25:["$","title",null,{"children":"Carbonate Constraints | Vekta Group | Observable"}] 49:T742,There are three types of rock formations - sedimentary, volcanic and metamorphic. Carbonate sediments are a class of sedimentary rock with unconsolidated material that contains more than 50% carbonate materials. Limestone and dolostone are the two major types: limestone is largely composed of calcite and/or aragonite, both forms of calcium carbonate (CaCO₃); whilst dolostone largely composes dolomite (CaMg(CO₃)₂). Carbonate sediments are primarily formed through biological or inorganic processes which result in the build up of calcium carbonate. This tends to happen in shallow, warm oceans, lakes and streams where a wide range of particle shapes and sizes are found: **1. Biological Processes** - Biogenic production - disintegration of skeletal structures and shells. - Reef growth - shallow, high energy environments encourage reef growth, forming hard carbonate structures. **2. Inorganic Processes** - Seawater precipitation - when seawater is naturally oversaturated with calcium carbonate it can lead to precipitation under high pressures and temperatures. - Bio-induced precipitation - changes in pH caused by microbial activity can cause carbonate precipitation. Carbonate sediments, common in mid-latitudes, range from soft uncemented silts to dense, well-cemented limestones. They vary greatly in cementation, compressibility, and shear strength, and are known for high spatial variability. A key concern in offshore wind development is their tendency for cyclic degradation—a weakening of sediment strength due to repeated loading from waves, wind, and turbine operation. In carbonate sediments, this can lead to particle breakdown, increased settlement, and reduced bearing capacity. These behaviours must be accounted for in site investigations and foundation design to ensure long-term stability.4a:T5c9,To explore the impact carbonate sediment formations have on offshore wind development compared to other physical constraints, Australia has been taken as a case study. The three variables used to build the model are bathymetry, distance to shore and bulk carbon content: 1. Bathymetry - a global terrain model for the ocean measured in metres provided by [GEBCO](https://www.gebco.net/data-products/gridded-bathymetry-data) and clipped to the Australian Exclusive Economic Zone (EEZ). 2. Distance Isochrone - a raster dataset displaying distance to shore in kilometres built in QGIS and clipped to the Australian EEZ. 4. Bulk Carbon - a raster displaying the carbonate content of seabed sediments expressed as a weighted percentage, provided by [Geoscience Australia](https://researchdata.edu.au/sedimentary-features-carbonate-geoscience-dataset/691586). The images below display the raw data. The bathymetry data highlights favourable areas around the coastline as well as extending northwards along the northern coast and within the Bass Strait, where red indicates shallower water depths. The distance isochrones are also favourable closer to shore. The bulk carbon data suggests more suitable areas off the coasts of Sydney and the Northern Territories, just north of the Gold Coast, as well as at the EEZ edge in the south west. The more suitable areas for this dataset are regions of lower bulk carbon percentages, which are therefore less likely to be carbonate sediments.4b:T1660,map = (function*() { let container = DOM.element('div', { style: `width:${width}px;height:${width / 1.6}px` }); yield container; // Initialize the map let map = L.map(container).setView([-28.822, 134.415], 4); // Add base tile layer let osmLayer = L.tileLayer("https://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}.png", { attribution: "© OpenStreetMap contributors, © CartoDB" }).addTo(map); function createInteractiveLayer(geojson, options = {}, styleField = null, label = "") { return L.geoJSON(geojson, { ...options, style: feature => { if (styleField) { const value = feature.properties[styleField]; const color = value > 900 ? '#9f0e14' : value > 800 ? '#bf151a' : value > 700 ? '#da2623' : value > 600 ? '#f0402f' : value > 500 ? '#f96144' : value > 400 ? '#fc7e5e' : value > 300 ? '#fc9a7c' : value > 200 ? '#fcb79c' : value > 100 ? '#fdd1be' : value > 0 ? '#fee6db' : '#fff5f0'; return { color, fillColor: color, fillOpacity: 0.6, weight: 0.2 }; } else { return options.style || { color: '#0000ff', weight: 1, fillColor: '#0000ff', fillOpacity: 0.7 }; } }, onEachFeature: options.onEachFeature }); } // Define the wind farms layer separately so we can reference it const windFarmsLayer = createInteractiveLayer(windFarms, { onEachFeature: (feature, layer) => { const props = feature.properties || {}; // Filter out unwanted keys const entries = Object.entries(props) .filter(([k]) => !["RUKID", "Latitude", "Longitude", "Project"].includes(k)) .map(([k, v]) => `${k}: ${v}`); const title = props.Project || "Wind Farm"; layer.on('click', function () { // Reset style for all wind farms windFarmsLayer.eachLayer(l => windFarmsLayer.resetStyle(l)); // Apply highlight style to the clicked feature layer.setStyle({ color: '#ffffff', weight: 2, fillOpacity: 0.7 }); const content = `${title}
` + entries.join('
'); layer.bindPopup(content).openPopup(); }); } }, null, "Wind Farms"); // Reset style when popup is closed map.on('popupclose', () => { windFarmsLayer.eachLayer(l => windFarmsLayer.resetStyle(l)); }); const layers = { "Suitability Model": createInteractiveLayer(model, { onEachFeature: (feature, layer) => { const props = feature.properties || {}; const entries = Object.entries(props) .filter(([k]) => k !== "fid") .map(([k, v]) => k === "DN" ? `Suitability: ${v}` : `${k}: ${v}`); layer.on('click', () => { const content = `Model
` + entries.join('
'); layer.bindPopup(content).openPopup(); }); } }, "DN", "Model"), "Wind Farms": windFarmsLayer }; Object.entries(layers).forEach(([name, layer]) => { layer.addTo(map); }); const LayerControl = L.Control.extend({ onAdd: function () { const div = L.DomUtil.create('div', 'layer-control'); div.style.background = 'white'; div.style.padding = '6px'; div.style.borderRadius = '4px'; div.innerHTML = "Suitability Model
"; const grades = [0, 100, 200, 300, 400, 500, 600, 700, 800, 900]; const colors = [ '#fee6db', '#fdd1be', '#fcb79c', '#fc9a7c', '#fc7e5e', '#f96144', '#f0402f', '#da2623', '#bf151a', '#9f0e14' ]; for (let i = grades.length - 1; i >= 0; i--) { const from = grades[i]; const to = i < grades.length - 1 ? grades[i + 1] : 1000; const label = `${from}–${to}`; const color = colors[i]; const item = document.createElement('div'); item.style.display = 'flex'; item.style.alignItems = 'center'; item.style.marginBottom = '4px'; const colorBox = document.createElement('div'); colorBox.style.width = '13px'; colorBox.style.height = '13px'; colorBox.style.backgroundColor = color; colorBox.style.marginRight = '6px'; colorBox.style.border = '1px solid #999'; const labelEl = document.createElement('span'); labelEl.innerText = label; item.appendChild(colorBox); item.appendChild(labelEl); div.appendChild(item); } // Wind Farms static legend entry const windLegendItem = document.createElement('div'); windLegendItem.style.display = 'flex'; windLegendItem.style.alignItems = 'center'; windLegendItem.style.marginTop = '10px'; const windColorBox = document.createElement('div'); windColorBox.style.width = '13px'; windColorBox.style.height = '13px'; windColorBox.style.backgroundColor = '#0000ff'; windColorBox.style.marginRight = '6px'; windColorBox.style.border = '1px solid #999'; const windLabel = document.createElement('span'); windLabel.innerText = 'Wind Farms'; windLegendItem.appendChild(windColorBox); windLegendItem.appendChild(windLabel); div.appendChild(windLegendItem); return div; } }); map.addControl(new LayerControl({ position: 'bottomright' })); })(); 4c:T49f,Taking a deeper dive into Australian wind farms, summary statistics are calculated using the Bulk Carbon dataset. It is noted that all projects except Spinifex and Blue Mackerel have a mean bulk carbon content greater than 50%, implying carbonate sediments are present across more than 90% of Australia's offshore wind farm developments. Whilst both Gippsland projects have the smallest deviation in their bulk carbon quantities across the polygon areas, at less than 1%, they also have the highest percentage of carbonate content, sitting at over 90%. In comparison, the Bunbury DA 1, 3 and 4 have carbon content c. 70%, yet the variation in this value can be up to 18% across the wind farm areas.
As mentioned above, the presence of carbonate material in an offshore wind farm zones can present challenges during the drilling phase of development. Given this, it is crucial to have a strong understanding of the seabed subsurface to reduce project risks. As the countrywide bulk carbon dataset demonstrates high variance, it is recommended individual developers undertake site specific surveys to improve their knowledge of the subsurface in order to de-risk their projects. 4d:T51d,### Implications The presence of carbonate rocks can impact the construction of turbine foundations, adding potential risks to the drilling phase of projects. Foundation design tends to involve driven or drilled and grouted piles. Driven piles are pre-manufactured and hammered into the ground using a pile driver, whereas the latter involves drilling a hole to a specified depth and filling with grout. Both piling options are impacted by the presence of carbonate rocks: - harder carbonate material can make pile driving extremely difficult, - fractures and cavities often found in carbonate sediments may lead to difficulty piling straight or lead to hole collapse during drilling, - drilling through highly compacted or cemented carbonate sediments may require specialised equipment. In areas where carbonate rock is hard or fractured, pre-drilling may be required to create a guide for the driven pile. However, the process can still be challenging due to the variability in the hardness of carbonate rocks. Drilled piles are often preferred in carbonate rocks, especially when the rock is fractured or has voids. This method allows for better control of pile installation, and the grout used can flow into fractures or cavities, improving the pile's load-bearing capacity and bonding to the rock.4e:[{"id":"c6bbc29562ce7da37289a030abed999aa7e84c26c28a2c5cd013a9e001713e652c6c698f24baf912f46b16ace13992232d1ff9738e0515adac57755338ee8fb3","href":"https://static.observableusercontent.com/files/c6bbc29562ce7da37289a030abed999aa7e84c26c28a2c5cd013a9e001713e652c6c698f24baf912f46b16ace13992232d1ff9738e0515adac57755338ee8fb3","name":"Insights template.png","type":"image/png","lastModified":1747128132099.213,"size":380487},{"id":"86f23bccc8329b56624caa1fd7560051a0b462904564596d5e33cc19c65605e0d1bab02c1a8961aa3c24d0e41e3310c927fa0b4de5dc9f847bafa7ea37cd41a2","href":"https://static.observableusercontent.com/files/86f23bccc8329b56624caa1fd7560051a0b462904564596d5e33cc19c65605e0d1bab02c1a8961aa3c24d0e41e3310c927fa0b4de5dc9f847bafa7ea37cd41a2","name":"CarbonateSedimentsStats@3.json","type":"application/json","lastModified":1747130789766.09,"size":2889},{"id":"3a7c0bea0811e5b46a625db7b676e2a313c4370b5242db3a23a0c2a2825fbc1a4da313f71b00f2e5e4f7f2c947be12d9e3f4fa1df04f8706546f6269a079b367","href":"https://static.observableusercontent.com/files/3a7c0bea0811e5b46a625db7b676e2a313c4370b5242db3a23a0c2a2825fbc1a4da313f71b00f2e5e4f7f2c947be12d9e3f4fa1df04f8706546f6269a079b367","name":"Aus_Wind-Farms.geojson","type":"application/geo+json","lastModified":1745858966396.422,"size":31526},{"id":"988a0435c161cb2874ff0ab950a71fdba12ae8dd398e823f199bf042e232dcea7f57f914d3917cdfd6c8fb97596d7ade3ad0db0f1052c782d9e1dcbf24eba797","href":"https://static.observableusercontent.com/files/988a0435c161cb2874ff0ab950a71fdba12ae8dd398e823f199bf042e232dcea7f57f914d3917cdfd6c8fb97596d7ade3ad0db0f1052c782d9e1dcbf24eba797","name":"Model_vectorised_1000.geojson","type":"application/geo+json","lastModified":1745926480003.551,"size":7259270}] 29:{"id":"824d70b41840a34b","slug":null,"title":"Carbonate Constraints","thumbnail":"67ada2a9c77bd2bb7e7feead31f68ed39ae6530613f10a4430f969cce251db64","access_level":"public","create_time":"$D2025-04-15T15:06:38.527Z","update_time":"$D2026-04-07T13:37:02.662Z","view_time":null,"first_public_time":"$D2025-05-13T11:47:47.882Z","has_unpublished_edits":null,"fork":{"id":"0dd48ecda7f5dfb5","slug":null,"title":"Frozen Foundations","owner":{"id":"3594fe6877d14711","login":"vekta-group","name":"Vekta Group"}},"stars":1,"starred":false,"owner":{"type":"team","id":"3594fe6877d14711","login":"vekta-group","name":"Vekta Group","avatar_url":"https://avatars-next.observableusercontent.com/13f6934c06a2c847905f92615bfe639e05a96b39badbe0036f3139b0c24ef101","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":778,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"353739170940576d","login":"vekta-group","name":"Vekta Group","avatar_url":"https://avatars-next.observableusercontent.com/13f6934c06a2c847905f92615bfe639e05a96b39badbe0036f3139b0c24ef101","tier":null,"bio":"","followed_by_you":false,"follows_you":false}],"members":[{"type":"individual","id":"353739170940576d","login":"vekta-group","name":"Vekta Group","avatar_url":"https://avatars-next.observableusercontent.com/13f6934c06a2c847905f92615bfe639e05a96b39badbe0036f3139b0c24ef101","tier":null,"role":"editor"},{"type":"team","id":"3594fe6877d14711","login":"vekta-group","name":"Vekta Group","avatar_url":"https://avatars-next.observableusercontent.com/13f6934c06a2c847905f92615bfe639e05a96b39badbe0036f3139b0c24ef101","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":{"id":"a5603c9dcf7492ca","slug":"vekta-digital-insights","title":"Vekta Digital Insights ","owner":{"id":"3594fe6877d14711","login":"vekta-group","name":"Vekta Group"}},"type":"notebook","body":{"titling":"auto","title":"Carbonate Constraints","cells":[{"id":0,"value":"# Carbonate Constraints","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"Earlier this month, historically glaciated regions were analysed in the context of 'tricky' geological areas for offshore wind development. This week a similar analysis will be undertaken on carbonate sediments, using Australia as a case study. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":19,"value":"## Geological Background","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":24,"value":"$49","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":244,"value":"## Case Study: Australia","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":247,"value":"$4a","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":272,"value":"modelBuilding = FileAttachment(\"Insights template.png\").image({\n width:900\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":267,"value":"For each input, the data is normalised between 0 and 1 to produce a common scale for easy comparison in generating the model. The table below details the input values, with thresholds chosen based on current offshore wind technology. Each dataset is then weighted to reflect their impact on offshore wind development. Bathymetry and bulk carbon content received a 40% weighting, whilst distance to shore a lesser weighting (20%) to demonstrate the harder constraints exerted by the former. \n\n| Suitability Score\t| Bathymetry (m) | Distance to Shore (km) | Bulk Carbon (%)|\n| - | - |\n| 1 | 0 - 70 | 10 - 40 | 0 - 50 |\n| 0.5 | 70 - 200 | 40 - 140 | - |\n| 0 | > 200 | 0 - 10, > 140 | 50 - 100 |","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":689,"value":"
\n### Results\n\nThe interactive map below displays the model output. Darker red denotes more favourable conditions for offshore wind development and currently planned wind farm developments are in blue. Zoom and click on the map to inspect the layers. \n\nThe model would suggest the northern coastline between Darwin and Thursday Island is the most suitable, with hotspots near Perth, Adelaide and Tasmania appearing fairly suitable. Concentrating on the potential areas in and around the Bass Strait, Blue Mackerel and Gippsland Dawn are sited most suitably based on the results of this model. Developments within the Bass Strait Tasmania Declared Area (DA) polygons should prioritise the eastern, smaller polygon compared to the west due to shallower water depths and less carbonate materials; Star of the South and Great Eastern should also seek to develop within the north western regions of their polygons for the same reasons.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":171,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":270,"value":"$4c","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":445,"value":"Plot.plot({\n y: {\n label: \"Bulk Carbon (%)\",\n grid: true,\n inset: 6, \n domain: [30, 95]\n },\n x: {\n label: \"Project\",\n tickRotate: 30,\n labelOffset: 90,\n inset: 10,\n domain: sortedProjects\n },\n color: {\n legend: true,\n domain: [\"Standard Deviation\", \"Mean\"],\n range: [\"blue\", \"black\"]\n },\n marks: [\n Plot.rectY(decoratedData.filter(d => d.type === \"Standard Deviation\"), {\n x: \"Project\",\n y1: \"y1\",\n y2: \"y2\",\n fill: \"type\",\n fillOpacity: 0.4,\n width: 20\n }),\n Plot.dot(decoratedData.filter(d => d.type === \"Mean\"), {\n x: \"Project\",\n y: \"y\",\n fill: \"type\",\n r: 3, \n tip: true\n }),\n Plot.ruleY([50], { stroke: \"red\", strokeWidth: 2, strokeDasharray: \"4 2\" }) // Red dashed line at y=50\n ],\n height: 500,\n width: 1100,\n marginBottom: 95,\n});\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":28,"value":"$4d","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":9,"value":"
\n## Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":112,"value":"### Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":257,"value":"Bulk Carbon: https://researchdata.edu.au/sedimentary-features-carbonate-geoscience-dataset/691586","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":11,"value":"### Plot 1: Suitability Model","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":187,"value":"windFarms = FileAttachment(\"Aus_Wind-Farms.geojson\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":225,"value":"model = FileAttachment(\"Model_vectorised_1000.geojson\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"### Plot 2: Bulk Carbon Statistics Bar Chart","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":509,"value":"carbonatesedstats = FileAttachment(\"CarbonateSedimentsStats@3.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":579,"value":"sortedProjects = carbonatesedstats\n .slice() // make a copy\n .sort((a, b) => b.Mean - a.Mean)\n .map(d => d.Project)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":570,"value":"// Flatten the data and assign types\ndecoratedData = carbonatesedstats.flatMap(d => [\n {\n ...d,\n type: \"Standard Deviation\",\n y1: d.Mean - d.StandardDeviation,\n y2: d.Mean + d.StandardDeviation\n },\n {\n ...d,\n type: \"Mean\",\n y: d.Mean\n }\n]);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":123,"value":"html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W4e","stdlib":"1"}} 24:null