Kopplung von Modellen unterschiedlicher Komplexität zur Simulation der CO2-Speicherung in tiefen salinaren Aquiferen

Modeling carbon dioxide (CO2) storage in saline aquifers on a reservoir scale is very demanding with respect to computational cost. In realistic scenarios, large heterogeneous geometries need to be described. In addition, the governing physical processes are very complex. The models need to take into account non-isothermal, multiphase-multicomponent flow and transport processes, as well as geomechanical processes, that occur during CO2 storage. However, in most cases it is not necessary to describe all physical processes for the whole simulation time and in the entire model domain. The processes which dominate during CO2 storage operations vary in time and space. This allows to use models of reduced or adapted complexity for the description of the dominant processes within a certain time period or subdomain. In this work a spatial and a sequential model coupling concept for CO2 storage simulation are developed and investigated with respect to efficiency increase and coupling errors. It can be shown that by applying these models of reduced or adapted complexity, the model efficiency can be increased without neglecting the relevant phenomena.Für die Realisierung großskaliger CO2-Speicherprojekte ist die Verfügbarkeit effizienter Simulationsprogramme zur Beschreibung der physikalischen Prozesse im Untergrund während und nach der CO2 Injektion unabdingbar. In der Planungsphase werden Simulationsprogramme für die Bestimmung geeigneter geologischer Speicherformationen und für die Abschätzung der verfügbaren Speicherkapazität benötigt. Außerdem dienen sie der Durchführung von Risikoanalysen und Machbarkeitsstudien. Während und nach der Injektionsphase helfen numerische Modelle bei der Optimierung der Injektionsabläufe und beim Aufbau eines effizienten Monitoringsystems. Die zum Einsatz kommenden Simulationswerkzeuge müssen in der Lage sein komplexe physikalische Prozesse abzubilden. Abgesehen von den nichtisothermen Strömungsprozessen der Porenfluide CO2 und Salzwasser, spielen durch die gegenseitige Löslichkeit von CO2 und Salzwasser auch Transportprozesse innerhalb der Fluidphasen eine Rolle. Außerdem kann es infolge des durch die CO2 Injektion verursachten Druckanstiegs zu geomechanischen Deformationen der Gesteinsmatrix kommen. Auch geochemische Prozesse können eine Rolle spielen, da das im Formationswasser gelöste CO2 zu einer Änderung des pH-Werts führt und mit den vorhandenen Gelöststoffen und der Feststoffmatrix neue chemische Verbindungen eingehen kann. Zusätzlich zur Komplexität der beteiligten Prozesse müssen für die Simulation von CO2-Speicherprojekten häufig große Zeit- und Raumskalen betrachtet werden. Eine Untersuchung der großskaligen Druckausbreitung und den damit verbundenen Konsequenzen für anderweitige Nutzungen des Untergrunds, wie Grundwassergewinnung, Geothermie oder Energiespeicherung, erfordert beispielsweise Modellgebiete mit einer lateralen Ausdehnung von bis zu 100 km. Das Langzeitverhalten des injizierten CO2, das für die Untersuchung der Speichersicherheit und Speicherkapazität eine Rolle spielt, kann sich auf Zeitskalen von bis zu mehreren tausend Jahren abspielen. Im Allgemeinen steigt die Rechenzeit mit der Modellkomplexität und der Größe der beschriebenen Zeit- und Raumskalen. Es zeigt sich allerdings, dass die Komplexität der beteiligten Prozesse bei der CO2 Speicherung sowohl zeitlich als auch räumlich variiert. Dies motiviert die Entwicklung und Anwendung von gekoppelten Modellen, die einzelne, spezialisierte Teilmodelle entsprechend der zeitlich und/oder räumlich erforderliche physikalischen Komplexität kombinieren. In dieser Arbeit werden zwei Arten von Modellkopplungen beschrieben, die sequentielle (zeitliche) und die räumlich Modellkopplung. Die sequentielle Kopplung wird zur Beschreibung des Langzeitverhaltens herangezogen. Hier liegt der Fokus auf der Beschreibung der nichtisothermen Strömungs- und Transportprozesse. Die räumliche Modellkopplung wird in dieser Arbeit für die Untersuchung der großskaligen Druckentwicklung unter Berücksichtigung linear elastischer geomechanischer Prozesse eingeführt. Sowohl die sequentielle als auch die räumliche Modellkopplung bietet folglich eine Möglichkeit die Effizienz der Modelle zu steigern, ohne dass relevante Prozesse vernachlässigt werden. Die Kopplungsfehler sind in den meisten der in dieser Arbeit untersuchten Testfälle gering

Simulating seismic chimney structures as potential vertical migration pathways for CO2 in the Snøhvit area, SW Barents Sea: model challenges and outcomes

Carbon capture and storage (CCS) activities at the Snøhvit field, Barents Sea, will involve carrying out an analysis to determine which parameters affect the migration process of CO2 from the gas reservoir, to what degree they do so and how sensitive these parameters are to any changes. This analysis will aim to evaluate the effects of applying a broad but realistic range of reservoir, fault and gas chimney properties on potential CO2 leakage at various depths throughout the subsurface. Fluid flow might take place through parts of or the entire extent of the overburden. One of the aims of the analysis is assessing the potential of CO2 reaching the seabed. Using the Snøhvit gas reservoir and overburden in the Barents Sea, a series of geological models were built using seismic and well-log data. We then performed numerical simulations of CO2 migration in focused fluid flow structures. Identification of potential migration pathways and their extent, such as gas chimneys and faults, and their incorporation into these models and simulations will provide a realistic insight into the migration potential of CO2. In the simulations the CO2 is injected over a 20 year period at a rate of 0.7 Mt/year and migration is allowed to take place over a 2000 year time frame for domains of approximately 21 km2 for the caprock fault models, 24 km2 for the realistic gas chimney models and 35 km2 for the generic gas chimney models, in a layered sedimentary succession. The total mass of CO2 injected in the reservoir during the 20-year injection period is 14 Mt. There is a strong interaction between the various parameters but the parameter that had the most influence on the CO2 migration process was probably the permeability of the reservoirs, especially the average permeability (k). Also, for the faulted caprock scenarios, it should be noted that at near surface depths the permeability of 765 mD is already adequate for a good CO2 flow. At the chimney top level (600 m) however, a further increase in permeability has an additional effect on improving CO2 flow. Overall, considering the slow upward migration velocity of the plume, this geological setup can be regarded as a suitable storage site

A benchmark study on problems related to CO₂ storage in geologic formations:SSummary and discussion of the results

International audienceThis paper summarises the results of a benchmark study that compares a number of mathematical and numerical models applied to specific problems in the context of carbon dioxide (CO2) storage in geologic formations. The processes modelled comprise advective multi-phase flow, compositional effects due to dissolution of CO2 into the ambient brine and non-isothermal effects due to temperature gradients and the Joule–Thompson effect. The problems deal with leakage through a leaky well, methane recovery enhanced by CO2 injection and a reservoir-scale injection scenario into a heterogeneous formation. We give a description of the benchmark problems then briefly introduce the participating codes and finally present and discuss the results of the benchmark study

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease