Increasing the quality of seismic interpretation

Acknowledgments E. Macrae was funded by an NERC Open CASE Ph.D. award (NE/F013728/1) with Midland Valley Exploration Ltd. as the industry partner. We thank 763 geoscientists for their participation, and in particular, the REs who gave their time freely to the project. M. Scott (University of Glasgow, UK) is thanked for assisting with the statistical analysis. Four reviewers are thanked for their constructive comments that improved the manuscript.Peer reviewedPublisher PD

Automated high accuracy, rapid beam hardening correction in X-Ray Computed Tomography of multi-mineral, heterogeneous core samples

X-ray Computed Tomography scanning is an innovative procedure that allows representing the internal structure of samples. Among its several purposes, X-ray CT is widely used for investigation of petrophysical properties of porous media. To provide accurate results, it is necessary to have high quality scan images, free of artefacts. One of the most problematic artefacts is beam hardening, which, in cylindrical shapes, increases the attenuation values with increasing distance from the centre. Until now, no automatic solution has been proposed for cylindrically-shaped cores that is both computationally feasible and applicable to all geological media. A new technique is here introduced for correcting beam hardening, using a linearization procedure of the beam hardening curve applied after the reconstruction process. We have developed an automated open source plug-in, running on ImageJ software, which does not require any a priori knowledge of the material, distance from the source or the scan conditions (current, energy), nor any segmentation of phases or calibration scan on phantom data. It is suitable for expert and non-expert use, alike. We have tested the technique on μCT scan images of a plastic rod, a sample of loose sand, several heterogeneous sandstone core samples (with near-cylindrical shapes), and finally, on an internal scan of a Berea sandstone core. The Berea core was also scanned using a medical X-ray CT scanner with a fan-beam geometry, as opposed to a cone beam geometry, showing that our algorithm is equally effective in both cases. Our correction technique successfully removes the beam hardening artefact in all cases, as well as removing the cupping effect common to internal scans. For a Berea Sandstone, with a porosity of 20%, porosity calculated using the corrected scan is 20.54%, which compares to a value of 14.24% using the software provided by the manufacturer

Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype phenotype correlations

We have generated a mouse carrying the human G551D mutation in the cystic fibrosis transmembrane conductance regulator gene (CFTR) by a one-step gene targeting procedure. These mutant mice show cystic fibrosis pathology but have a reduced risk of fatal intestinal blockage compared with 'null' mutants, in keeping with the reduced incidence of meconium ileus in G551D patients. The G551D mutant mice show greatly reduced CFTR-related chloride transport, displaying activity intermediate between that of cftr(mlUNC) replacement ('null') and cftr(mlHGU) insertional (residual activity) mutants and equivalent to approximately 4% of wild-type CFTR activity. The long-term survival of these animals should provide an excellent model with which to study cystic fibrosis, and they illustrate the value of mouse models carrying relevant mutations for examining genotype-phenotype correlations

A Data Science and Machine Learning Approach to Measure and Monitor Physical Activity in Children

Physical Activity is a fundamental component for the maintenance of a healthy lifestyle. Recommendations for physical activity levels are issued by most governments as part of public health measures. Therefore, it is vital for regulatory purposes, that there are reliable measurements of physical activity. However, the techniques and protocols used in existing physical activity research, including laboratory-based measurement, have received increasingly critical scrutiny in recent times. Consequently, physical activity researchers have begun to explore the use of wearable sensing technology to capture large amounts of data and the use of machine learning techniques, specifically artificial neural networks, to produce classifications for specific physical activity events. This paper explores this idea further and presents a supervised machine learning approach that utilises data obtained from accelerometer sensors worn by children in free-living environments. The paper posits a rigorous data science approach that presents a set of activities and features suitable for measuring physical activity in children in free-living environments. A Multilayer Perceptron neural network is used to classify physical activities by activity type, using ecologically valid data from body worn accelerometer sensors. A rigorous reproducible data science methodology is presented for subsequent use in physical activity research. Our results show that it was possible to obtain an overall accuracy of 92% using the initial data set, and 99.8% using interpolated cases

Do intraplate and plate boundary fault systems evolve in a similar way with repeated slip events?

As repeated slip events occur on a fault, energy is partly dissipated through rock fracturing and frictional processes in the fault zone and partly radiated to the surface as seismic energy. Numerous field studies have shown that the core of intraplate faults is wider on average with increasing total displacement (and hence slip events). In this study we compile data on the fault core thickness, total displacement and internal structure (e.g., fault core composition, host rock juxtaposition, slip direction, fault type, and/or the number of fault core strands) of plate boundary faults to compare to intraplate faults (within the interior of tectonic plates). Fault core thickness data show that plate boundary faults are anomalously narrow by comparison to intraplate faults and that they remain narrow regardless of how much total displacement they have experienced or the local structure of the fault. By examining the scaling relations between seismic moment, average displacement and surface rupture length for plate boundary and intraplate fault ruptures, we find that for a given value of displacement in an individual earthquake, plate boundary fault earthquakes typically have a greater seismic moment (and hence earthquake magnitude) than intraplate events. We infer that narrow plate boundary faults do not process intact rock as much during seismic events as intraplate faults. Thus, plate boundary faults dissipate less energy than intraplate faults during earthquakes meaning that for a given value of average displacement, more energy is radiated to the surface manifested as higher magnitude earthquakes. By contrast, intraplate faults dissipate more energy and get wider as fault slip increases, generating complex zones of damage in the surrounding rock and propagating through linkage with neighbouring structures. The more complex the fault geometry, the more energy has to be consumed at depth during an earthquake and the less energy reaches the surface

Simulating spatial and temporal evolution of multiple wing cracks around faults in crystalline basement rocks

Fault zones are structurally highly spatially heterogeneous and hence extremely complex. Observations of fluid flow through fault zones over several scales show that this structural complexity is reflected in the hydrogeological properties of faults. Information on faults at depth is scarce, hence, it is highly valuable to understand the controls on spatial and temporal fault zone development. In this paper we increase our understanding of fault damage zone development in crystalline rocks by dynamically simulating the growth of single and multiple splay fractures produced from failure on a pre-existing fault. We present a new simulation model, MOPEDZ (Modeling Of Permeability Evolution in the Damage Zone surrounding faults), that simulates fault evolution through solution of Navier's equation with a combined Mohr-Coulomb and tensile failure criteria. Simulations suggest that location, frequency, mode of failure and orientation of splay fractures are significantly affected both by the orientation of the fault with respect to the maximum principal compressive stress and the conditions of differential stress. Model predictions compare well with published field outcrop data, confirming that this model produces realistic damage zone geometries

Secondary school pupils' preferences for different types of structured grouping practices

The aim of this paper is to explore pupils’ preferences for particular types of grouping practices an area neglected in earlier research focusing on the personal and social outcomes of ability grouping. The sample comprised over 5,000 year 9 pupils (aged 13-14 years) in 45 mixed secondary comprehensive schools in England. The schools represented three levels of ability grouping in the lower school (years 7 to 9). Pupils responded to a questionnaire which explored the types of grouping that they preferred and the reasons for their choices. The majority of pupils preferred setting, although this was mediated by their set placement, type of school, socio-economic status and gender. The key reason given for this preference was that it enabled work to be matched to learning needs. The paper considers whether there are other ways of achieving this avoiding the negative social and personal outcomes of setting for some pupils

Comparison of Zn_{1-x}Mn_xTe/ZnTe multiple-quantum wells and quantum dots by below-bandgap photomodulated reflectivity

Large-area high density patterns of quantum dots with a diameter of 200 nm have been prepared from a series of four Zn_{0.93}Mn_{0.07}Te/ZnTe multiple quantum well structures of different well width (4 nm, 6 nm, 8 nm and 10 nm) by electron beam lithography followed by Ar+ ion beam etching. Below-bandgap photomodulated reflectivity spectra of the quantum dot samples and the parent heterostructures were then recorded at 10 K and the spectra were fitted to extract the linewidths and the energy positions of the excitonic transitions in each sample. The fitted results are compared to calculations of the transition energies in which the different strain states in the samples are taken into account. We show that the main effect of the nanofabrication process is a change in the strain state of the quantum dot samples compared to the parent heterostructures. The quantum dot pillars turn out to be freestanding, whereas the heterostructures are in a good approximation strained to the ZnTe lattice constant. The lateral size of the dots is such that extra confinement effects are not expected or observed.Comment: 23 pages, LaTeX2e (amsmath, epsfig), 7 EPS figure

Experimental evidence that livestock grazing intensity affects cyclic vole population regulation processes

Peer reviewedPublisher PD

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens