Towards an integrated restoration/forward geomechanical modelling workflow for basin evolution prediction

Many sedimentary basins host important reserves of exploitable energy resources. Understanding of the present-day state of stresses, porosity, overpressure and geometric configuration is essential in order to minimize production costs and enhance safety in operations. The data that can be measured from the field is, however, limited and at a non-optimal resolution. Structural restoration (inverse modelling of past deformation) is often used to validate structural interpretations from seismic data. In addition, it provides the undeformed state of the basin, which is a pre-requisite to understanding fluid migration or to perform forward simulations. Here, we present a workflow that integrates geomechanical-based structural restoration and forward geomechanical modelling in a finite element framework. The geometry and the boundary kinematics derived from restoration are used to automatically create a forward geomechanical model. Iterative correction may then be performed by either modifying the assumptions of the restoration or modifying the restoration-derived boundary conditions in the forward model. The methodology is applied to two problems; firstly, a sand-box scale benchmark model consisting of sand sediments sliding on silicon leading to the formation of a graben structure; secondly, a field-scale thrust-related anticline from Niger Delta. Two strategies to provide further constraint on fault development in the restoration-derived forward simulation are also presented. It is shown that the workflow reproduces the first order structural features observed in the target geometry. Furthermore, it is demonstrated that the iterative approach provides improved understanding of the evolution and additional information of current-day stress and material state for the Niger Delta Case

Epidemiology of SARS-CoV-2 infection among staff and students in a cohort of English primary and secondary schools during 2020–2021

BACKGROUND: There remains uncertainty about the epidemiology of SARS-CoV-2 among school students and staff and the extent to which non-pharmaceutical-interventions reduce the risk of school settings. METHODS: We conducted an open cohort study in a sample of 59 primary and 97 secondary schools in 15 English local authority areas that were implementing government guidance to schools open during the pandemic. We estimated SARS-CoV-2 infection prevalence among those attending school, antibody prevalence, and antibody negative to positive conversion rates in staff and students over the school year (November 2020–July 2021). FINDINGS: 22,585 staff and students participated. SARS-CoV-2 infection prevalence among those attending school was highest during the first two rounds of testing in the autumn term, ranging from 0.7% (95% CI 0.2, 1.2) among primary staff in November 2020 to 1.6% (95% CI 0.9, 2.3) among secondary staff in December 2020. Antibody conversion rates were highest in the autumn term. Infection patterns were similar between staff and students, and between primary and secondary schools. The prevalence of nucleoprotein antibodies increased over the year and was lower among students than staff. SARS-CoV-2 infection prevalence in the North-West region was lower among secondary students attending school on normal school days than the regional estimate for secondary school-age children. INTERPRETATION: SARS-CoV-2 infection prevalence in staff and students attending school varied with local community infection rates. Non-pharmaceutical interventions intended to prevent infected individuals attending school may have partially reduced the prevalence of infection among those on the school site. FUNDING: UK Department of Health and Social Care