Ocean Drilling Program Leg 176 deepened Hole 735B in gabbroic lower ocean crust by 1 km to 1.5 km. The section has the physical properties of seismic layer 3, and a total magnetization sufficient by itself to account for the overlying lineated sea-surface magnetic anomaly. The rocks from Hole 735B are principally olivine gabbro, with evidence for two principal and many secondary intrusive events. There are innumerable late small ferrogabbro intrusions, often associated with shear zones that cross-cut the olivine gabbros. The ferrogabbros dramatically increase upward in the section. Whereas there are many small patches of ferrogabbro representing late iron-and titanium-rich melt trapped intragranularly in olivine gabbro, most late melt was redistributed prior to complete solidification by compaction and deformation. This, rather than in situ upward differentiation of a large magma body, produced the principal igneous stratigraphy. The computed bulk composition of the hole is too evolved to mass balance mid-ocean ridge basalt back to a primary magma, and there must be a significant mass of missing primitive cumulates. These could lie either below the hole or out of the section. Possibly the gabbros were emplaced by along-axis intrusion of moderately differentiated melts into the near-transform environment. Alteration occurred in three stages. High-temperature granulite-to amphibolite-facies alteration is most important, coinciding with brittle^ductile deformation beneath the ridge. Minor greenschist-facies alteration occurred under largely static conditions, likely during block uplift at the ridge transform intersection. Late post-uplift lowtemperature alteration produced locally abundant smectite, often in previously unaltered areas. The most important features of the high-and low-temperature alteration are their respective associations with ductile and cataclastic deformation, and an overall decrease downhole with hydrothermal alteration generally 95% in the bottom kilometer. Hole 735B provides evidence for a strongly heterogeneous lower ocean crust, and for the inherent interplay of deformation, alteration and igneous processes at slow-spreading ridges. It is strikingly different from gabbros sampled from fast-spreading ridges and at most well-described ophiolite complexes. We attribute this to the remarkable diversity of tectonic environments where crustal accretion occurs in the oceans and to the low probability of a section of old slow-spread crust formed near a major large-offset transform being emplaced onland compared to sections of young crust from small ocean basins.

Glacigenic and fluvial deposits of variable lithological composition underlie many major cities in Europe and North America. Traditional geological mapping and 3D modelling techniques rarely capture this complexity as they use lithostratigraphic designations which are commonly based on genesis and age rather than lithological compositions.In urban areas, thousands of boreholes have been, and continue to be, drilled to facilitate the planning, design and construction of buildings and infrastructure. While these data may provide the basis for geological maps and 3D models based on lithological interpretation, they are too numerous for manual correlation to be undertaken efficiently. In this paper we explore the application of largely automated stochastic modelling techniques to develop predictive lithology models for glacial and fluvial deposits in the city of Glasgow, UK. These techniques are commonly used to assess facies variation in oilfield models and are applied here in an urban setting using over 4000 borehole records.Predictions derived from these methods have been evaluated by removing control data and rerunning the simulations. We demonstrate a moderate improvement in the prediction of lithology when using a lithologically-derived stochastic model compared with a conventionally interpolated lithostratigraphic model. It is possible to report uncertainty within the resulting models, either with probability maps or through a suite of plausible simulations of the lithologies across the study region. IntroductionThe growth and decay of high-and mid-latitude Pleistocene ice sheets has left 8% of the Earth's land surface, including one third of Europe and a quarter of North America, covered by glacigenic and fluvial deposits Gibbard, 2004a, 2004b). These deposits underlie many major cities and much of their associated infrastructure networks, and exert a significant influence on the groundwater system. Increasing urban development, and its demands (e.g. suitable foundation conditions, the need for waste storage, contaminant migration, drainage re-routing) requires that information about subsurface glacial deposits, which are often highly lithologically variable across short distances, is available for those involved in planning and construction (Campbell et al., 2010). A key challenge for the three-dimensional (3D) geological modelling community is therefore to represent these subsurface deposits in appropriate ways across large, city-wide areas (Culshaw, 2005;MacCormack et al., 2005;Kessler et al., 2009).In Glasgow, west central Scotland (Figure 1), the British Geological Survey (BGS), in partnership with Glasgow City Council and other local authorities, have used extensive borehole datasets to develop and successfully apply a suite of 3D Quaternary lithostratigraphic models (Merritt et al., 2007;Campbell et al., 2010) (Figure 2). A key strength of lithostratigraphic modelling is that it brings together the expertise of geologists and known geological relationships, enabling a geologically realistic r...

The move towards a lower carbon society is likely to lead to a greater utilisation of geothermal heat as the UK meets the challenge of its EU renewable obligation to source 15% of its energy from renewables by 2020. The shallow temperature field can

The growing importance of subsurface carbon storage for tackling anthropogenic carbon emissions requires new ideas to improve the rate and cost of carbon capture and storage (CCS) project development and implementation. We assess sandstones from the UK Geoenergy Observatories (UKGEOS) site in Glasgow, UK and the Wilmslow Sandstone Formation (WSF) in Cumbria, UK at the pore scale to indicate suitability for further assessment as CCS reservoirs. We measure porosity, permeability and other pore geometry characteristics using digital rock physics techniques on micro computed tomographic images of core material from each site. We find the Glasgow material to be unsuitable for CCS due to very little porosity—up to 1.65%—whereas the WSF material showed connected porosity up to 26.3% and permeabilities up to 6040 mD. Our results support the presence of a percolation threshold at 10% total porosity, introducing near full connectivity. We find total porosity varies with permeability with an exponent of 3.19. This provides reason to assume near full connectivity in sedimentary samples showing porosities above this threshold without the need for expensive and time consuming analyses.Supplementary material: Information about the boreholes sampled in this study, additional well logs of both boreholes and a summary of the supporting data plotted throughout this article from literature is available at https://doi.org/10.6084/m9.figshare.c.5260074.Thematic collection: This article is part of the Geoscience for CO2 storage collection available at: https://www.lyellcollection.org/cc/geoscience-for-co2-storage

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Abstract. Realistic representations of geological complexity are important to address several engineering and environmental challenges. The spatial distribution of properties controlling physical and geochemical processes can be effectively described by the geological structure of the subsurface. In this work, we present an approach to account for geological structure in geostatistical simulations of categorical variables. The approach is based on the extraction of information from a deterministic conceptualization of the subsurface, which is then used in the geostatistical analysis for the development of models of spatial correlation and as soft conditioning data. The approach was tested to simulate the distribution of four lithofacies in highly heterolithic Quaternary deposits. A transition probability-based stochastic model was implemented using hard borehole data and soft data extracted from a 3-D deterministic lithostratigraphic model. Simulated lithofacies distributions were also used as input in a flow model for numerical simulation of hydraulic head and groundwater flux. The outputs from these models were compared to corresponding values from models based exclusively on borehole data. Results show that soft lithostratigraphic information increases the accuracy and reduces the uncertainty of these predictions. The representation of the geological structure also allows a more precise definition of the spatial distribution of prediction uncertainty, here quantified with a metric based on Shannon information entropy. Correlations between prediction uncertainties for lithofacies, hydraulic heads and groundwater fluxes were also investigated. The results from this analysis provide useful insights about the incorporation of soft geological data into stochastic realizations of subsurface heterogeneity, and emphasize the critical importance of this type of information for reducing the uncertainty of simulations considering flux-dependent processes.3

An accurate and reliable description of the porosity–permeability relationship in geological materials is valuable in understanding subsurface fluid movement. This is important for reservoir characterisation, energy exploitation, geological carbon storage (GCS) and groundwater contamination and remediation. Whilst the relationship between pore characteristics and porosity and permeability are well examined, further investigation into the influence of grain characteristics on porosity and permeability would be beneficial due to the inherent relationship between grains and pores. This work aims to determine whether incorporation of grain characteristics into a porosity–permeability model is effective in constraining this relationship. Two fully digital approaches to individual 3D grain analysis based upon watershed segmentation are compared to determine the most effective, yet simple, workflow applicable to core plugs of significantly compacted grains. The identification of an effective segmentation workflow will facilitate future work on similarly complex materials, removing the need for traditional time-consuming and manual techniques. We use the most effective approach of measuring grain shape (sphericity) and size (Feret diameter) alongside an established fully digital workflow to measure porosity and permeability to investigate the impact of grain characteristics on porosity and permeability. We show that grain sphericity and porosity exhibit a positive relationship whereas no such relationship exists with grain size. Measurements of grain sphericity are applied to calculate a Kozeny–Carman (K–C) type porosity–permeability fit which was found to be unsatisfactory, compared to a simpler fit excluding any grain parameters. This is possibly due to the lower sphericity of the studied grains, deviating significantly from the K–C assumption that grains are entirely spherical. The simpler fit is most suitable for the studied materials, showing that inclusion of grain characteristics is not effective for better defining the porosity–permeability relationship in a K–C paradigm for these samples. This highlights the need for a model capable of considering a range of grain sphericities to further constrain the porosity–permeability relationship.