Senegal-Mauritania wave and hydrodynamic hindcast models now available

MetOcean Solutions recently completed the development of high-resolution wave and hydrodynamic hindcast models offshore Senegal and Mauritania, West Africa.

“Senegal and Mauritania coastal areas are influenced by oceanographic processes, including tides, coastal upwelling/downwelling, eddies, internal waves, and highly-energetic wave conditions,” says Senior Oceanographer Dr Séverin Thiébaut. “Our challenge was to ensure the models would adequately replicate those multi-scale processes and both ambient and extreme metocean conditions.”

The Simulating WAves Nearshore (SWAN) model was used to resolve the wave climate and the Regional Ocean Modeling System (ROMS) was applied to simulate the hydrodynamic circulation. The technique implemented is known as ‘dynamical downscaling’, using information from large scale global models to drive regional/nearshore models at much higher resolution. All models were carefully calibrated with measured data from several current meters and wave buoys that were made available.

The SWAN model simulates the growth, refraction and decay of each frequency-direction component of the complete sea state, providing a realistic description of the wave field as it changes in time and space.

“In order to reliably replicate the regional and nearshore wave climate, the SWAN nests were defined with increasing resolutions of 5 km, 1 km and 100 m,” explains Séverin. “This approach allows the model to resolve fine-scale features near the coast while still accounting for remote influences to the area from far-field generated swell.”

Full spectral boundaries were prescribe from the MetOcean Solutions’ global wave model to the 5-km SWAN domain. The latter was used to force the boundaries of the 1-km SWAN domain, which in turn was applied to the boundaries of the high-resolution 100-m SWAN domain (Figure 1). All model nests were simulated in series over 39 years (1979 to 2017).

Figure 1: Snapshot of modelled significant wave height from the 5-km resolution SWAN parent nest off the Senegal/Mauritania coasts, delimited by the outer rectangle on (a). Extents of the 1-km resolution child nest are represented by the outer and inner rectangles on (a) and (b), respectively. Extents of the 100-m resolution child nest are represented by the inner rectangle on (b).

Figure 1: Snapshot of modelled significant wave height from the 5-km resolution SWAN parent nest off the Senegal/Mauritania coasts, delimited by the outer rectangle on (a). Extents of the 1-km resolution child nest are represented by the outer and inner rectangles on (a) and (b), respectively. Extents of the 100-m resolution child nest are represented by the inner rectangle on (b).

This ROMS model is an open source state of the art ocean model which has been used widely in the scientific community and industry for a range of ocean basin, regional and coastal scales. ROMS has a curvilinear horizontal coordinate system and solves the hydrostatic, primitive equations subject to a free-surface condition. Its terrain-following vertical coordinate system results in accurate modelling of areas of variable bathymetry, allowing the vertical resolution to be inversely proportional to the local depth. Two ROMS nests were defined with horizontal resolutions of approximately 6 km and 2 km for the regional and local model grid domains, respectively, as shown in Figure 2.

Figure 2: ROMS (a) regional (6 km) and (b) local (2km) computational model grids. The red lines illustrate the transect corresponding to the vertical sigma grid structures provided in the following figure. Note the bathymetry is represented with distinct colorbars in (a) and (b).

Figure 2: ROMS (a) regional (6 km) and (b) local (2km) computational model grids. The red lines illustrate the transect corresponding to the vertical sigma grid structures provided in the following figure. Note the bathymetry is represented with distinct colorbars in (a) and (b).

The terrain-following grid configuration consisted of 30 and 23 vertical levels with increased resolution at surface and near-bottom to better represent the boundary layers (Figure 3). The model was produced over 25 years (1993 to 2017), delivering 3-dimensional current, water temperature and salinity and sea surface elevation data.

Figure 3: Representation of the 30 vertical sigma levels of the regional grid domain over a cross-shelf transect along the latitude of 16.064०N.

Figure 3: Representation of the 30 vertical sigma levels of the regional grid domain over a cross-shelf transect along the latitude of 16.064०N.

Hindcast datasets offer key baseline information for project scoping, offshore and coastal design, project planning and environmental impact assessments.

For further information about MetOcean Solutions hindcast datasets, please contact hindcast@metocean.co.nz.

Modelling the dispersal and settlement of drill cuttings

Drilling operations at sea produce a mix of fine rock fragments that need to be discharged into the ocean. While inert, these fragments (known as drill cuttings) can have sediments, contaminants and drilling fluids adhering to them. To help regulators and marine managers assess the potential impact of drilling operations, MetOcean Solutions is regularly engaged to model the dispersal and settlement of drill cuttings in the marine environment at locations all over the world. 

“Drill cuttings settle on the seabed, where they can cause adverse environmental impacts,” explains Oceanographer Remy Zyngfogel. “The oceanic discharge of drill cuttings occurs over specific time periods, but their dispersal and deposition are driven by random variables such as currents and turbulence.” 

“To determine where the drill cuttings end up on the seabed, we use a variety of methods and leverage the expertise of our multidisciplinary science team. This includes modelling the hydrodynamics of the region and simulating the trajectory and the settling of the drill cuttings to the seabed. Regulators and marine managers require good knowledge of the likely footprint of  deposition and how thick the deposits will be at increasing distances from the drill site.”

Project Director Dr Brett Beamsley oversees the hydrodynamic modelling. “We use different models to produce the historical datasets needed for the studies,” advises Brett. “Oceanic and coastal currents vary according to synoptic and seasonal winds, tides and density differences. To account for this variability, and to provide robust statistical estimates of dispersal and deposition, we use historical data to recreate the actual oceanographic conditions, typically hour-by-hour for a 10-year period. We recreate these currents using the most appropriate model. For offshore studies, we use the Regional Ocean Modeling System (ROMS), whereas for smaller-scale studies at inshore sites SCHISM or Delft3D are used.” 
 

An example of 7-day mean surface current circulation and Sea Surface Temperature (°C) for the south-eastern region of Brazil.

An example of 7-day mean surface current circulation and Sea Surface Temperature (°C) for the south-eastern region of Brazil.

Remy uses the historical current dataset to determine the dispersal of drill cuttings. “Once we have the historical currents, we use a particle tracking model to trace the dispersal and deposition of drill cuttings for simulated discharges at different times of the year,” he explains. “Ocean currents vary with factors like seasonal winds and riverine discharges, so the depositional footprint will differ depending on which time of year the drilling is done. The size of fragments discharged into the sea depends on the rock type and the drill bit design. From an estimate of particle size, we can determine settling velocities - the finest fractions of the drill cuttings settle through the water column very slowly and become widely dispersed, whereas larger particles settle quickly and much closer to the discharge location.”

Example deposition thickness for drill cuttings discharged from a marine location. The spatial distributions of deposition thickness are color-coded with values in mm on each contour line in four zoom views: 100x100 km (top left), 10x10 km (top right), 1x1 km (bottom left) and 100x100 m (bottom right). The release site is indicated as a black cross. 

Example deposition thickness for drill cuttings discharged from a marine location. The spatial distributions of deposition thickness are color-coded with values in mm on each contour line in four zoom views: 100x100 km (top left), 10x10 km (top right), 1x1 km (bottom left) and 100x100 m (bottom right). The release site is indicated as a black cross. 

“The modelling represents what is likely to happen statistically, over long time periods. Naturally, for any given discharge, the drill cuttings will disperse according to the flow conditions at the time. For example, if discharge occurs during high current flows, the drill cuttings will be transported further, and the deposition will be more spread out. If current velocities are low at the time of discharge, the cuttings will accumulate closer to the discharge point.” 

Where pre- and post-drilling sediment samples have been taken, it is possible to verify the dispersal modelling. 

“We often use barium as a tracer,” explains Remy.  “Drill cuttings contain elevated concentrations of barium from the drilling fluids. This makes barium an ideal tracer of discharged cuttings. Seabed samples taken before and after drilling can be used to determine the change in barium concentration and thereby verify the modelled deposition of the cuttings.“

“The modelling provides a statistical representation of possible outcomes, taking into account the natural variety of current flow conditions. The modelled results typically show good agreement with observed barium levels, which means that operators and regulators can confidently use the modelling to determine the extent of potential adverse effects. This information is used both when applying for permits and post-permit, in the design of environmental monitoring programmes.” 

Contact us if you would like to discuss modelling the discharge of drill cuttings or historical current data for your drilling location.

Storm watch helps safe management

Forecasts of wind and wave conditions are vital for effective and safe management of near- and offshore operations. MetOcean Solutions has developed a warning system based on ensemble forecasting, which allows us to provide warning of upcoming severe wind and wave conditions for up to 7-day horizons, thereby helping operators plan for safe and efficient management.

Accurate high-resolution forecasts of wave conditions at local scales can be done using nested or grid-refining models such as SWAN (Simulating WAves Nearshore). Such forecasts capture local wave transformation and dissipation, and can be done at a reasonable computational cost. However, at horizons beyond 2-3 days a forecast inevitably suffers from the onset of chaotic uncertainty that is a physical characteristic of the atmosphere-ocean system. 

Ensemble forecasting is a method that quantifies this uncertainty in longer-range forecasts, providing probabilistic guidance for management decisions. MetOcean Solutions can customise a forecast warning system for any offshore or nearshore location based on the 7-day forecast wind speed, significant wave height (Hs) and maximum individual wave height (Hmax). The method used to estimate extreme Hmax accounts for the long-term uncertainty of the severity of the environment and the short-term uncertainty of the severity of the maximum wave of a given sea state, complying with the International Organization for Standardization (ISO standards).

Example of Storm Watch programme. T indicates present time.

Example of Storm Watch programme. T indicates present time.

We use such ensemble forecasts to provide the best possible site-specific warning to clients of upcoming severe conditions, using pre-set thresholds to define the level of alert. 

Up to 60 wind and wave ensemble forecasts can be used to support a storm watch programme.  

An example of email alert is illustrated below. All components of the email can be customised upon request.
 

Example of Storm Watch alert email. 

Example of Storm Watch alert email. 

Storm watch guidance. Orange shading indicates when the alerting thresholds are exceeded. Wsp: windspeed. Hmax: maximum wave height. Hs: significant wave height. 90 PCTL: 90th percentile. 

Storm watch guidance. Orange shading indicates when the alerting thresholds are exceeded. Wsp: windspeed. Hmax: maximum wave height. Hs: significant wave height. 90 PCTL: 90th percentile. 

Wave height warnings. Red shaded area represents the incoming wave direction for which thresholds are exceeded.

Wave height warnings. Red shaded area represents the incoming wave direction for which thresholds are exceeded.

MetOcean Solutions can set up a storm watch programme for any location. For more information, or to discuss your site, contact us at enquiries@metocean.co.nz.

MetOceanView - making the offshore oil & gas industry safer and more efficient

Worldwide, a variety of offshore oil and gas companies use historical data from MetOceanView to understand the environment they work in. Packaged up in the site’s ‘hindcast app’, historical wind, wave and current data is summarised in an easy-to-access format that users can download and integrate into their operational planning.

“The offshore oil and gas industry needs access to reliable site data,” explains Senior Oceanographer Dr Rafael Guedes. “Nowadays, many data sources are available, and the industry needs a robust web platform where they can easily access, browse and download time-series from some of the best hindcast data sources available around the globe. To meet their needs, we set up a hindcast downloading app within our MetOceanView web service.”

Reliable data

The hindcast app provides access to an extensive compilation of data, going as far back as 1958 for some of the datasets.

“We host some of the most reliable global ocean and atmospheric reanalysis data sources in the world,” adds Dr Guedes. “These include NOAA’s CFSR V1 and V2, Hycom from the National Ocean Partnership Program (NOPP) and JRA-55 from the Japanese Meteorological Agency (JMA). In addition, we also provide MetOcean Solutions’ in-house WAVEWATCH III wave hindcast datasets.”

Gaining efficiency

Dealing with huge datasets is not easy, and to set up a useable service, practical obstacles had to be overcome.

“One common problem when accessing historical data is that the volume of data in gridded datasets can be very large,” says Dr Guedes. “For example, a subset of the HYCOM dataset we host comprises about 2.6 trillion individual data points for each variable. Reading long-term time-series from such enormous datasets can be very slow. To make a user-friendly service, we came up with an efficient process to speed up the reading, so that datasets that used to take more than two hours to download could be read in just five minutes.”

One-stop-shop for ocean data

The service works by hosting a range of reference datasets in our servers, giving the client access to unlimited data from all available global datasets as well as MetOcean Solutions’ wave and current model outputs.

“We provide a user-friendly map-based web interface where the user can inspect the different data sources and request time-series for any available grid location,” adds Dr Guedes. “The results are generated without human intervention and delivered within minutes in standard file formats, a link to which is sent directly to the user’s email.”

Data for safer operations

The hindcast app gives access to historical ocean temperature, current, elevation and wave data, as well as atmospheric parameters such as wind, temperature and precipitation.

“Accurate wave, wind and current information is essential for anyone operating offshore,” explains Dr Guedes. “Oil and gas companies use the hindcast data for a range of purposes, including determining the potential operational conditions for offshore locations and ensuring safety at sea.”

The hindcast data subscription service allows customers to browse map views of global datasets with descriptions of the variables that can be downloaded. Grid points show the exact location of each data point. Time-series are provided in either CF-compliant netCDF files or a format specially requested by the client. Wave hindcast data can be downloaded as time-series of spectral parameters or as two-dimensional, frequency-direction wave spectra. This allows a comprehensive description of the modelled wave field over the entire globe. For example, the spectra shed light on the multiple wave systems influencing wave conditions at a certain location and given time.

Making our clients’ life easier

This is the second year of delivering online historical metocean data services to Shell.  “We’ve found the global hindcast portal very valuable,” states Octavio Sequeiros, Shell Metocean Engineer. “Previously, to obtain data for a given location we had to create a specific purchase order for each request. Now, unlimited high quality historical data for any location are just a mouse-click away.

“The fast data download has made our planning easier, more efficient and cost-effective” continues Mr. Sequeiros. “The app is easy to use, and because it provides map layers along with the data grid locations, we can inspect areas and do a few queries before we decide to download time-series. Many summary statistics are shown in tile format, which means we can get a sense of the data before committing to downloads. We mostly use the time-series of wave parameters and wave spectra. On these, we run our own statistics in-house to obtain operational and design criteria for preliminary studies of new potential sites for oil and gas exploration. Our goal is to get workability predictions using accurate modelling.”

High level statistics from each of the datasets hosted by MetOcean Solutions is available via our MetOceanView interface.

Sea surface temperature snapshot from CFS dataset.

Sea surface temperature snapshot from CFS dataset.

Sea ice area snapshot from CFS dataset.

Sea ice area snapshot from CFS dataset.

Eastward wind snapshot from CFS dataset.

Eastward wind snapshot from CFS dataset.

Sea surface wave significant height snapshot from MetOcean Solutions’ dataset.

Sea surface wave significant height snapshot from MetOcean Solutions’ dataset.

Validation of tool for safer and more efficient offshore oil & gas vessel operations

The MetOcean Solutions' tool can predict conditions that are unsafe for FPSOs.

The MetOcean Solutions' tool can predict conditions that are unsafe for FPSOs.

A paper detailing research carried out at MetOcean Solutions has just been published in the Ocean Engineering journal.

The research, done by Ian Milne, Sebastien Delaux and Peter McComb, presents the validation of a tool used to predict the behaviour of the large vessels used for the processing and storage of oil and gas in remote and deepwater offshore locations under different metocean conditions. 

Floating Production, Storage and Offloading (FPSO) and Floating Liquid Natural Gas (FLNG) vessels are used around the world. These huge vessels (lengths of up to 300-400 m) are moored using a turret system, which lets the vessel rotate around the mooring fixed to the seabed. Once tethered, the vessels are typically left for up to 25 years in one location from which they are only moved if the safety of operations is threatened. 

The combined forces of wind, waves and currents determine the alignment of the vessels. Therefore, the ability to forecast headings is important to operators as certain directions could result in roll motion which may compromise safety and hence require operations to be shut down. 

Supported by a research and development grant from Callaghan Innovation, MetOcean Solutions has developed a tool for the prediction of vessel heading. The paper details the validation of the tool using measurements from an operating FPSO.

"The model predicted the vessel heading within an accuracy of 5% for a range of environmental conditions," states Dr Sebastien Delaux. "It is great to have a good validation, and we are looking forward to finalising the tool and making it operational, so that we can help operators identify dangerous conditions. The tool will also be useful in planning stages to assess the operability of an FPSO for a particular site." 


Ian Milne is now with the University of Western Australia.
Data for the validation of the tool was provided by OMV New Zealand.
Click here for details of the Callaghan Innovation Research and Development Grant.  
The full journal article can be found here