USGS Science⌕ Search

Geology topics

J. Browning

Publications and source records attributed to J. Browning.

4 recordsLinked to original sources
USGS2023

Climate change hotspots and implications for the global subsea telecommunications network

A global network of subsea telecommunications cables underpins our daily lives, enabling >95% of global digital data transfer, $trillions/day in financial trading, and providing critical communications links, particularly to remote, low-income countries. Despite their importance, subsea cables and their landing stations are vulnerable to damage by natural hazards, including storm surges, waves, cyclones, earthquakes, floods, volcanic eruptions , submarine landslides and ice scour. However, the likelihood or recurrence interval of many of these types of events will likely change under future projected climate change scenarios, compounded by sea-level rise; potentially increasing hazard severity, creating previously unanticipated hazards, or hazards may shift to new locations during the 20–30-year operational life of cable systems. To date, no study has assessed the wide-reaching impacts of future climate change on subsea cables and landing stations on a global scale. Here, for the first time we synthesize the current evidence base, based on published peer-reviewed datasets, to fill this crucial knowledge gap, specifically to assess how and where future climate change is likely to impact subsea cables and their shore-based infrastructure. We find that ocean conditions are highly likely to change on a global basis as a result of climate change, but the feedbacks and links between climate change, natural processes and human activities are often complicated, resulting in a high degree of geographic variability. We identify climate change ‘hotspots’ (regions and locations likely to experience the greatest impacts) but find that not all areas will be affected in the same manner, nor synchronously by the same processes. We conclude that cable routes should carefully consider locally-variable drivers of hazard frequency and magnitude. Consideration should be given both to instantaneous events (e.g. landslides, tropical cyclones) as well as longer-term, sustained impacts (e.g. seabed currents that circulate even in deep water). Multiple factors can combine to increase the risk posed to subsea cables, hence a holistic approach is essential to assess the compounded effects of both natural processes and human activities in the future.

Earth Science Reviews↗
USGS2018

KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 1: measurements, pressure dependence and pore-fluid effects

Measuring the permeability of tight rocks remains a challenging task. In addition to the traditional sources of errors that affect more permeable formations (e.g. sample selection, non-representative specimens, disturbance introduced during sample acquisition and preparation), tight rocks can be particularly prone to solid–fluid interactions and thus more sensitive to the methods, procedures and techniques used to measure permeability. To address this problem, it is desirable to collect, for a single material, measurements obtained by different methods and pore-fluids. For that purpose a collaborative benchmarking exercise involving 24 laboratories was organized for measuring the permeability of a single low permeability material, the Grimsel granodiorite, at a common effective confining pressure (5 MPa). The objectives of the benchmark were: (i) to compare the results for a given method, (ii) to compare the results between different methods, (iii) to analyze the accuracy of each method, (iv) to study the influence of experimental conditions (especially the nature of pore fluid), (v) to discuss the relevance of indirect methods and models and finally (vi) to suggest good practice for low permeability measurements. In total 39 measurements were collected that allowed us to discuss the influence of (i) pore-fluid, (ii) measurement method, (iii) sample size and (iv) pressure sensitivity. Discarding some outliers from the bulk data set (4 out of 39) an average permeability of 1.11 × 10 −18 m² with a standard deviation of 0.57 × 10 −18 m² was obtained. The most striking result was the large difference in permeability for gas measurements compared to liquid measurements. Regardless of the method used, gas permeability was higher than liquid permeability by a factor approximately 2 ( k gas = 1.28 × 10 −18 m² compared to k liquid = 0.65 × 10 −18 m²). Possible explanations are that (i) liquid permeability was underestimated due to fluid-rock interactions (ii) gas permeability was overestimated due to insufficient correction for gas slippage and/or (iii) gases and liquids do not probe exactly the same porous networks. The analysis of Knudsen numbers shows that the gas permeability measurements were performed in conditions for which the Klinkenberg correction is sufficient. Smaller samples had a larger scatter of permeability values, suggesting that their volume were below the Representative Elementary Volume. The pressure dependence of permeability was studied by some of the participating teams in the range 1–30 MPa and could be fitted to an exponential law k = k o .exp(– γP eff ) with γ = 0.093 MPa −1 . Good practice rules for measuring permeability in tight materials are also provided.

Geophysical Journal International↗
USGS2018

KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 2: modeling, microstructures and complementary data

Measuring and modelling the permeability of tight rocks remains a challenging task. In addition to the traditional sources of errors that affect more permeable formations (e.g. sample selection, non-representative specimens, disturbance introduced during sample acquisition and preparation), tight rocks can be particularly prone to solid–fluid interactions and thus more sensitive to the methods, procedures and techniques used to measure permeability. To address this problem, it is desirable to collect, for a single material, measurements obtained by different methods and pore fluids. For that purpose, a benchmarking exercise involving 24 laboratories was organized for measuring and modelling the permeability of a single low-permeability material, the Grimsel granodiorite. The objectives of the benchmark were: (i) to compare the results for a given method, (ii) to compare the results between different methods, (iii) to analyse the accuracy of each method, (iv) to study the influence of experimental conditions (especially the nature of pore fluid), (v) to discuss the relevance of indirect methods and models and finally (vi) to suggest good practice for low-permeability measurements. To complement the data set of permeability measurements presented in a companion paper, we focus here on (i) quantitative analysis of microstructures and pore size distribution, (ii) permeability modelling and (iii) complementary measurements of permeability anisotropy and poroelastic parameters. Broad ion beam—scanning electron microscopy, micro-computerized tomography, mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) methods were used to characterize the microstructures and provided the input parameters for permeability modelling. Several models were used: (i) basic statistical models, (ii) 3-D pore network and effective medium models, (iii) percolation model using MICP data and (iv) free-fluid model using NMR data. The models were generally successful in predicting the actual range of measured permeability. Statistical models overestimate the permeability because they do not adequately account for the heterogeneity of the crack network. Pore network and effective medium models provide additional constraints on crack parameters such as aspect ratio, aperture, density and connectivity. MICP and advanced microscopy techniques are very useful tools providing important input data for permeability estimation. Permeability measured—orthogonal to foliation is lower that—parallel to foliation. Combining the experimental and modelling results provide a unique and rich data set.

Geophysical Journal International↗