Scott James

Fully compositional and thermal reservoir simulation

Abstract Fully compositional and thermal reservoir simulation capabilities are important in oil exploration and production. There are significant resources in existing wells and in heavy oil, oil sands, and deep-water reservoirs. This article has two main goals: (1) to clearly identify chemical engineering sub-problems within reservoir simulation that the PSE community can potentially make contributions to and (2) to describe a new computational framework for fully compositional and thermal reservoir simulation based on a combination of the Automatic Differentiation-General Purpose Research Simulator (AD-GPRS) and the multiphase equilibrium flash library (GFLASH). Numerical results for several chemical engineering sub-problems and reservoir simulations for two EOR applications are presented. Reservoir simulation results clearly show that the Solvent Thermal Resources Innovation Process (STRIP) outperforms conventional steam injection using two important metrics – sweep efficiency and oil recovery.

Analysis and modeling of Nannochloropsis growth in lab, greenhouse, and raceway experiments

Efficient production of algal biofuels could reduce dependence on foreign oil by providing a domestic renewable energy source. Moreover, algae-based biofuels are attractive for their large oil yield potential despite decreased land use and natural resource (e.g., water and nutrients) requirements compared to terrestrial energy crops. Important factors controlling algal lipid productivity include temperature, nutrient availability, salinity, pH, and the light-to-biomass conversion rate. Computational approaches allow for inexpensive predictions of algae growth kinetics for various bioreactor sizes and geometries without the need for multiple, expensive measurement systems. Parametric studies of algal species include serial experiments that use off-line monitoring of growth and lipid levels. Such approaches are time consuming and usually incomplete, and studies on the effect of the interaction between various parameters on algal growth are currently lacking. However, these are the necessary precursors for computational models, which currently lack the data necessary to accurately simulate and predict algae growth. In this work, we conduct a lab-scale parametric study of the marine alga Nannochloropsis salina and apply the findings to our physics-based computational algae growth model. We then compare results from the model with experiments conducted in a greenhouse tank and an outdoor, open-channel raceway pond. Results show that the computational model effectively predicts algae growth in systems across varying scale and identifies the causes for reductions in algal productivities. Applying the model facilitates optimization of pond designs and improvements in strain selection.

Estimating the Storm Surge Recurrence Interval for Hurricane Sandy

Hurricane Sandy’s storm surge peaked at 2.87 m (9.40 ft) above mean sea level (MSL) (9.64 ft Manhattan Borough Datum [MBD]) at the southern tip of Manhattan in New York City on October 29, 2012 at 9:24 pm. The peak storm surge coincided with a tide of 0.64 m MSL (0.24 ft MBD), only 30 minutes after a high tide, contributing to catastrophic flooding of near-coastal areas. Traditional flood analysis fitting techniques using various probability distribution functions (normal, lognormal, Gumbel, and log-Pierson III) yielded return frequencies from 667 years to over 10,000 years. The more advanced Lin et al. (2010; 2012) analyses yielded recurrence intervals of between 559 and 650 years for the storm surge alone and 993 years for the surge plus tide. Considering the 2.77-mm/yr (0.11-in/yr) sea-level rise and using the analysis of Lin et al. (2012), future storms equal in magnitude to Hurricane Sandy will result in even greater flooding.

Rapid hydrogen gas generation using reactive thermal decomposition of uranium hydride.

Oxygen gas injection has been studied as one method for rapidly generating hydrogen gas from a uranium hydride storage system. Small scale reactors, 2.9 g UH{sub 3}, were used to study the process experimentally. Complimentary numerical simulations were used to better characterize and understand the strongly coupled chemical and thermal transport processes controlling hydrogen gas liberation. The results indicate that UH{sub 3} and O{sub 2} are sufficiently reactive to enable a well designed system to release gram quantities of hydrogen in {approx} 2 seconds over a broad temperature range. The major system-design challenge appears to be heat management. In addition to the oxidation tests, H/D isotope exchange experiments were performed. The rate limiting step in the overall gas-to-particle exchange process was found to be hydrogen diffusion in the {approx}0.5 {mu}m hydride particles. The experiments generated a set of high quality experimental data; from which effective intra-particle diffusion coefficients can be inferred.

Simulating Flow Changes Due to Current Energy Capture: SNL-EFDC Model Verification

Increasing interest in current energy capture (CEC) has led to significant efforts to optimally design and site emerging technologies to maximize energy conversion and minimize effects on the environment. Turbine-based CEC technologies remove energy (momentum) from tidal/current systems and in the process generate distinct turbulent wakes. These wakes may interact with other nearby turbines, thereby influencing power generation, and have the potential to alter ecosystem processes such as flow regimes, sediment dynamics, and water quality. For the CEC industry to succeed, the interrelationship between the number, size, and location of installed CEC devices and their commensurate hydrodynamic and environmental effects must be characterized. This work verifies a model that simulates the hydrodynamic response of flow through and around CEC turbines. The tool facilitates virtual design of array layouts to optimize energy generation and minimize environmental effects. This study is based on modifications to an existing flow, sediment dynamics, and water-quality code (SNL-EFDC) where simulations of experimental flume data are used to quantify and visualize the influence of CEC on flow dynamics. Turbulence generation and breakdown and flow parameters are calibrated against wake data from two turbine-in-flume experiments to produce validated simulations of CEC. Considering the assumptions going into the model, results compare favorably and the model can be considered verified.

Noncohesive Sediment Transport Modeling with Multiple Size Classes

Contemporary three-dimensional sediment transport models are computationally expensive and thus a compromise must be struck between accurately modeling sediment transport and the number of effective size classes to represent in such a model. The Environmental Fluid Dynamics Code (EFDC) was used to model the experimental results of Yen and Lee who investigated sediment erosion and gradation around a 180-degree bend subject to transient flow. The EFDC model was first calibrated using the eight distinct size classes reported in the physical experiment to find the best erosion formulations to use. Once the best erosion formulations were ascertained, numerical simulations were carried out for each experimental run using a single effective particle size. Four techniques for evaluating the effective particle size were investigated. Each procedure yields comparable effective sizes, each within a factor of 1.5 of the others. Model results indicate that particle size as determined by the weighted critical shear velocity most faithfully reproduced the experimental results for erosion and deposition depths. Subsequently, model runs were conducted with different numbers of size classes to determine the optimal number that yields an accurate estimate for noncohesive sediment transport. Results from this study indicate that using three effective size classes to estimate the distribution of sediment sizes is optimum. In addition, when modeling only one non-cohesive size class, the best technique for calculating effective particle size is to use a weighted critical shear velocity.

Sandia National Laboratories environmental fluid dynamics code : pH effects user manual.

This document describes the implementation level changes in the source code and input files of Sandia National Laboratories Environmental Fluid Dynamics Code (SNL-EFDC) that are necessary for including pH effects into algae-growth dynamics. The document also gives a brief introduction to how pH effects are modeled into the algae-growth model. The document assumes that the reader is aware of the existing algae-growth model in SNL-EFDC. The existing model is described by James, Jarardhanam and more theoretical considerations behind modeling pH effects are presented therein. This document should be used in conjunction with the original EFDC manual and the original water-quality manual.

Fully Compositional and Thermal Reservoir Simulations Efficiently Compare EOR Techniques

Primary oil recovery methods in Saskatchewan’s heavy oil basin extract 5 to 10% of the available resource with the vast majority left in the ground and recoverable only through Enhanced Oil Recovery (EOR) methods. Traditional EOR generates steam in surface facilities and injects it underground to mobilize the oil for production with considerable energy losses inherent in the process. R.I.I. North America’s Solvent Thermal Resource Innovation Process (STRIP) technology moves the steam generator underground, reducing the operating and capital costs of a surface thermal production facility by 30% and 50% respectively, and saving more than 30% of the energy typically required for thermal production. STRIP technology combusts methane to produce in situ CO2 and steam. Because CO2 acts as a co-solvent, STRIP outperforms traditional steaminjection technology. This is demonstrated using a breakthrough modeling technique that couples fully compositional and thermal reservoir flow simulation capabilities. This new approach couples FlashPoint’s equation-of-state solver for the multiphase, multi-component, isothermal, isobaric flash problem, GFLASH, with Stanford’s Automatic Differentiation General Purpose Research Simulator for thermal reservoir flow simulations. This new computational framework exploits advanced techniques for skipping phase-identification computations and only uses exact phase equilibria from GFLASH when needed, reducing computational times by one to two orders of magnitude compared to the full rigorous solution.