Faster convergence in seismic history matching by dividing and conquering the unknowns

The aim in reservoir management is to control field operations to maximize both the short and long term recovery of hydrocarbons. This often comprises continuous optimization based on reservoir simulation models when the significant unknown parameters have been updated by history matching where they are conditioned to all available data. However, history matching of what is usually a high dimensional problem requires expensive computer and commercial software resources. Many models are generated, particularly if there are interactions between the properties that update and their effects on the misfit that measures the difference between model predictions to observed data. In this work, a novel 'divide and conquer' approach is developed to the seismic history matching method which efficiently searches for the best values of uncertain parameters such as barrier transmissibilities, net:gross, and permeability by matching well and 4D seismic predictions to observed data. The ‘divide’ is carried by applying a second order polynomial regression analysis to identify independent sub-volumes of the parameters hyperspace. These are then ‘conquered’ by searching separately but simultaneously with an adapted version of the quasi-global stochastic neighbourhood algorithm. This 'divide and conquer' approach is applied to the seismic history matching of the Schiehallion field, located on the UK continental shelf. The field model, supplied by the operator, contained a large number of barriers that affect flow at different times during production, and their transmissibilities were largely unknown. There was also some uncertainty in the petrophysical parameters that controlled permeability and net:gross. Application of the method was accomplished because it is found that the misfit function could be successfully represented as sub-misfits each dependent on changes in a smaller number of parameters which then could be searched separately but simultaneously. Ultimately, the number of models required to find a good match reduced by an order of magnitude. Experimental design was used to contribute to the efficiency and the ‘divide and conquer’ approach was also able to separate the misfit on a spatial basis by using time-lapse seismic data in the misfit. The method has effectively gained a greater insight into the reservoir behaviour and has been able to predict flow more accurately with a very efficient 'divide and conquer' approach

Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity

In this paper we present a scalable approach for robustly computing a 3D surface mesh from multi-scale multi-view stereo point clouds that can handle extreme jumps of point density (in our experiments three orders of magnitude). The backbone of our approach is a combination of octree data partitioning, local Delaunay tetrahedralization and graph cut optimization. Graph cut optimization is used twice, once to extract surface hypotheses from local Delaunay tetrahedralizations and once to merge overlapping surface hypotheses even when the local tetrahedralizations do not share the same topology.This formulation allows us to obtain a constant memory consumption per sub-problem while at the same time retaining the density independent interpolation properties of the Delaunay-based optimization. On multiple public datasets, we demonstrate that our approach is highly competitive with the state-of-the-art in terms of accuracy, completeness and outlier resilience. Further, we demonstrate the multi-scale potential of our approach by processing a newly recorded dataset with 2 billion points and a point density variation of more than four orders of magnitude - requiring less than 9GB of RAM per process.Comment: This paper was accepted to the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. The copyright was transfered to IEEE (ieee.org). The official version of the paper will be made available on IEEE Xplore (R) (ieeexplore.ieee.org). This version of the paper also contains the supplementary material, which will not appear IEEE Xplore (R

Conquering the great divide: Rural mothers of children with chronic health conditions accessing specialist medical care for their children

© 2019 Australian College of Nursing Ltd Background: Globally, the number of children with chronic health conditions (CHCs) is increasing and mothers are mostly responsible for their care. Aim: Few studies have focused on rural mothers and their experiences of sourcing health care for their children who have CHCs. The purpose of this study was to explore these experiences. Method: Using a phenomenological approach, semi-structured interviews were conducted in early 2018. The Consolidated criteria for Reporting Qualitative research (COREQ) guidelines were followed. Sixteen rural mothers were interviewed regarding their experiences of accessing health care to provide optimal management of their children's CHC. Findings: Thematic analysis of resulting data revealed the overarching theme ‘Conquering the great divide’. From this overarching theme, four themes emerged. This paper focuses on the first theme, ‘Heading to the big smoke: access’. Discussion: Rural mothers felt challenged accessing health care for their children in the major cities whilst also maintaining routine family life back home. Conclusion: Understanding these rural women's experiences could assist health care professionals to develop strategies to facilitate rural mothers accessing services for their children with a CHC

Factors affecting hospice social work utilization among hospice patients: Focusing on place of care and economic status

Objective. Hospice social workers empower their patients and families as they journey through end of life. However, even when social work services are available, some hospice families choose not to use or fully utilize this service. Guided by the Anderson behavioral model, this study examined factors affecting utilization of hospice social work services with particular focus on two enabling factors - place of care and economic status. Method. Data came from the 2007 National Home and Hospice Care Survey. The sample was restricted to Medicare Hospice Benefit enrollees 65 years of age and older. Hospice social work utilization was categorized into six visit intervals (0= none, 5= more than two visits in a week). Bivariate and ordinal logistic regressions were used to examine associations between hospice social work utilization and 1) place of care (home vs. institution) and 2) economic status (low vs. not low). Results. The frequencies of hospice social work utilization were found to be significantly different between place of care (χ2(1)=92.86, p\u3c.001) and economic status (χ2(5)=11.28, p\u3c.05). Even after controlling for predisposing and need factors in ordinal logistic regressions, hospice patients receiving care at home (Coef.=-.58, p\u3c.001) and of low economic status (Coef.=-0.35, p\u3c.001) were found to use social work services less frequently than their counterparts. Discussion. This study adds to the limited body of literature on enabling factors associated with hospice social work utilization. Possible implications and suggestions aimed at addressing these disparities are discussed

Conquering nature and engaging with the environment in the Russian industrialised north

This dissertation explores perceptions of the environment and practices of interaction with natural environments at the Northern periphery of the Soviet Union/Russia as well as concepts of nature characteristic for the official Soviet discourse. In order to extract the rich natural resources of the North, numerous new industrial towns were founded from the ground up in areas with no previous permanent human settlements and were populated by migrants from all over the Soviet Union. The Soviet authorities motivated people to go to the North by material benefits but also by an intense ideological campaign with a rhetoric of ‘conquering nature’ and ‘mastering the North’. In this thesis, I argue that for an understanding of human-environment relations in the Russian industrialised Arctic, we need to combine two different analytical angles: the Soviet dominant discourse on nature and its transformation over time on one hand, and the lived experience of the implementers of Soviet industrialisation and their engagement with the natural world on the other hand. Therefore, I examine how people who were on the State’s mission to ‘master the North and nature’ came to feel a strong emotional attachment to and love for the Northern environments. Based on empirical materials from three industrial towns in the Murmansk region, I analyse how new Northerners combined both their involvement in the extractive approach to natural resources and their lived experience of dwelling in Northern environments. In the existing scope of social science scholarship on non-indigenous residents of the Russian North, studies of people’s engagement with the natural environment are usually separated from studies of the State’s strategies and discourses of nature. This study focuses on the so far understudied relations of the urban population of the Russian Arctic to their environment.This thesis bridges these gaps by innovatively combining the concept of ‘discourses of nature’(Macnaghten 1999) with the building and dwelling perspectives suggested by Tim Ingold (Ingold 2000), in analysing the dominant discourse on nature in the USSR and engagements with the natural environment of people working for extractive industries

Optimization of Time-Course Experiments for Kinetic Model Discrimination

Systems biology relies heavily on the construction of quantitative models of biochemical networks. These models must have predictive power to help unveiling the underlying molecular mechanisms of cellular physiology, but it is also paramount that they are consistent with the data resulting from key experiments. Often, it is possible to find several models that describe the data equally well, but provide significantly different quantitative predictions regarding particular variables of the network. In those cases, one is faced with a problem of model discrimination, the procedure of rejecting inappropriate models from a set of candidates in order to elect one as the best model to use for prediction

Spatial IQ Test for AI

We introduce SITD (Spatial IQ Test Dataset), a dataset used to evaluate the capabilities of computational models for pattern recognition and visual reasoning. SITD is a generator of images in the style of the Raven Progressive Matrices (RPM), a common IQ (Intelligence Quotient) test used to test analytical intelligence. RPMs are purely visual, and require little prior knowledge. RPM tests the users ability to derive abstract rules and patterns from a set of images. For the last 100 years, humans have evaluated intelligence us- ing standardized intelligence quotient exams. These tests examine different aspects of intelligence, including verbal, quantitative reasoning, and spatial reasoning ability. In the field of AI, there exists few intelligence established metrics beyond the Turing Test (TT) and the Total Turing Test (TTT). Thus, SITD makes for a useful dataset researchers can use to divide and conquer the task of creating ’intelligent’ machines.This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 123 1216

The Currency of Art: a collaboration between the Baring Archive and the Graduate School of CCW.

This publication arises from a collaborative project undertaken by The Baring Archive and the Graduate School of CCW (Camberwell College of Arts, Chelsea College of Art and Design and Wimbledon College of Art, three of the constituent colleges of University of the Arts London). In 1995, ING acquired the business of Barings plc, after Barings became insolvent as a result of unauthorized trading. Along with the acquisition of the company came a collection of archival material relating to the long history of Barings, whose origins stretch back to 1717 when John Baring of Bremen settled in Exeter and set up business as a merchant and manufacturer. In 1762, his three sons established the London merchant house of John & Francis Baring & Co., later known as Baring Brothers and, by the nineteenth century, the firm had expanded to become a leading financier for overseas governments and businesses. Documentation and objects relating to the illustrious history of the bank were augmented by portraits – eighteenth and nineteenth century paintings of the Baring family by leading practitioners of the period, such as Thomas Lawrence, Benjamin West, John Linnell, Ambrose McEvoy and William Orpen. From the 1970s onwards, a distinguished collection of water-colours was added to the historical archive, containing works by artists such as Paul Sandby, Francis Towne and David Cox, and Barings, with great discernment, had also accrued an impressive group of modern British artworks to hang on its office walls.Prunella Clough, L.S. Lowry, Paul Nash, Matthew Smith, Stanley Spencer, Keith Vaughan and Carel Weight are just a few of the artists represented. The Currency of Art is one outcome of a collaboration initiated with ING seven years ago. Staff and students from Wimbledon College of Art, and pupils from three of its neighbouring secondary schools, were invited to create new works in response to the painting collection which now hangs in ING’s offices at 60 London Wall. The staff, students and schoolchildren – diverse communities in themselves – brought fresh perspectives, distinct from those of financial historians or more traditional academics, to the collection. Residencies, symposia and workshops generated responses to the paintings, culminating in two exhibitions hosted by ING, re:MAKING and re:INVENTING, whereby the newly created works were hung alongside the originals that had inspired them. This represented an unusual opportunity, given the problems associated with conservation and stewardship that often inhibit such a combination