Underground CO2 storage: demonstrating regulatory conformance by convergence of history-matched modeled and observed CO2 plume behavior using Sleipner time-lapse seismics

One of the three key regulatory requirements in Europe for transfer of storage site liability is to demonstrate conformity between predictive models of reservoir performance and monitoring observations. This is a challenging requirement because a perfect and unique match between observed and modeled behavior is near impossible to achieve. This study takes the time-lapse seismic monitoring data from the Sleipner storage operation to demonstrate that as more seismic data becomes available with time, predictive models can be matched more accurately to observations and become more reliable predictors of future performance. Six simple performance measures were defined: plume footprint area, maximum lateral migration distance of CO2 from the injection point, area of CO2 accumulation trapped at top reservoir, volume of CO2 accumulation trapped at top reservoir, area of all CO2 layers summed, and spreading co-efficient. Model scenarios were developed to predict plume migration up to 2008. Scenarios were developed for 1996 (baseline), 2001, and 2006 conditions, with models constrained by the information available at those times, and compared with monitoring datasets obtained up to 2008. The 1996 predictive range did generally encompass the future observed plume behavior, but with such a wide range of uncertainty as to render it of only marginal practical use. The 2001 predictions (which used the 1999 and 2001 seismic monitoring datasets) had a much lower uncertainty range, with the 2006 uncertainties somewhat lower again. There are still deficiencies in the actual quality of match but a robust convergence, with time, of predicted and observed models is clearly demonstrated. We propose modeling-monitoring convergence as a generic approach to demonstrating conformance

An experimental study of the flow of gas along synthetic faults of varying orientation to the stress field: implications for performance assessment of radioactive waste disposal

Critical stress theory states that fault transmissivity is strongly dependent upon orientation with respect to the stress tensor. This paper describes an experimental study aimed at verifying critical stress theory using a bespoke angled shear rig designed to examine the relationship between gas flows along a kaolinite-filled synthetic fault as a function of fault dip. A total of 22 gas injection experiments were conducted on faults oriented 0°, 15°, 30°, and 45° to horizontal; both with and without active shear. Gas flow was seen to be complex; repeat gas injection testing showed a consistent gas entry pressure but considerably different, nonrepeatable, gas peak or breakthrough pressure. Gas flow occurred along discrete, dilatant pathways. The physics governing the pressure at which these features formed was repeatable; however, permeability was dependent on the number, distribution, and geometry of the resultant pathways. The nonrepeatable gas response suggests that the number of pathways was dependent on very subtle variations in gouge properties. No fault orientations were seen to exhibit nonflow characteristics, although critical stress theory predicted that two of the investigated fault angles should be effective seals. However, a small variation in gas entry pressure was seen with fault angle as a result of varying normal and shear stress acting on the gouge material. Shear was seen to enhance gas movement by reducing gas entry pressure and increased permeability once gas became mobile. Therefore, in kaolinite gouge-filled faults, shear is not an effective self-sealing mechanism to gas flow

Theoretical Spectra and Atmospheres of Extrasolar Giant Planets

We present a comprehensive theory of the spectra and atmospheres of irradiated extrasolar giant planets. We explore the dependences on stellar type, orbital distance, cloud characteristics, planet mass, and surface gravity. Phase-averaged spectra for specific known extrasolar giant planets that span a wide range of the relevant parameters are calculated, plotted, and discussed. The connection between atmospheric composition and emergent spectrum is explored in detail. Furthermore, we calculate the effect of stellar insolation on brown dwarfs. We review a variety of representative observational techniques and programs for their potential for direct detection, in light of our theoretical expectations, and we calculate planet-to-star flux ratios as a function of wavelength. Our results suggest which spectral features are most diagnostic of giant planet atmospheres and reveal the best bands in which to image planets of whatever physical or orbital characteristics.Comment: 47 pages, plus 36 postscript figures; with minor revisions, accepted to the Astrophysical Journal, May 10, 2003 issu

Unzipping Kinetics of Double-Stranded DNA in a Nanopore

We studied the unzipping kinetics of single molecules of double-stranded DNA by pulling one of their two strands through a narrow protein pore. PCR analysis yielded the first direct proof of DNA unzipping in such a system. The time to unzip each molecule was inferred from the ionic current signature of DNA traversal. The distribution of times to unzip under various experimental conditions fit a simple kinetic model. Using this model, we estimated the enthalpy barriers to unzipping and the effective charge of a nucleotide in the pore, which was considerably smaller than previously assumed.Comment: 10 pages, 5 figures, Accepted: Physics Review Letter

Albedo and Reflection Spectra of Extrasolar Giant Planets

We generate theoretical albedo and reflection spectra for a full range of extrasolar giant planet (EGP) models, from Jovian to 51-Pegasi class objects. Our albedo modeling utilizes the latest atomic and molecular cross sections, a Mie theory treatment of extinction by condensates, a variety of particle size distributions, and an extension of the Feautrier radiative transfer method which allows for a general treatment of the scattering phase function. We find that due to qualitative similarities in the compositions and spectra of objects within each of five broad effective temperature ranges, it is natural to establish five representative EGP albedo classes: a ``Jovian'' class (T$_{\rm eff} \lesssim 150$ K; Class I) with tropospheric ammonia clouds, a ``water cloud'' class (T$_{\rm eff} \sim 250$ K; Class II) primarily affected by condensed H$_2$O, a ``clear'' class (T$_{\rm eff} \gtrsim 350$ K; Class III) which lacks clouds, and two high-temperature classes: Class IV (900 K $\lesssim$ T$_{\rm{eff}}$ $\lesssim$ 1500 K) for which alkali metal absorption predominates, and Class V (T$_{\rm{eff}}$ $\gtrsim$ 1500 K and/or low surface gravity ($\lesssim$ 10$^3$ cm s$^{-2}$)) for which a high silicate layer shields a significant fraction of the incident radiation from alkali metal and molecular absorption. The resonance lines of sodium and potassium are expected to be salient features in the reflection spectra of Class III, IV, and V objects. We derive Bond albedos and effective temperatures for the full set of known EGPs and explore the possible effects of non-equilibrium condensed products of photolysis above or within principal cloud decks. As in Jupiter, such species can lower the UV/blue albedo substantially, even if present in relatively small mixing ratios.Comment: revised LaTeX manuscript accepted to Ap.J.; also available at http://jupiter.as.arizona.edu/~burrows/paper

A Dynamic Knowledge Management Framework for the High Value Manufacturing Industry

Dynamic Knowledge Management (KM) is a combination of cultural and technological factors, including the cultural factors of people and their motivations, technological factors of content and infrastructure and, where these both come together, interface factors. In this paper a Dynamic KM framework is described in the context of employees being motivated to create profit for their company through product development in high value manufacturing. It is reported how the framework was discussed during a meeting of the collaborating company’s (BAE Systems) project stakeholders. Participants agreed the framework would have most benefit at the start of the product lifecycle before key decisions were made. The framework has been designed to support organisational learning and to reward employees that improve the position of the company in the market place

Energetic Selection of Topology in Ferredoxins

Models of early protein evolution posit the existence of short peptides that bound metals and ions and served as transporters, membranes or catalysts. The Cys-X-X-Cys-X-X-Cys heptapeptide located within bacterial ferredoxins, enclosing an Fe4S4 metal center, is an attractive candidate for such an early peptide. Ferredoxins are ancient proteins and the simple α+β fold is found alone or as a domain in larger proteins throughout all three kingdoms of life. Previous analyses of the heptapeptide conformation in experimentally determined ferredoxin structures revealed a pervasive right-handed topology, despite the fact that the Fe4S4 cluster is achiral. Conformational enumeration of a model CGGCGGC heptapeptide bound to a cubane iron-sulfur cluster indicates both left-handed and right-handed folds could exist and have comparable stabilities. However, only the natural ferredoxin topology provides a significant network of backbone-to-cluster hydrogen bonds that would stabilize the metal-peptide complex. The optimal peptide configuration (alternating αL,αR) is that of an α-sheet, providing an additional mechanism where oligomerization could stabilize the peptide and facilitate iron-sulfur cluster binding

Visualising biological data: a semantic approach to tool and database integration

<p>Abstract</p> <p>Motivation</p> <p>In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are <it>ad hoc </it>collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research.</p> <p>Methods</p> <p>To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.</p> <p>Results</p> <p>The toolkit, named Utopia, is freely available from <url>http://utopia.cs.man.ac.uk/</url>.</p

Positron-emission tomography–based staging reduces the prognostic impact of early disease progression in patients with follicular lymphoma

Background: Previous studies reported that early progression of disease (POD) after initial therapy predicted poor overall survival (OS) in patients with follicular lymphoma (FL). Here, we investigated whether pre-treatment imaging modality had an impact on prognostic significance of POD. Methods: In this retrospective study, we identified 1088 patients with grade I–IIIA FL; of whom, 238 patients with stage II–IV disease were initially treated with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP), and 346 patients were treated with rituximab-based chemotherapy. Patients (N = 484) from the FOLL05 study served as an independent validation cohort. We risk-stratified patients based on pre-treatment radiographic imaging (positron-emission tomography [PET] versus computed tomography [CT]) and early POD status using event-defining and landmark analyses. A competing risk analysis evaluated the association between early POD and histologic transformation. Results: In the discovery cohort, patients with POD within 24 months (PFS24) of initiating R-CHOP therapy had a 5-year OS of 57.6% for CT-staged patients compared with 70.6% for PET-staged patients. In the validation cohort, the 5-year OS for patients with early POD was 53.9% and 100% in CT- and PET-staged patients, respectively. The risk of histologic transformation in patients whose disease progressed within one year of initiating therapy was higher in CT-staged patients than in PET-staged patients (16.7% versus 6.3%, respectively), which was associated with a 9.7-fold higher risk of death. Conclusion: In FL, pre-treatment PET staging reduced the prognostic impact of early POD compared with CT staging. Patients with early POD and no histologic transformation have an extended OS with standard therapy

Variations in hydrological connectivity of Australian semiarid landscapes indicate abrupt changes in rainfall-use efficiency of vegetation

[1] Dryland vegetation frequently shows self‐organized spatial patterns as mosaic‐like structures of sources (bare areas) and sinks (vegetation patches) of water runoff and sediments with variable interconnection. Good examples are banded landscapes displayed by Mulga in semiarid Australia, where the spatial organization of vegetation optimizes the redistribution and use of water (and other scarce resources) at the landscape scale. Disturbances can disrupt the spatial distribution of vegetation causing a substantial loss of water by increasing landscape hydrological connectivity and consequently, affecting ecosystem function (e.g., decreasing the rainfall‐use efficiency of the landscape). We analyze (i) connectivity trends obtained from coupled analysis of remotely sensed vegetation patterns and terrain elevations in several Mulga landscapes subjected to different levels of disturbance, and (ii) the rainfall‐use efficiency of these landscapes, exploring the relationship between rainfall and remotely sensed Normalized Difference Vegetation Index. Our analyses indicate that small reductions in the fractional cover of vegetation near a particular threshold can cause abrupt changes in ecosystem function, driven by large nonlinear increases in the length of the connected flowpaths. In addition, simulations with simple vegetation‐thinning algorithms show that these nonlinear changes are especially sensitive to the type of disturbance, suggesting that the amount of alterations that an ecosystem can absorb and still remain functional largely depends on disturbance type. In fact, selective thinning of the vegetation patches from their edges can cause a higher impact on the landscape hydrological connectivity than spatially random disturbances. These results highlight surface connectivity patterns as practical indicators for monitoring landscape health