1, driven by exothermic chemistry and appropriate for the dayside of Titan. The former is primarily contributed by neutral-neutral reactions, whereas the latter is dominated by ion–neutral reactions; however, contributions from neutral–neutral and DR reactions to the latter cannot be ignored either. Our calculations further reveal that the bulk of N escape is driven by hot N(4S) production from the collisional quenching of N(2D) by ambient N2, while C escape is mainly driven by hot CH3 and CH4 production via a number of important ion–neutral and neutral–neutral reactions. Conclusions. Considered in the context of prior investigations of other known escape mechanisms, we suggest that exothermic chemistry is likely to contribute appreciably to non-thermal C escape on the dayside of Titan, although it plays an insignificant role in N escape.

Face-Detection Algorithm Handles Big Data To Help Identify Candidates for Restimulation

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 187328, “From Face Detection to Fractured-Reservoir Characterization: Big Data Analytics for Restimulation-Candidate Selection,” by Egbadon Udegbe, SPE, Eugene Morgan, SPE, and Sanjay Srinivasan, SPE, The Pennsylvania State University, prepared for the 2017 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 9–11 October. The paper has not been peer reviewed. The recent proliferation of subsurface data from instrumented wells has created significant challenges for traditional production-data-analysis methods to extract useful information for reservoir management. This paper demonstrates the viability of a production-data-classification approach adapted from real-time face detection for identifying restimulation candidates. The approach has the potential to be used as a big-data analytic tool for long-duration production-data analysis to serve as a screening tool for selection of restimulation candidates. Introduction Restimulation treatments in producing shale wells have the potential to improve economic performance by increasing the conductivity of existing fractures or enhancing their contact with the formation. The influence of matrix and fracture characteristics on the success of restimulation, however, is not completely understood, which has led to uncertainty in determining favorable candidate wells. Several methods to select restimulation candidates have been proposed. These methods, however, are time-consuming and tend to require detailed input data or exhibit a lack of generality for other reservoir settings. This paper aims to address these challenges with a new methodology for fast and robust analysis of production data from hydraulically fractured wells. A dual-permeability forward-flow modeling approach is used to generate multiple realizations of production-rate profiles by modifying fracture and other parameters. Using this data, pattern-recognition tools are applied to help uncover trends associated with favorable and unfavorable restimulation candidates. This is achieved using a binary classification framework adapted from real-time face detection, which uses simple numerical criteria computed directly from raw flow-rate data, thus eliminating the need for detailed information and promoting computational efficiency. The algorithm also provides probabilistic predictions, which serve as a means to rank candidate wells. While the process of training the classifier has the potential to be computationally intensive, the application of the trained classifier on the observed data is extremely fast, making the method useful for real-time classification of well performance. Face-Detection Overview The Viola-Jones face-detection algorithm is a binary classification scheme that takes labeled examples of images containing faces and nonfaces and develops a set of numerical criteria for distinguishing between both categories. Using these rules, an arbitrary test image can be analyzed and classified as a face or a nonface.

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO2 capture

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capture and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. The paper also presents a Lyapunov stability analysis of the proposed scheme.

Helical Boundary Conditions To Capture Interpattern Flow in In-Situ-Upgrading-Process Pattern Simulations

Summary The in-situ upgrading process (IUP) involves very complicated multiphase thermal transport and chemical reactions. Numerical simulation of IUP is computationally expensive, and direct simulation of field-scale IUP models becomes prohibitive. A practical way is to simulate a sector model under proper boundary and initial conditions and then upscale the simulation results to the full field scale with superposition techniques. Because of nonsymmetric pattern configuration and time delay of developing patterns sequentially, interpattern flow may become significant, and its impact on the simulation results cannot be neglected. Therefore, no-flow boundary conditions become inappropriate for such IUP sector models. In this paper, we proposed a new type of “helical” boundary conditions (HBCs) in which pressures and temperatures are periodic in space, except for a shift in time. The HBCs are specifically designed for a field-scale IUP development in which patterns are developed sequentially in time, along a long strip. In such a development, each pattern has exactly the same well configuration and operational schedule, except for a time delay. Because of high viscosity of heavy oil and low heat conductivity of formation rock, the impact of field boundary conditions on interpattern flow will be dampened quickly within only a few patterns, and a repetitive “pseudosteady state” of interpattern flow develops, in which the energy and mass fluxes from the previous pattern to the current pattern are the same as those from the current pattern to the next pattern, except for the delay time. By use of a 1D heat-transfer model, we analytically demonstrate that the pseudosteady state and therefore the HBCs hold for a long strip of patterns. A practical procedure to implement these HBCs in numerical simulation is developed, in which the state variables (pressure, temperature, and fluid composition) are iteratively updated in gridblocks on both edges of a sector model that is composed of two patterns. This iterative approach to impose HBCs was implemented in our in-house simulator. This approach was tested and validated by simulation results of an IUP model that is composed of 59 patterns. Our results show that the full-field boundary conditions only affect the production-rate profiles of the first and the last patterns. Production-rate profiles generated from all other patterns are almost identical except for the interpattern time delay, which also validates the pseudosteady state of interpattern flow for a more-complicated IUP model. The two-pattern sector model with the HBCs converges in three to four iterations. The production-rate profiles of oil, gas, and water generated by the sector model with HBCs are almost identical to those produced from one of those inner patterns in the 59-pattern model. With the 1D example, we also analytically demonstrate the convergence of our numerical implementation of HBCs. In terms of clock-time used, it is possible to achieve 5N time speedup through application of the HBCs, in which N is the number of patterns in a field-scale model. Therefore, the new approach is proved a key enabler for field-scale IUP pattern optimization. Provided that the interpattern-pressure communication that is induced by the pattern delay time is not too severe, we expect that one can also apply HBCs to the simulation of other field-scale thermal processes, such as the in-situ conversion process and steamfloods.

On the wave and current interaction with a rippled seabed in the coastal ocean bottom boundary layer

Interactions of currents and waves with a rippled seabed in the inner part of the coastal ocean bottom boundary layer are studied using particle image velocimetry, ADV, and bottom roughness measurements. Mean velocity profiles collapse with appropriate scaling in the log layer, but vary substantially in the roughness sublayer. When wave-induced motions are similar or greater than the mean current, the hydrodynamic roughness ( z0) determined from velocity profiles is substantially larger than directly measured values. The roughness signature in turbulent energy spectra persists with elevation when its scale falls in the dissipation range, but decays in the log layer for larger roughness elements. Reynolds shear stress profiles peak in the lower parts of the log layer, diminishing below it, and gradually decaying at higher elevations. In contrast, wave shear stresses are negligible within the log layer, but become significant within the roughness sublayer. This phenomenon is caused by an increase in the magnitude and phase lag of the vertical component of wave-induced motion. No single boundary layer length scale collapses the Reynolds stresses, but both the Prandtl mixing length and eddy viscosity profiles agree well with the classical model of linear increase with elevation, especially near the seabed. Within the log region, profiles of shear production and dissipation rates of turbulence converge. Below it, dissipation rapidly increases, peaking near the seabed. Conversely, the shear production decays near the seabed, in agreement with the eddy viscosity model, but in contrast to both laboratory and computational rough wall studies.

Ionization and NO production in the polar mesosphere during high-speed solar wind streams: model validation and comparison with NO enhancements observed by Odin-SMR

Abstract. Precipitation of high-energy electrons (EEP) into the polar middle atmosphere is a potential source of significant production of odd nitrogen, which may play a role in stratospheric ozone destruction and in perturbing large-scale atmospheric circulation patterns. High-speed streams of solar wind (HSS) are a major source of energization and precipitation of electrons from the Earth's radiation belts, but it remains to be determined whether these electrons make a significant contribution to the odd-nitrogen budget in the middle atmosphere when compared to production by solar protons or by lower-energy (auroral) electrons at higher altitudes, with subsequent downward transport. Satellite observations of EEP are available, but their accuracy is not well established. Studies of the ionization of the atmosphere in response to EEP, in terms of cosmic-noise absorption (CNA), have indicated an unexplained seasonal variation in HSS-related effects and have suggested possible order-of-magnitude underestimates of the EEP fluxes by the satellite observations in some circumstances. Here we use a model of ionization by EEP coupled with an ion chemistry model to show that published average EEP fluxes, during HSS events, from satellite measurements (Meredith et al., 2011), are fully consistent with the published average CNA response (Kavanagh et al., 2012). The seasonal variation of CNA response can be explained by ion chemistry with no need for any seasonal variation in EEP. Average EEP fluxes are used to estimate production rate profiles of nitric oxide between 60 and 100 km heights over Antarctica for a series of unusually well separated HSS events in austral winter 2010. These are compared to observations of changes in nitric oxide during the events, made by the sub-millimetre microwave radiometer on the Odin spacecraft. The observations show strong increases of nitric oxide amounts between 75 and 90 km heights, at all latitudes poleward of 60° S, about 10 days after the arrival of the HSS. These are of the same order of magnitude but generally larger than would be expected from direct production by HSS-associated EEP, indicating that downward transport likely contributes in addition to direct production.

An empirical approach to modeling ion production rates in Titan's ionosphere II: Ion production rates on the nightside

AbstractIonization of neutrals by precipitating electrons and ions is the main source of Titan's nightside ionosphere. This paper has two goals: (1) characterization of the role of electron impact ionization on the nightside ionosphere for different magnetospheric conditions and (2) presentation of empirical ion production rates determined using densities measured by the Cassini Ion and Neutral Mass Spectrometer on the nightside. The ionosphere between 1000 and 1400 km is emphasized. We adopt electron fluxes measured by the Cassini Plasma Spectrometer‐Electron Spectrometer and the Magnetospheric Imaging Instrument as classified by Rymer et al. (2009). The current paper follows an earlier paper (Paper I), in which we investigated sources of Titan's dayside ionosphere and demonstrated that the photoionization process is well understood. The current paper (Paper II) demonstrates that modeled and empirical ionization rates on the nightside are in agreement with an electron precipitation source above 1100 km. Ion production rate profiles appropriate for different Saturnian magnetospheric conditions, as outlined by Rymer et al., are constructed for various magnetic field topologies. Empirical production rate profiles are generated for deep nightside flybys of Titan. The results also suggest that at lower altitudes (below 1100 km) another source, such as ion precipitation, is probably needed.

An empirical approach to modeling ion production rates in Titan's ionosphere I: Ion production rates on the dayside and globally

AbstractTitan's ionosphere is created when solar photons, energetic magnetospheric electrons or ions, and cosmic rays ionize the neutral atmosphere. Electron densities generated by current theoretical models are much larger than densities measured by instruments on board the Cassini orbiter. This model density overabundance must result either from overproduction or from insufficient loss of ions. This is the first of two papers that examines ion production rates in Titan's ionosphere, for the dayside and nightside ionosphere, respectively. The first (current) paper focuses on dayside ion production rates which are computed using solar ionization sources (photoionization and electron impact ionization by photoelectrons) between 1000 and 1400 km. In addition to theoretical ion production rates, empirical ion production rates are derived from CH4, CH3+, and CH4+ densities measured by the INMS (Ion Neutral Mass Spectrometer) for many Titan passes. The modeled and empirical production rate profiles from measured densities of N2+ and CH4+ are found to be in good agreement (to within 20%) for solar zenith angles between 15 and 90°. This suggests that the overabundance of electrons in theoretical models of Titan's dayside ionosphere is not due to overproduction but to insufficient ion losses.

PRECIPITATION OF ENERGETIC NEUTRAL ATOMS AND INDUCED NON-THERMAL ESCAPE FLUXES FROM THE MARTIAN ATMOSPHERE

The precipitation of energetic neutral atoms, produced through charge exchange collisions between solar wind ions and thermal atmospheric gases, is investigated for the Martian atmosphere. Connections between parameters of precipitating fast ions and resulting escape fluxes, altitude-dependent energy distributions of fast atoms and their coefficients of reflection from the Mars atmosphere, are established using accurate cross sections in Monte Carlo simulations. Distributions of secondary hot atoms and molecules, induced by precipitating particles, have been obtained and applied for computations of the non-thermal escape fluxes. A new collisional database on accurate energy-angular dependent cross sections, required for description of the energy-momentum transfer in collisions of precipitating particles and production of non-thermal atmospheric atoms and molecules, is reported with analytic fitting equations. 3D Monte Carlo simulations with accurate energy-angular dependent cross sections have been carried out to track large ensembles of energetic atoms in a time-dependent manner as they propagate into the Martian atmosphere and transfer their energy to the ambient atoms and molecules. Results of the Monte Carlo simulations on the energy-deposition altitude profiles, reflection coefficients, and time-dependent atmospheric heating, obtained for the isotropic hard sphere and anisotropic quantum cross sections, are compared. Atmospheric heating rates, thermalization depths, altitude profiles of production rates, energy distributions of secondary hot atoms and molecules, and induced escape fluxes have been determined.

Thermophysical simulations of comet Hale-Bopp

Aims. In this work, we simulate the global behavior of comet Hale-Bopp with our thermophysical model starting with simple, homogeneous conditions, so that dust mantling and the active area develop consistently depending on the properties of the simulated nucleus. We aim to obtain a range of compatibility between our model and the observations, that can be used as constraints on some of the characteristics of cometary nuclei. Methods. Our thermophysical model includes crystallization (and release of trapped CO), sublimation/recondensation, heat and gas transport through the nucleus, and dragged dust release. We run a battery of simulations with different parameter sets selected according to our current knowledge of comets and compare our results with observational data. Initial calculations are performed for a comet radius R0 = 30 km. To match the calculated integrated H2O production to the observed rate, we renormalize to a new R ,w hich must be within 20 and 40 km, that is a range compatible with several estimates. Further selection is performed comparing the simulated water and carbon monoxide production rate profiles with the observational profiles and checking that the observational upper/lower limits of the H2O production are fulfilled. Results. We have found a reasonable agreement between our model and the data for H2O and CO production rates, without the need of distributed sources, for the following initial conditions: the nucleus is composed of water, carbon monoxide, and dust with a moderate dust proportion, tending to be icy, with a dust-to-ice ratio of between 0.5 and 1. The water ice must be initially amorphous with 15 to 20% of trapped carbon monoxide. The icy matrix has a thermal inertia between 100 and 200 J m −2 Ks −1/2 , considering the initial composition with crystalline ice at 140 K. The dust follows an exponential size distribution with particles from 0.1 μ mt o 1m m and leaves the comet dragged by the expelled vapor with a dragging efficiency (dust-to-gas ratio) of 3.

Using geological strength index (GSI) to model uncertainty in rock mass properties of coal for CBM/ECBM reservoir geomechanics

The use of geostatistics has become an important concept to characterize uncertainty in reservoir simulations. Only recently has the concept been applied to geomechanics and coupled reservoir geomechanical simulations. The work presented here describes how the Geological Strength Index (GSI) is used to represent the fractured reservoir properties of a coalseam reservoir, and link changes in flow properties with stress changes as well as to strength and deformation. The approach is demonstrated by using a spherical geostatistical model to create 11 GSI realizations and one constant GSI model.Two years of primary methane production and then 3months CO2 storage were simulated using each of the 12 models as inputs. Much higher cumulative gas and gas production rate profiles were observed for models with a mean GSI below 80, than the 80GSI model. All models above 80 GSI show much lower cumulative gas and gas production rates than the 80GSI model. The same trend held true for the CO2 injection component of the operation. Stress path profiles for three monitoring points in the reservoir showed large variability, but similar paths, whereas monitoring points in the overlying caprock showed very low variability for each realization.