28 research outputs found

    An introduction to Marchenko methods for imaging

    Get PDF

    Subsurface seismic imaging in the presence of multiply scattered waves

    Get PDF
    The aim of seismic imaging is to produce maps indicative of spatial variations in properties of the Earth's subsurface. To create such images geophysicists use seismograms of energy measured over time by receivers at fixed observation points. These seismograms partially sample the seismic wavefield and are used to estimate the interactions between the seismic wavefield and the subsurface heterogeneity. However, because observation points are limited spatially the true interactions are unknown so approximations must be made to estimate these interactions. Conventional methods make the assumption that seismic waves observed in the seismograms reflect or diffract at most once from the subsurface heterogeneity (the so-called Born approximation). This assumption allows a low-wave-number smoothly varying estimate of the subsurface velocity structure to be used to back extrapolate the observed seismic wavefield to points inside the subsurface { producing an estimate of the subsurface seismic wavefield. However, this approximation can lead to inaccuracies when the seismograms contain energy that has reflected or diffracted more than once. In this thesis we create a suite of methods that offer a solution to this problem in a variety of scenarios. The majority of this thesis focuses on a set of novel techniques called Marchenko methods. These enable us to project seismograms to points in the subsurface - creating seismograms as though they had been measured at each subsurface point - while accounting for many of the complex, multiply-reflected seismic wave interactions that take place in the real Earth's subsurface. As a result images created using Marchenko imaging contain a reduction in artifacts that usually contaminate subsurface images due to multiply-reflected seismic waves. This thesis has four main aims which are addressed in consecutive chapters: (1) To introduce Marchenko methods with the minimum amount of mathematics required to understand how the methods iterate to a solution, and to provide a well-commented, easily editable MATLAB code package for demonstration and training purposes. (2) The second aim is to understand the application of Marchenko methods in a three-dimensional world, that is to say we investigate the implications of three-dimensional data, subsurface structures, wavefields and acquisition geometries on the results of Marchenko redatuming and imaging. (3) In a third set of results we aim to incorporate the additional wavefield sampling of vertical seismic profile (VSP) data (measured in boreholes in the Earth's subsurface) into Marchenko imaging with the emphasis being on improving imaging of vertical and near vertical subsurface interfaces. (4) The aim of the final set of results is to use multiply scattered (particularly duplex waves) as well as primary (singly scattered) waves to image the subsurface, again to improve imaging of vertical or near vertical interfaces but this time only using surface seismic data. Overall the results of this thesis demonstrate the effectiveness of Marchenko methods to redatum and image accurately when only low-wavenumber smoothly varying estimates of the subsurface velocity structure are available. We demonstrate the applicability of the methods to three-dimensional problems and a means to include VSP data into the method. Finally, we also redefine the conditions used to create subsurface images, allowing us to image using singly and multiply scattered seismic waves

    Marchenko Methods in a Three-dimensional World

    Get PDF
    ISSN:0956-540XISSN:1365-246

    3D Bayesian Variational Full Waveform Inversion

    Get PDF
    Seismic full-waveform inversion (FWI) provides high resolution images of the subsurface by exploiting information in the recorded seismic waveforms. This is achieved by solving a highly nonnlinear and nonunique inverse problem. Bayesian inference is therefore used to quantify uncertainties in the solution. Variational inference is a method that provides probabilistic, Bayesian solutions efficiently using optimization. The method has been applied to 2D FWI problems to produce full Bayesian posterior distributions. However, due to higher dimensionality and more expensive computational cost, the performance of the method in 3D FWI problems remains unknown. We apply three variational inference methods to 3D FWI and analyse their performance. Specifically we apply automatic differential variational inference (ADVI), Stein variational gradient descent (SVGD) and stochastic SVGD (sSVGD), to a 3D FWI problem, and compare their results and computational cost. The results show that ADVI is the most computationally efficient method but systematically underestimates the uncertainty. The method can therefore be used to provide relatively rapid but approximate insights into the subsurface together with a lower bound estimate of the uncertainty. SVGD demands the highest computational cost, and still produces biased results. In contrast, by including a randomized term in the SVGD dynamics, sSVGD becomes a Markov chain Monte Carlo method and provides the most accurate results at intermediate computational cost. We thus conclude that 3D variational full-waveform inversion is practically applicable, at least in small problems, and can be used to image the Earth's interior and to provide reasonable uncertainty estimates on those images

    Physician supply forecast: better than peering in a crystal ball?

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Anticipating physician supply to tackle future health challenges is a crucial but complex task for policy planners. A number of forecasting tools are available, but the methods, advantages and shortcomings of such tools are not straightforward and not always well appraised. Therefore this paper had two objectives: to present a typology of existing forecasting approaches and to analyse the methodology-related issues.</p> <p>Methods</p> <p>A literature review was carried out in electronic databases Medline-Ovid, Embase and ERIC. Concrete examples of planning experiences in various countries were analysed.</p> <p>Results</p> <p>Four main forecasting approaches were identified. The supply projection approach defines the necessary inflow to maintain or to reach in the future an arbitrary predefined level of service offer. The demand-based approach estimates the quantity of health care services used by the population in the future to project physician requirements. The needs-based approach involves defining and predicting health care deficits so that they can be addressed by an adequate workforce. Benchmarking health systems with similar populations and health profiles is the last approach. These different methods can be combined to perform a gap analysis. The methodological challenges of such projections are numerous: most often static models are used and their uncertainty is not assessed; valid and comprehensive data to feed into the models are often lacking; and a rapidly evolving environment affects the likelihood of projection scenarios. As a result, the internal and external validity of the projections included in our review appeared limited.</p> <p>Conclusion</p> <p>There is no single accepted approach to forecasting physician requirements. The value of projections lies in their utility in identifying the current and emerging trends to which policy-makers need to respond. A genuine gap analysis, an effective monitoring of key parameters and comprehensive workforce planning are key elements to improving the usefulness of physician supply projections.</p

    Oral versus intravenous antibiotics for bone and joint infection

    Get PDF
    BACKGROUND The management of complex orthopedic infections usually includes a prolonged course of intravenous antibiotic agents. We investigated whether oral antibiotic therapy is noninferior to intravenous antibiotic therapy for this indication. METHODS We enrolled adults who were being treated for bone or joint infection at 26 U.K. centers. Within 7 days after surgery (or, if the infection was being managed without surgery, within 7 days after the start of antibiotic treatment), participants were randomly assigned to receive either intravenous or oral antibiotics to complete the first 6 weeks of therapy. Follow-on oral antibiotics were permitted in both groups. The primary end point was definitive treatment failure within 1 year after randomization. In the analysis of the risk of the primary end point, the noninferiority margin was 7.5 percentage points. RESULTS Among the 1054 participants (527 in each group), end-point data were available for 1015 (96.3%). Treatment failure occurred in 74 of 506 participants (14.6%) in the intravenous group and 67 of 509 participants (13.2%) in the oral group. Missing end-point data (39 participants, 3.7%) were imputed. The intention-to-treat analysis showed a difference in the risk of definitive treatment failure (oral group vs. intravenous group) of −1.4 percentage points (90% confidence interval [CI], −4.9 to 2.2; 95% CI, −5.6 to 2.9), indicating noninferiority. Complete-case, per-protocol, and sensitivity analyses supported this result. The between-group difference in the incidence of serious adverse events was not significant (146 of 527 participants [27.7%] in the intravenous group and 138 of 527 [26.2%] in the oral group; P=0.58). Catheter complications, analyzed as a secondary end point, were more common in the intravenous group (9.4% vs. 1.0%). CONCLUSIONS Oral antibiotic therapy was noninferior to intravenous antibiotic therapy when used during the first 6 weeks for complex orthopedic infection, as assessed by treatment failure at 1 year. (Funded by the National Institute for Health Research; OVIVA Current Controlled Trials number, ISRCTN91566927. opens in new tab.

    SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

    Get PDF
    BACKGROUND: Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. METHODS: In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FINDINGS: Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. INTERPRETATION: The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. FUNDING: This study has been supported by ISARIC4C and PHOSP-COVID consortia. ISARIC4C is supported by grants from the National Institute for Health and Care Research and the Medical Research Council. Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research. The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research. The funders were not involved in the study design, interpretation of data or the writing of this manuscript
    corecore