{"id":26638,"date":"2019-12-09T13:17:38","date_gmt":"2020-04-16T13:46:59","guid":{"rendered":"https:\/\/www.bgs.ac.uk\/?post_type=research_project&#038;p=26638"},"modified":"2020-08-28T09:03:45","modified_gmt":"2020-08-28T09:03:45","slug":"theory","status":"publish","type":"research_project","link":"https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/theory\/","title":{"rendered":"Theory"},"content":{"rendered":"\t\t\t<section class=\"hero-section hero-section-with-social\">\n\t\t\t\t\t\t\t\t<div class=\"hero-info-wrap\">\n\t\t\t\t\t<div class=\"container\">\n\t\t\t\t\t\t<div class=\"row\">\n\t\t\t\t\t\t\t<div class=\"col-12\">\n\t\t\t\t\t\t\t\t<div class=\"hero-info\">\n\t\t\t\t\t\t\t\t\t<h1>Theory<\/h1>\n\t\t\t\t\t\t\t\t\t<p>BGS Research &mdash; Geophysical tomography<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"social-wrap social-wrap-inline-them\">\n\t\t\t\t<div class=\"sea-background-f\">\n\t\t\t\t\t<span>Share this article<\/span><a target=\"_blank\"  href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/theory\/\"><span class=\"icon-facebook\"><span class=\"hidden\">Facebook<\/span><\/span><\/a><a target=\"_blank\"  href=\"https:\/\/twitter.com\/intent\/tweet?text=Theory&#038;url=https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/theory\/\"><span class=\"icon-twitter\"><span class=\"hidden\">Twitter<\/span><\/span><\/a><a   onclick=\"javascript:void( (function() {var e=document.createElement('script' );e.setAttribute('type','text\/javascript' );e.setAttribute('charset','UTF-8' );e.setAttribute('src','\/\/assets.pinterest.com\/js\/pinmarklet.js?r='+Math.random()*99999999);document.body.appendChild(e)})());\"  href=\"javascript:void(0);\"><span class=\"icon-pinterest\"><span class=\"hidden\">Pinterest<\/span><\/span><\/a><a target=\"_blank\"  href=\"https:\/\/wa.me?text=https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/theory\/\"><span class=\"icon-whatsapp\"><span class=\"hidden\">WhatsApp<\/span><\/span><\/a><a   href=\"mailto:?subject=Theory&#038;body=The%20team%20%20are%20actively%20researching%20and%20developing%20new%20modelling%20and%20data%20analysis%20methods%20in%20geophysical%20tomography.%20(https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/theory\/)\"><span class=\"icon-mail\"><span class=\"hidden\">Email<\/span><\/span><\/a><a href=\"#\" data-copy=\"https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/theory\/\" class=\"copy-url-on-click\"><span class=\"icon-link\"><span class=\"hidden\">Copy Link<\/span><\/span><\/a><\/div><\/div>\t\t\t\t\t\t\t<\/section>\n\t\t\t\n\n\n<section class=\"wp-block-bgs-blocks-content-container content-section\"><div class=\"container\"><div class=\"row\"><div class=\"col-12\">\n<p><a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/\">BGS Geophysical Tomography<\/a> (GTom) has analytical and numerical expertise in all aspects of geoelectrical theory and data processing. We are actively researching and developing new modelling and data analysis methods. Recent advances in acquisition, reconstruction and analysis include:<\/p>\n\n\n\n<ul><li>optimal survey design to maximise image information content<\/li><li>adaptive acquisition strategies for time-lapse monitoring applications<\/li><li>automated segmentation and clustering for image analysis<\/li><li>joint analysis of geoelectrical and seismic imaging data <\/li><\/ul>\n\n\n<figure  class=\"img-wrap\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/theory_graphic-150x150.jpg\" class=\"lazy-blur\" alt=\"Geographical tomography theory equation\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/theory_graphic.jpg\" \/><\/figure>\n\n\n<p>We have also developed inversion strategies to extract electrode movements from geoelectrical monitoring data, which reduces or eliminates image distortion for applications on unstable ground and enables the electrode grids to act as distributed motion sensors.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Quick links<\/strong><\/h3>\n\n\n\n<ul><li><a href=\"#optimised\">Optimised survey design and image reconstruction<\/a><\/li><li><a href=\"#adaptive\">Adaptive monitoring<\/a><\/li><li><a href=\"#EMT\">Electrode movement tracking<\/a><\/li><li><a href=\"#automated\">Automated image analysis<\/a><\/li><li><a href=\"#coupled\">Coupled modelling<\/a><\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"optimised\">Optimised survey design and image reconstruction<\/h2>\n\n\n\n<p>Electrical resistivity tomography (ERT) surveys have tended to use well-understood, traditional electrode configurations to gather resistivity data. <a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/technologies\/#PRIME\">PRIME<\/a> permits the use of arbitrary arrangements of electrodes and enables the collection of very large measurement sets that can cover extensive areas at high data density. Research is therefore ongoing into algorithms that can make use of this flexibility to maximise ERT image resolution.<\/p>\n\n\n\n<p>Software has been developed that can automatically generate optimal electrode arrays for ERT surveys with 2D, 3D, cross-borehole and buried electrode arrays. These optimised surveys make efficient use of multichannel systems (e.g. PRIME) and have been tested using synthetic modelling studies both in the laboratory and in the field. They have been shown to provide better image resolution than traditional arrays of the same size (e.g. dipole-dipole).<\/p>\n\n\n<figure  class=\"img-wrap\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_Optimised_Survey.gif\" class=\"lazy-blur\" alt=\"Video showing the improved resolution given by using optimised 2D arrays for a synthetic model.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_Optimised_Survey.gif\" \/><figcaption class=\"caption sm-line\">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Improved resolution given by using optimised 2D arrays for a synthetic model.<\/p>\n<\/div>\n\t\t\t\t\t\n\t\t\t\t<\/figcaption><\/figure>\n\n<div  class=\"accordions\">\n\t\t\t\t<div class=\"acc-wrap\">\n\t\t\t\t\t<button class=\"acc-top secondary-background icon-arrow button no-btn\"><span class=\"button-content\" tabindex=\"-1\">Key references<\/span><\/button>\n\t\t\t\t\t<div class=\"acc-body sea-background-e\">\n\t\t\t\t\t\t<p>Loke, M H, Wilkinson, P B, and Chambers, J E. 2010.\u00a0<a href=\"https:\/\/doi.org\/10.1016\/j.cageo.2010.03.016\" target=\"_blank\" rel=\"noopener\">Fast computation of optimised electrode arrays for 2D resistivity surveys<\/a>.\u00a0<em>Computers &amp; Geosciences<\/em>, Vol. 36(11), 1414\u20131426.<\/p>\n<p>Loke, M H, Wilkinson, P B, and Chambers, J E. 2010.\u00a0<a href=\"https:\/\/doi.org\/10.1111\/j.1365-246X.2010.04796.x\" target=\"_blank\" rel=\"noopener\">Parallel computation of optimised arrays for 2D electrical imaging surveys<\/a>. <em>Geophysical Journal International<\/em>, Vol. 183(3), 1302\u20131315.<\/p>\n<p>Loke, M H, Wilkinson, P B, Chambers, J E, and Strutt, M. 2014. <a href=\"https:\/\/doi.org\/10.1111\/1365-2478.12072\" target=\"_blank\" rel=\"noopener\">Optimised arrays for 2D cross-borehole electrical tomography surveys<\/a>. <em>Geophysical Prospecting<\/em>, Vol. 62(1), 172\u2013187.<\/p>\n<p>Loke, M H, Wilkinson, P B, Uhlemann, S S, Chambers, J E, and Oxby, L S. 2014. <a href=\"https:\/\/doi.org\/10.1093\/gji\/ggu357\" target=\"_blank\" rel=\"noopener\">Computation of optimised arrays for 3D electrical imaging surveys<\/a>. <em>Geophysical Journal International<\/em>, Vol. 199(3), 1751\u20131764.<\/p>\n<p>Loke, M H, Kiflu, H, Wilkinson, P B, Harro, D, and Kruse, S. 2015. <a href=\"https:\/\/doi.org\/10.3997\/1873-0604.2015038\" target=\"_blank\" rel=\"noopener\">Optimised arrays for 2D resistivity surveys with combined surface and buried arrays<\/a>. <em>Near Surface Geophysics<\/em>, Vol. 13(5), 505\u2013518.<\/p>\n<p>Loke, M H, Wilkinson, P B, Chambers, J E, Uhlemann, S S, and Sorensen, J P R. 2015. <a href=\"https:\/\/doi.org\/10.1016\/j.jappgeo.2014.11.011\" target=\"_blank\" rel=\"noopener\">Optimised arrays for 2D resistivity survey lines with a large number of electrodes<\/a>. <em>Journal of Applied Geophysics<\/em>, Vol. 112, 136\u2013146.<\/p>\n<p>Uhlemann, S, Wilkinson, P B, Maurer, H, Wagner, F M, Johnson, T C and Chambers, J E. 2018.\u00a0<a href=\"https:\/\/doi.org\/10.1093\/gji\/ggy128\" target=\"_blank\" rel=\"noopener\">Optimised survey design for electrical resistivity tomography: combined optimisation of measurement configuration and electrode placement<\/a>. <em>Geophysical Journal International<\/em>, Vol. 214(1), 108\u2013121.<\/p>\n<p>Wilkinson, P B, Loke, M H, Meldrum, P I, Chambers, J E, Kuras, O, Gunn, D A, and Ogilvy, R D. 2012.\u00a0<a href=\"https:\/\/doi.org\/10.1111\/j.1365-246X.2012.05372.x\" target=\"_blank\" rel=\"noopener\">Practical aspects of applied optimised survey design for electrical resistivity tomography<\/a>. <em>Geophysical Journal International<\/em>, Vol. 189(1), 428\u2013440.<\/p>\n<p>Wilkinson, P B, Meldrum, P I, Chambers, J E, Kuras, O, and Ogilvy, R D. 2006.\u00a0<a href=\"https:\/\/doi.org\/10.1111\/j.1365-246X.2006.03196.x\" target=\"_blank\" rel=\"noopener\">Improved strategies for the automatic selection of optimized sets of electrical resistivity tomography measurement configurations<\/a>.\u00a0<em>Geophysical Journal International<\/em>, Vol. 167(3), 1119\u20131126.<\/p>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"adaptive\">Adaptive monitoring<\/h2>\n\n\n\n<p>Typically, ERT monitoring involves repeating the same survey on a time-lapse basis. The resolution of the monitoring images can be improved by using an adaptive, optimal, experimental design method. This uses previous images to guide the choice and design of future surveys. These survey designs are time dependent and, compared to dipole-dipole or static optimised surveys that do not change over time, focus a greater degree of the image resolution on regions of the subsurface that are actively changing.<\/p>\n\n\n\n<p>The adaptive optimisation method was validated with a controlled laboratory monitoring experiment comprising a well-defined cylindrical target moving along a trajectory that changes its depth and lateral position. The algorithm was implemented on a standard PC in conjunction with a modified, automated, multichannel resistivity imaging system. Data acquisition using the adaptive survey designs required no more time or power than with comparable standard surveys and the algorithm processing was sufficiently rapid to be carried out while the measurement system batteries recharged. The results showed that adaptively designed optimal surveys gave an extra increase of 15 per cent in image quality over and above that gained by using static (time independent) optimised surveys instead of dipole-dipole.<\/p>\n\n\n<figure  class=\"img-wrap\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_3a_Adaptive.gif\" class=\"lazy-blur\" alt=\"Video displaying results from adaptive monitoring of a moving cylindrical target in a laboratory environment.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_3a_Adaptive.gif\" \/><figcaption class=\"caption sm-line\">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Adaptive monitoring of a moving cylindrical target in a laboratory environment.<\/p>\n<\/div>\n\t\t\t\t\t\n\t\t\t\t<\/figcaption><\/figure>\n\n<div  class=\"accordions\">\n\t\t\t\t<div class=\"acc-wrap\">\n\t\t\t\t\t<button class=\"acc-top secondary-background icon-arrow button no-btn\"><span class=\"button-content\" tabindex=\"-1\">Key references<\/span><\/button>\n\t\t\t\t\t<div class=\"acc-body sea-background-e\">\n\t\t\t\t\t\t<p>Wilkinson, P B, Uhlemann, S, Meldrum, P I, Chambers, J E, Carri\u00e8re, S, Oxby, L, and Loke, M H. 2015.\u00a0<a href=\"https:\/\/doi.org\/10.1093\/gji\/ggv329\" target=\"_blank\" rel=\"noopener\">Adaptive time-lapse optimised survey design for electrical resistivity tomography monitoring<\/a>.\u00a0<em>Geophysical Journal International<\/em>, Vol. 203(1), 755\u2013766.<\/p>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"EMT\">Electrode movement tracking<\/h2>\n\n\n\n<p>If the electrode positions used in geoelectrical resistivity inversion are uncertain then the resulting tomographic images will exhibit artefacts that can obscure genuine features and time-lapse changes in the subsurface. This is a particular problem when using resistivity monitoring on unstable slopes such as landslides. We have developed innovative inverse methods to recover movements of resistivity imaging electrodes on unstable ground, either for 2D surveys (movement along a linear electrode array) or 3D surveys (movements in both directions across a grid electrode array).<\/p>\n\n\n<figure  class=\"img-wrap\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_4a-Option1_Electrode-Movement.gif\" class=\"lazy-blur\" alt=\"Video showing electrode movement of a 2D ERT arrey on a landslide in Yorkshire, UK.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_4a-Option1_Electrode-Movement.gif\" \/><figcaption class=\"caption \">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Electrode movement of a 2D ERT array on a landslide in Yorkshire, UK. Contains Ordnance Data \u00a9 Crown Copyright and database rights 2020 . Ordnance Survey Licence no. 100021290.<\/p>\n<\/div>\n\t\t\t\t\t\n\t\t\t\t<\/figcaption><\/figure>\n\n\n<p>The efficacy of these techniques has been demonstrated using numerical simulations, laboratory experiments and data from field monitoring sites. <\/p>\n\n\n\n<p>Using a monitoring installation on an active landslide, it was possible to recover sequences of movement over timescales of days to years. Typically these methods are able to recover the movements of the electrodes to an accuracy of 5\u201310 per cent of the spacing between the electrodes. Over short timescales, when the resistivity of the ground did not change significantly, an order-of-magnitude better accuracy was achievable. This enabled the onset and acceleration of landslide activity to be detected with a spatial resolution of a few centimetres and a temporal resolution of a few days.<\/p>\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_4b_Electrode-Movement.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;3D electrode movement of a grid array on a landslide in Yorkshire, UK. Contains Ordnance Data \u00a9 Crown Copyright and database rights 2020 . Ordnance Survey Licence no. 100021290.&lt;\/p&gt;\n\" data-gallery=\"gallery_10\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_4b_Electrode-Movement-150x150.jpg\" class=\"lazy-blur\" alt=\"Image showing 3D electrode movement of a grid array on a landslide in Yorkshire, UK.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_4b_Electrode-Movement.jpg\" \/><\/a><figcaption class=\"caption \">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>3D electrode movement of a grid array on a landslide in Yorkshire, UK. Contains Ordnance Data \u00a9 Crown Copyright and database rights 2020 . Ordnance Survey Licence no. 100021290.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_4b_Electrode-Movement.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;3D electrode movement of a grid array on a landslide in Yorkshire, UK. Contains Ordnance Data \u00a9 Crown Copyright and database rights 2020 . Ordnance Survey Licence no. 100021290.&lt;\/p&gt;\n\" data-gallery=\"gallery_10\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n<div  class=\"accordions\">\n\t\t\t\t<div class=\"acc-wrap\">\n\t\t\t\t\t<button class=\"acc-top secondary-background icon-arrow button no-btn\"><span class=\"button-content\" tabindex=\"-1\">Key references<\/span><\/button>\n\t\t\t\t\t<div class=\"acc-body sea-background-e\">\n\t\t\t\t\t\t<p>Boyle, A, Wilkinson, P B, Chambers, J E, Meldrum, P I, Uhlemann, S, and Adler, A. 2018.\u00a0<a href=\"https:\/\/doi.org\/10.1093\/gji\/ggx453\" target=\"_blank\" rel=\"noopener\">Jointly reconstructing ground motion and resistivity for ERT-based slope stability monitoring<\/a>. <em>Geophysical Journal International<\/em>, Vol. 212(2), 1167\u20131182.<\/p>\n<p>Loke, M H, Wilkinson, P B, Chambers, J E, and Meldrum, P I. 2018.\u00a0<a href=\"https:\/\/doi.org\/10.1111\/1365-2478.12522\" target=\"_blank\" rel=\"noopener\">Rapid inversion of data from 2D resistivity surveys with electrode displacements<\/a>.\u00a0<em>Geophysical Prospecting<\/em>, Vol. 66(3), 579\u2013594.<\/p>\n<p>Wilkinson, P B, Chambers, J E, Lelliott, M, Wealthall, G P, and Ogilvy, R D. 2008. <a href=\"https:\/\/doi.org\/10.1111\/j.1365-246X.2008.03725.x\" target=\"_blank\" rel=\"noopener\">Extreme sensitivity of crosshole electrical resistivity tomography measurements to geometric errors<\/a>.\u00a0<em>Geophysical Journal International<\/em>, Vol. 173(1), 49\u201362.<\/p>\n<p>Wilkinson, P B, Chambers, J E, Meldrum, P I, Gunn, D A, Ogilvy, R D, and Kuras, O. 2010.\u00a0<a href=\"https:\/\/doi.org\/10.1111\/j.1365-246X.2010.04760.x\" target=\"_blank\" rel=\"noopener\">Predicting the movements of permanently installed electrodes on an active landslide using time-lapse geoelectrical resistivity data only<\/a>. <em>Geophysical Journal International<\/em>, Vol. 183(2), 543\u2013556.<\/p>\n<p>Wilkinson, P B, Uhlemann, S Chambers, J E, Meldrum, P I, and Loke, M H. 2015. <a href=\"https:\/\/doi.org\/10.1093\/gji\/ggu483\" target=\"_blank\" rel=\"noopener\">Development and testing of displacement inversion to track electrode movements on 3D electrical resistivity tomography monitoring grids<\/a>. <em>Geophysical Journal International<\/em>, Vol. 200(3), 1566\u20131581.<\/p>\n<p>Wilkinson, P, Chambers, J, Uhlemann, S, Meldrum, P, Smith, A, Dixon, N, and Loke, M H. 2016. <a href=\"https:\/\/doi.org\/10.1002\/2015GL067494\" target=\"_blank\" rel=\"noopener\">Reconstruction of landslide movements by inversion of 4D electrical resistivity tomography monitoring data<\/a>.\u00a0<em>Geophysical Research Letters<\/em>, Vol. 43(3), 1166\u20131174.<\/p>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"automated\">Automated image analysis<\/h2>\n\n\n\n<p>We have applied computer vision and machine learning methods to automatically interpret geoelectrical resistivity images. <\/p>\n\n\n\n<p>Identifying interfaces in resistivity images can be difficult due to the smoothness constraints typically used in the inversion. A statistical, population-based approach has been used to guide a &#8216;fuzzy clustering&#8217; method, which identifies clusters of related cells in the resistivity images while avoiding the assumption of hard edges. It also provides a measure of the uncertainties in the cluster boundaries. The algorithm was validated by direct comparisons with known bedrock depths at two 3D resistivity survey sites and performed as well as other image analysis methods but with much less user input.<\/p>\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5a_Image-Analysis.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Fuzzy clustering of related resistivity cells avoids the assumption of hard edges and estimates the bedrock\u2013sediment interface.&lt;\/p&gt;\n\" data-gallery=\"gallery_53253\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5a_Image-Analysis-150x150.jpg\" class=\"lazy-blur\" alt=\"Fuzzy clustering of related resistivity cells avoiuds the assumption of hard edges, and estimates the bedrock\/sediment interface.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5a_Image-Analysis-960x627.jpg\" \/><\/a><figcaption class=\"caption \">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Fuzzy clustering of related resistivity cells avoids the assumption of hard edges and estimates the bedrock\u2013sediment interface.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5a_Image-Analysis.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Fuzzy clustering of related resistivity cells avoids the assumption of hard edges and estimates the bedrock\u2013sediment interface.&lt;\/p&gt;\n\" data-gallery=\"gallery_53253\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n\n<p>Such techniques were also used to automatically track the motion of tracers in resistivity monitoring images. Using Bayesian inference techniques, in the form of a Kalman filter, the trajectory of the tracer was monitored by predicting and updating a state model representing its movements. Observations for the Kalman filter were gathered using a maximally stable volumes algorithm to isolate the tracer from the background in the resistivity images. This method was able to track the movements of tracers in 2D and 3D monitoring experiments successfully in the presence of noise without manual intervention.<\/p>\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5b_Image-Analysis.png\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Automated image analysis of a tracer experiment.&lt;\/p&gt;\n\" data-gallery=\"gallery_59870\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5b_Image-Analysis-150x150.png\" class=\"lazy-blur\" alt=\"Automated image analysis of tracer experiment.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5b_Image-Analysis-960x360.png\" \/><\/a><figcaption class=\"caption sm-line\">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Automated image analysis of a tracer experiment.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_5b_Image-Analysis.png\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Automated image analysis of a tracer experiment.&lt;\/p&gt;\n\" data-gallery=\"gallery_59870\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n<div  class=\"accordions\">\n\t\t\t\t<div class=\"acc-wrap\">\n\t\t\t\t\t<button class=\"acc-top secondary-background icon-arrow button no-btn\"><span class=\"button-content\" tabindex=\"-1\">Key references<\/span><\/button>\n\t\t\t\t\t<div class=\"acc-body sea-background-e\">\n\t\t\t\t\t\t<p>Ward, W O C, Wilkinson, P B, Chamber, J E, Oxby, L S, and Bai, L. 2014.\u00a0<a href=\"https:\/\/doi.org\/10.1093\/gji\/ggu006\" target=\"_blank\" rel=\"noopener\">Distribution-based fuzzy clustering of electrical resistivity tomography images for interface detection<\/a>.\u00a0<em>Geophysical Journal International<\/em>, Vol. 197(1), 310\u2013321.<\/p>\n<p>Ward, W O C, Wilkinson, P B, Chambers, J E, Nilsson, H, Kuras, O, and Bai, L. 2016.\u00a0<a href=\"https:\/\/doi.org\/10.1002\/2015WR017958\" target=\"_blank\" rel=\"noopener\">Tracking tracer motion in a 4-D electrical resistivity tomography experiment<\/a>.\u00a0<em>Water Resources Research<\/em>, Vol. 52(5), 4078\u20134094.<\/p>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"coupled\">Coupled modelling<\/h2>\n\n\n\n<p>Resistivity imaging of the Hollin Hill landslide in Yorkshire clearly shows formations with different resistivities (Redcar and Whitby Mudstone formations (RMF; WMF) with lower resistivities at the base and top of the image and the intermediate Staithes Sandstone Formation (SSF) with higher resistivities). These images have smooth boundaries, which make locating the exact interface difficult (Figure 1). <\/p>\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6a_Coupled-Modelling.gif\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 1: separate inversions of 2D electrical resistivity and seismic data.&lt;\/p&gt;\n\" data-gallery=\"gallery_46106\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6a_Coupled-Modelling-150x150.gif\" class=\"lazy-blur\" alt=\"Separate inversions of 2D electrical resistivity and seismic data.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6a_Coupled-Modelling.gif\" \/><\/a><figcaption class=\"caption sm-line\">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Figure 1: separate inversions of 2D electrical resistivity and seismic data.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6a_Coupled-Modelling.gif\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 1: separate inversions of 2D electrical resistivity and seismic data.&lt;\/p&gt;\n\" data-gallery=\"gallery_46106\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n\n<p>P- and S-wave seismic refraction tomography surveys have also been carried out and used to produce images of Poisson\u2019s ratio, which give a very clear indication of the boundary between the WMF and SSF. By extracting the surface from the seismic images and including it as a structural constraint in the resistivity inversion, the resolution of the WMF\/SSF boundary was much improved in the resistivity image (Figure 2).<\/p>\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6b_Coupled-Modelling.gif\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 2: inversion of 3D ERT data using seismic data as a structural constraint.&lt;\/p&gt;\n\" data-gallery=\"gallery_8843\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6b_Coupled-Modelling-150x150.gif\" class=\"lazy-blur\" alt=\"Inversion of 3D ERT data using seismic data as a structural constraint.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6b_Coupled-Modelling.gif\" \/><\/a><figcaption class=\"caption sm-line\">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Figure 2: inversion of 3D ERT data using seismic data as a structural constraint.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6b_Coupled-Modelling.gif\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 2: inversion of 3D ERT data using seismic data as a structural constraint.&lt;\/p&gt;\n\" data-gallery=\"gallery_8843\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n\n<p>Coupled hydrogeophysical modelling links flow and transport modelling to geophysical modelling. It enables simulation of geophysical monitoring responses to flow scenarios and inverse modelling to predict hydrological parameters from geophysical measurements, e.g. leak locations from geoelectrical monitoring data. <\/p>\n\n\n\n<p>Animation 1 shows a 2D flow and transport model simulating a tracer injection at an injector in the upper left of the domain. Groundwater movement is towards an extraction well to the lower right. An ERT imaging cell with four boreholes is located at the centre of the domain. As the conductive tracer migrates through the ERT imaging cell, there is a corresponding increase in electrical conductivity in the ERT imaging cell.<\/p>\n\n\n<figure  class=\"img-wrap\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6d_Coupled-Modelling.gif\" class=\"lazy-blur\" alt=\"Modelling of a tracer experiment using a 2D flow and transport model.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6d_Coupled-Modelling.gif\" \/><figcaption class=\"caption sm-line\">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Animation 1: modelling of a tracer experiment using a 2D flow and transport model.<\/p>\n<\/div>\n\t\t\t\t\t\n\t\t\t\t<\/figcaption><\/figure>\n\n\n<p>The possibility for geoelectrical resistivity monitoring data to inform and update slope stability models in near-real-time is being investigated using coupled geophysical and geomechanical modelling. This work links temperature-corrected resistivity models via soil suction modelling to volumetric estimates of shear strength. <\/p>\n\n\n\n<p>The preliminary results in the animation show the changes in resistivity in the Hollin Hill 3D geoelectrical model and the subsequent effects on the distribution of shear strength, which drops dramatically in the winter months around the break of slope near the top of the modelled region.<\/p>\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6c_Coupled-Modelling.png\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 3: the process of simulating geophysical responses to hydraulic flow scenarios.&lt;\/p&gt;\n\" data-gallery=\"gallery_9296\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6c_Coupled-Modelling-150x150.png\" class=\"lazy-blur\" alt=\"Process of simulating geophysical responses to hydraulic flow scenarios.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6c_Coupled-Modelling.png\" \/><\/a><figcaption class=\"caption sm-line\">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Figure 3: the process of simulating geophysical responses to hydraulic flow scenarios.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6c_Coupled-Modelling.png\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 3: the process of simulating geophysical responses to hydraulic flow scenarios.&lt;\/p&gt;\n\" data-gallery=\"gallery_9296\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6e-Option1_Coupled-Modelling.gif\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 4: shear strength geomechanical model derived from geoelectrical measurements on a landslide in Yorkshire, UK.&lt;\/p&gt;\n\" data-gallery=\"gallery_71511\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6e-Option1_Coupled-Modelling.gif\" class=\"lazy-blur\" alt=\"Geomechanical model derived from geoelectrical measurements on a landslide in Yorkshire, UK.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6e-Option1_Coupled-Modelling.gif\" \/><\/a><figcaption class=\"caption \">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Figure 4: shear strength geomechanical model derived from geoelectrical measurements on a landslide in Yorkshire, UK.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/Theory_6e-Option1_Coupled-Modelling.gif\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Figure 4: shear strength geomechanical model derived from geoelectrical measurements on a landslide in Yorkshire, UK.&lt;\/p&gt;\n\" data-gallery=\"gallery_71511\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n<div  class=\"accordions\">\n\t\t\t\t<div class=\"acc-wrap\">\n\t\t\t\t\t<button class=\"acc-top secondary-background icon-arrow button no-btn\"><span class=\"button-content\" tabindex=\"-1\">Key references<\/span><\/button>\n\t\t\t\t\t<div class=\"acc-body sea-background-e\">\n\t\t\t\t\t\t<p>Uhlemann, S, Chambers, J, Wilkinson, P, Maurer, H, Merritt, A, Meldrum, P, Kuras, O, Gunn, D, Smith, A, and Dijkstra, T. 2017.\u00a0<a href=\"https:\/\/doi.org\/10.1002\/2016JF003983\" target=\"_blank\" rel=\"noopener\">Four-dimensional imaging of moisture dynamics during landslide reactivation<\/a>.\u00a0<em>Journal of Geophysical Research: Earth Surface<\/em>, Vol. 122(1), 398\u2013418.<\/p>\n<p>&nbsp;<\/p>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\n\n<h2 class=\"wp-block-heading\">Contact<\/h2>\n\n\n\n<p>If you want to discover more then please contact <a href=\"https:\/\/www.bgs.ac.uk\/people\/wilkinson-paul\/\">Paul Wilkinson<\/a> or&nbsp;<a href=\"https:\/\/www.bgs.ac.uk\/people\/chambers-jonathan\/\">Jonathan Chambers<\/a>.<\/p>\n\n\n\n<p><\/p>\n<\/div><\/div><\/div><\/section>\n\n\n\t\t\t\t\t<section   id=\"latest-content-1346-block_5eaa9444001e7\" class=\"grid-section  primary-background   \" >\n\t\t\t\t\t\t<div class=\"container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"row header-of-section\">\n\t\t\t\t\t\t\t\t<div class=\"col-12\">\n\t\t\t\t\t\t\t\t\t<h2>You may also be interested in<\/h2>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"row grid-wrap\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"col-lg-6 col-12\">\n\t<div class=\"cards cards-orizontal-sm  cards-find-more  cards-bordered\">\n\t\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/technologies\/prime\/\" class=\"media-wrap\">\n\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/PRIME_feature-150x150.jpg\" class=\"lazy-blur wp-post-image\" alt=\"Close up of PRIME hardware.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/04\/PRIME_feature.jpg\" \/>\t\t\t\t\t<\/a>\n\t\t\t\t<div class=\"info-wrap\">\n\t\t\t<div class=\"info\">\n\t\t\t\t<h4><a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/technologies\/prime\/\">PRIME<\/a><\/h4>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<p>PRIME is a low-cost system specifically designed to monitor through remote operation for deployment on &#8216;at risk&#8217; geotechnical assets (e.g. embankments; cuttings; dams). <\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/geophysical-tomography\/technologies\/prime\/\">Show more<\/a>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n<div class=\"col-lg-6 col-12\">\n\t<div class=\"cards cards-orizontal-sm  cards-find-more  cards-bordered\">\n\t\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/landslides\/\" class=\"media-wrap\">\n\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/02\/P786645-150x150.jpg\" class=\"lazy-blur wp-post-image\" alt=\"Debris pathway downslope, partly netted. Debris on the railway line has been cleared and the line is in the process of being repaired.\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/02\/P786645.jpg\" \/>\t\t\t\t\t<\/a>\n\t\t\t\t<div class=\"info-wrap\">\n\t\t\t<div class=\"info\">\n\t\t\t\t<h4><a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/landslides\/\">Landslides<\/a><\/h4>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<p>The BGS landslides team is involved in many aspects of landslide research, with the primary objective of building resilience both in the UK and internationally.<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/landslides\/\">Show more<\/a>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n<div class=\"col-lg-6 col-12\">\n\t<div class=\"cards cards-orizontal-sm  cards-find-more  cards-bordered\">\n\t\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geological-research\/science-facilities\/engineering-geotechnical-capability\/\" class=\"media-wrap\">\n\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/02\/feature_Geotechnical_RD-150x150.jpg\" class=\"lazy-blur wp-post-image\" alt=\"Geotechnical research and design facility\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/02\/feature_Geotechnical_RD.jpg\" \/>\t\t\t\t\t<\/a>\n\t\t\t\t<div class=\"info-wrap\">\n\t\t\t<div class=\"info\">\n\t\t\t\t<h4><a href=\"https:\/\/www.bgs.ac.uk\/geological-research\/science-facilities\/engineering-geotechnical-capability\/\">Engineering and Geotechnical Capability<\/a><\/h4>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<p>The BGS Engineering and Geotechnical Capability leads the development and application of field and laboratory infrastructure and long-term management of geophysical and geotechnical property data.<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geological-research\/science-facilities\/engineering-geotechnical-capability\/\">Show more<\/a>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n<div class=\"col-lg-6 col-12\">\n\t<div class=\"cards cards-orizontal-sm  cards-find-more  cards-bordered\">\n\t\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/news\/bgs-prime-an-early-warning-system-for-slope-failure\/\" class=\"media-wrap\">\n\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/feature_Teton_Dam_Flood_Newdale-150x150.jpg\" class=\"lazy-blur wp-post-image\" alt=\"feature_Teton_Dam_Flood_Newdale\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/feature_Teton_Dam_Flood_Newdale.jpg\" \/>\t\t\t\t\t<\/a>\n\t\t\t\t<div class=\"info-wrap\">\n\t\t\t<div class=\"info\">\n\t\t\t\t<h4><a href=\"https:\/\/www.bgs.ac.uk\/news\/bgs-prime-an-early-warning-system-for-slope-failure\/\">BGS PRIME: an early warning system for slope failure<\/a><\/h4>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<p>Dam and slope failures can lead to the wide-scale destruction of property and, in some cases, catastrophic loss of life.<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/news\/bgs-prime-an-early-warning-system-for-slope-failure\/\">Show more<\/a>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"row\">\n\t\t\t\t\t\t\t\t<div class=\"col-12\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t","protected":false},"excerpt":{"rendered":"<p>The team  are actively researching and developing new modelling and data analysis methods in geophysical tomography.<\/p>\n","protected":false},"featured_media":28477,"parent":24240,"menu_order":3,"template":"","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"33925,21316,37470,51064,9908,8183","_relevanssi_noindex_reason":""},"tags":[],"region":[13,11,12,10,9,8,116],"topic":[26,33,20,21,32,23,24,25,27,29,30],"purpose":[],"area":[15,16,17,19],"challenge":[50,49,51],"challenge_topic":[118,134,135,132,131,137,142,139],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.3 - 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