Mine Site Evaluation


Surveys indicate that subsea mineral reserves are potentially huge, and contain large volumes of critical minerals. There are an estimated 250 trillion (dry) tons of subsea minerals, worth around $233 trillion US dollars. However, not all these resources are economically or technically feasible to produce, and it is important to understand how mine site economics vary.

Production Support Vessel and with Riser Air Lift System deployed, supporting harvesting from 2 subsea harvesters

Schematic by NOV (Guido Van Den Bos) of a Production Support Vessel with RALS and Harvesters deployed, offloading to a STARS via tandem (line-astern) offloading.

This article gives a basic overview of likely mine site operations for polymetallic nodules, and therefore likely production, revenues and valuation of a given site. As a primer, you should be familiar with how deep sea mining works, and the equipment required.

Licenses, Sites and Strips

A license holder may have one (or more) license blocks that permit exploration or mining of subsea minerals. License block sizes vary, but are typically between 20,000km² and 75,000km².

Given the large area of a license block, there is the potential for multiple simultaneous operations with multiple PSVs and harvesters. Consequently a license block will likely be subdivided into a number of mine sites, each of which can be harvested by a PSV. Selection of mines sites is a function of nodule densities and grades (which may vary significantly within a license block), and topography (which means that certain areas may be unproducable).

A mine site is then likely to be partitioned into mining strips. These are a proposed method to optimise harvesting, which involves planning a series of long, narrow strips which the subsea harvester travels along. This is similar to farming practises, where combine harvesters work a field in long narrow strips. Efficient calculation and optimization of these planned strips is a key factor in optimizing nodule yield.

Definition of a mining license, versus site and strips


"Production key figures for planning the mining of manganese nodules"

Sebastian E. Volkmann, Felix Lehnen

Marine Georesources & Geotechnology, Volume 36, 2018, Issue 3, Pages 360-375

Combine harvester operating a field

Harvester Operations

In conventional harvesting of polymetallic nodules using a tracked harvester, a single PSV operates one or more Harvesters at any one time, along with a single Riser Air Lift System (RALS)

Harvesters gather nodules by travelling along the seabed, and transfer collected nodules to the RALS which transports them to the surface. Nodules are temporarily stored in the hold of the PSV, until they are offloaded to a bulk ore carrier for tranport to processing and/or refining facilities.

The main factors that impact the weight of nodules harvested are:

  • Nodule density (kg / m²)
  • Width of Harvester (m)
  • Harvester speed (knots)
  • Mining pattern efficiency (%)
  • Harvester operating up-time (%)
  • RALS lift capacity (tons / hr)
  • Surface dewatering capacity (tons / hr)
  • PSV hold capacity (tons)
  • PSV offload rate (tons / hr)

The value of the nodules harvested is then a function of the grade and composition of the nodules, along with the current price and proportion of each mineral that can be refined from the nodules.

Production Support Vessel and with Riser Air Lift System deployed with 1 harvester

Note: there is a distinct difference between wet and dry tonnage of nodules. Polymetallic nodules average around 27% moisture content. This moisture is lost through a number of processes, including surface dewatering and drying. It is important to understand if processes must account for the extra weight of wet nodules (for example, RALS lift capacity) or if the nodules are dry and therefore lighter (for example, for offloading, or for composition by weight)

Mine Site Evaluator

We can evaluate a given mine site by the likely daily and annual production rates of polymetallic nodules that can be achieved given the various operating and geological factors involved.

Below is a simple calculator for a single Harvester operating at a mine site. Use the sliders to vary the various parameters that impact production:


Variables impacting the production rate of a subsea harvester
  • Collector Efficiency is the % of nodules collected in any given area
  • Collector Operating Uptime is the % of time that the Harvester is operating, versus undergoing maintenance or other non-productive time


Hourly Daily Annually
Nodules Produced 174 4171 1523390

Limiting Factors:

At a certain point, the Riser Air Lift System (RALS) that lifts the nodules from the seafloor up to the PSV, becomes the limiting factor. The RALS has a maximum lift capacity, dictated primarily by the internal diameter of the riser and the dynamics of injected air, and this becomes a limiting factor in nodule production:

Change the variables below to see the impact on production above:

wet t/hr
dry t/hr
Riser Air Lift System (RALS) diagram


Deep Sea Mining companies typically hold a number of license blocks, which will likely be harvested by PSVs operating in sub-divisions called Mine Sites, with their Harvester(s) following Mining Strip patterns. The valuation of a company is a function of the potential value of their mine sites, and how / when these mine sites will be harvested.

Mine sites vary in quality according to a number of geological, topographical and operational constraints. The most important factors are the nodule density within a site, the nodule composition (not discussed here), operational efficiencies, and various operational capacity limits. However, there are myriad further details that need to be considered when evaluating a mine site.

We hope that our simple interactive mine site evaluator helps illustrate these various factors, as well as the limitatitions in place.

Related Articles:

Phillip Gales is a serial entrepreneur who has built tech companies in various heavy industries including Oil & Gas, Construction, Real Estate and Supply Chain Logistics. Originally from the UK, he now lives in Toronto, Canada, with his wife and young family.

Phillip holds an MBA from Harvard Business School, and an MEng in Electrical Engineering from the University of Cambridge, specialising in Machine Intelligence.