Chemo-mechanical coupling in kerogen gas adsorption/desorption.

Kerogen plays a central role in hydrocarbon generation in an oil/gas reservoir. In a subsurface environment, kerogen is constantly subjected to stress confinement or relaxation. The interplay between mechanical deformation and gas adsorption of the materials could be an important process for shale gas production but unfortunately is poorly understood. Using a hybrid Monte Carlo/molecular dynamics simulation, we show here that a strong chemo-mechanical coupling may exist between gas adsorption and mechanical strain of a kerogen matrix. The results indicate that the kerogen volume can expand by up to 5.4% and 11% upon CH4 and CO2 adsorption at 192 atm, respectively. The kerogen volume increases with gas pressure and eventually approaches a plateau as the kerogen becomes saturated. The volume expansion appears to quadratically increase with the amount of gas adsorbed, indicating a critical role of the surface layer of gas adsorbed in the bulk strain of the material. Furthermore, gas uptake is greatly enhanced by kerogen swelling. Swelling also increases the surface area, porosity, and pore size of kerogen. Our results illustrate the dynamic nature of kerogen, thus questioning the validity of the current assumption of a rigid kerogen molecular structure in the estimation of gas-in-place for a shale gas reservoir or gas storage capacity for subsurface carbon sequestration. The coupling between gas adsorption and kerogen matrix deformation should be taken into consideration.

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study.

BACKGROUND: Progressive optic nerve damage in glaucoma results in vision loss, quantifiable with visual field (VF) testing. VF measurements are, however, highly variable, making identification of worsening vision ('progression') challenging. Glaucomatous optic nerve damage can also be measured with imaging techniques such as optical coherence tomography (OCT). OBJECTIVE: To compare statistical methods that combine VF and OCT data with VF-only methods to establish whether or not these allow (1) more rapid identification of glaucoma progression and (2) shorter or smaller clinical trials. DESIGN: Method 'hit rate' (related to sensitivity) was evaluated in subsets of the United Kingdom Glaucoma Treatment Study (UKGTS) and specificity was evaluated in 72 stable glaucoma patients who had 11 VF and OCT tests within 3 months (the RAPID data set). The reference progression detection method was based on Guided Progression Analysis™ (GPA) Software (Carl Zeiss Meditec Inc., Dublin, CA, USA). Index methods were based on previously described approaches [Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS), Permutation analyses Of Pointwise Linear Regression (PoPLR) and structure-guided ANSWERS (sANSWERS)] or newly developed methods based on Permutation Test (PERM), multivariate hierarchical models with multiple imputation for censored values (MaHMIC) and multivariate generalised estimating equations with multiple imputation for censored values (MaGIC). SETTING: Ten university and general ophthalmology units (UKGTS) and a single university ophthalmology unit (RAPID). PARTICIPANTS: UKGTS participants were newly diagnosed glaucoma patients randomised to intraocular pressure-lowering drops or placebo. RAPID participants had glaucomatous VF loss, were on treatment and were clinically stable. INTERVENTIONS: 24-2 VF tests with the Humphrey Field Analyzer and optic nerve imaging with time-domain (TD) Stratus OCT™ (Carl Zeiss Meditec Inc., Dublin, CA, USA). MAIN OUTCOME MEASURES: Criterion hit rate and specificity, time to progression, future VF prediction error, proportion progressing in UKGTS treatment groups, hazard ratios (HRs) and study sample size. RESULTS: Criterion specificity was 95% for all tests; the hit rate was 22.2% for GPA, 41.6% for PoPLR, 53.8% for ANSWERS and 61.3% for sANSWERS (all comparisons p ≤ 0.042). Mean survival time (weeks) was 93.6 for GPA, 82.5 for PoPLR, 72.0 for ANSWERS and 69.1 for sANSWERS. The median prediction errors (decibels) when the initial trend was used to predict the final VF were 3.8 (5th to 95th percentile 1.7 to 7.6) for PoPLR, 3.0 (5th to 95th percentile 1.5 to 5.7) for ANSWERS and 2.3 (5th to 95th percentile 1.3 to 4.5) for sANSWERS. HRs were 0.57 [95% confidence interval (CI) 0.34 to 0.90; p = 0.016] for GPA, 0.59 (95% CI 0.42 to 0.83; p = 0.002) for PoPLR, 0.76 (95% CI 0.56 to 1.02; p = 0.065) for ANSWERS and 0.70 (95% CI 0.53 to 0.93; p = 0.012) for sANSWERS. Sample size estimates were not reduced using methods including OCT data. PERM hit rates were between 8.3% and 17.4%. Treatment effects were non-significant in MaHMIC and MaGIC analyses; statistical significance was altered little by incorporating imaging. LIMITATIONS: TD OCT is less precise than current imaging technology; current OCT technology would likely perform better. The size of the RAPID data set limited the precision of criterion specificity estimates. CONCLUSIONS: The sANSWERS method combining VF and OCT data had a higher hit rate and identified progression more quickly than the reference and other VF-only methods, and produced more accurate estimates of the progression rate, but did not increase treatment effect statistical significance. Similar studies with current OCT technology need to be undertaken and the statistical methods need refinement. TRIAL REGISTRATION: Current Controlled Trials ISRCTN96423140. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 4. See the NIHR Journals Library website for further project information. Data analysed in the study were from the UKGTS. Funding for the UKGTS was provided through an unrestricted investigator-initiated research grant from Pfizer Inc. (New York, NY, USA), with supplementary funding from the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Imaging equipment loans were made by Heidelberg Engineering, Carl Zeiss Meditec and Optovue (Fremont, CA, USA). Pfizer, Heidelberg Engineering, Carl Zeiss Meditec and Optovue had no input into the design, conduct, analysis or reporting of any of the UKGTS findings or this work. The sponsor for both the UKGTS and RAPID data collection was Moorfields Eye Hospital NHS Foundation Trust. David F Garway-Heath, Tuan-Anh Ho and Haogang Zhu are partly funded by the NIHR Biomedical Research Centre based at Moorfields Eye Hospital and UCL Institute of Ophthalmology. David F Garway-Heath's chair at University College London (UCL) is supported by funding from the International Glaucoma Association.

Atomistic Structure of Mineral Nano-aggregates from Simulated Compaction and Dewatering.

The porosity of clay aggregates is an important property governing chemical reactions and fluid flow in low-permeability geologic formations and clay-based engineered barrier systems. Pore spaces in clays include interlayer and interparticle pores. Under compaction and dewatering, the size and geometry of such pore spaces may vary significantly (sub-nanometer to microns) depending on ambient physical and chemical conditions. Here we report a molecular dynamics simulation method to construct a complex and realistic clay-like nanoparticle aggregate with interparticle pores and grain boundaries. The model structure is then used to investigate the effect of dewatering and water content on micro-porosity of the aggregates. The results suggest that slow dewatering would create more compact aggregates compared to fast dewatering. Furthermore, the amount of water present in the aggregates strongly affects the particle-particle interactions and hence the aggregate structure. Detailed analyses of particle-particle and water-particle interactions provide a molecular-scale view of porosity and texture development of the aggregates. The simulation method developed here may also aid in modeling the synthesis of nanostructured materials through self-assembly of nanoparticles.

Density Fluctuation in Aqueous Solutions and Molecular Origin of Salting-Out Effect for CO2.

Using molecular dynamics simulation, we studied the density fluctuations and cavity formation probabilities in aqueous solutions and their effect on the hydration of CO2. With increasing salt concentration, we report an increased probability of observing a larger than the average number of species in the probe volume. Our energetic analyses indicate that the van der Waals and electrostatic interactions between CO2 and aqueous solutions become more favorable with increasing salt concentration, favoring the solubility of CO2 (salting in). However, due to the decreasing number of cavities forming when salt concentration is increased, the solubility of CO2 decreases. The formation of cavities was found to be the primary control on the dissolution of gas, and is responsible for the observed CO2 salting-out effect. Our results provide the fundamental understanding of the density fluctuation in aqueous solutions and the molecular origin of the salting-out effect for real gas.

Nanostructural control of methane release in kerogen and its implications to wellbore production decline.

Despite massive success of shale gas production in the US in the last few decades there are still major concerns with the steep decline in wellbore production and the large uncertainty in a long-term projection of decline curves. A reliable projection must rely on a mechanistic understanding of methane release in shale matrix-a limiting step in shale gas extraction. Using molecular simulations, we here show that methane release in nanoporous kerogen matrix is characterized by fast release of pressurized free gas (accounting for ~30-47% recovery) followed by slow release of adsorbed gas as the gas pressure decreases. The first stage is driven by the gas pressure gradient while the second stage is controlled by gas desorption and diffusion. We further show that diffusion of all methane in nanoporous kerogen behaves differently from the bulk phase, with much smaller diffusion coefficients. The MD simulations also indicate that a significant fraction (3-35%) of methane deposited in kerogen can potentially become trapped in isolated nanopores and thus not recoverable. Our results shed a new light on mechanistic understanding gas release and production decline in unconventional reservoirs. The long-term production decline appears controlled by the second stage of gas release.

Liquid water can slip on a hydrophilic surface.

Understanding and predicting the behavior of water, especially in contact with various surfaces, is a scientific challenge. Molecular-level understanding of hydrophobic effects and their macroscopic consequences, in particular, is critical to many applications. Macroscopically, a surface is classified as hydrophilic or hydrophobic depending on the contact angle formed by a water droplet. Because hydrophobic surfaces tend to cause water slip whereas hydrophilic ones do not, the former surfaces can yield self-cleaning garments and ice-repellent materials whereas the latter cannot. The results presented herein suggest that this dichotomy might be purely coincidental. Our simulation results demonstrate that hydrophilic surfaces can show features typically associated with hydrophobicity, namely liquid water slip. Further analysis provides details on the molecular mechanism responsible for this surprising result.