Seismic vessel’s engine exhaust: Predicting, monitoring, and mitigating green house gases

Industrial generation and release of so called “green-house” gases into the atmosphere has many source components, for example: electricity generation, manufacturing, transportation, and natural resource exploration and extraction. At some stage, all these activities require some form of combustion of hydrocarbon based fuels. As is well known, the combustion process produces by-products of nitrogen (N), sulfur (S), and carbon (C) oxide gases (NOx, SOx, and COx), all of which have been claimed to contribute to apparent global warming trends.

During a marine towed streamer seismic survey, the exhaust from the survey vessel's engines produces various proportions of the gases from these three base elements. The volume of each type depends on the chemical composition of the fuel in use and the volume of fuel burned during the course of the survey. The volume of fuel burned is directly related to the amount of power required for the vessel to perform a particular task. The primary tasks required of a seismic vessel can be described in three main categories; transit, production, and standby. Each category requires different amounts of engine power and therefore the volume of fuel burned and resulting gaseous by-products in the exhaust will differ with each. For example, when a seismic ship is in transit, the main power requirements are related to the maximum speed attainable for given ocean and weather conditions. On the other hand, when a seismic vessel is in production (i.e acquiring seismic data) the main engine power requirements are a function of the total drag, or load, of the seismic acquisition spread (sources and receivers and positioning devices) that the vessel has to pull through the water at an optimal survey speed. In standby mode, the spread is deployed but the vessel is not in acquisition mode so speed is not necessarily a prime operational consideration.

In 2008, DNV (Det Norske Veritas) published a report where they described a model designed to predict the volumes of NO_x, SO_x, and CO_x   gases in a ship's engines' exhaust based upon the chemical composition of the fuel, the power efficiency of vessel's engines, the work required of the engines, and any exhaust cleaning technologies employed prior to release into the atmosphere. The output of the model is an emission index which relates the emitted volume of a particular gas to the work performed by vessel.

Fig1.  A schematic representation of the input and output parameters of the model

As part of the Polarcus "Explore Green" agenda, this model has been used to aid in ship and seismic acquisition system design parameters and identification of exhaust cleaning technologies, to pursue a goal of significantly reducing emissions of "green-house" gases from our vessels during the course of their activities. With this in mind, solutions can be broken down into two main components; enhanced hydrodynamic efficiency and effective exhaust cleaning.

Enhanced hydrodynamic efficiency refers to reducing the work the ship has to do, and therefore the power the engines have to generate, to accomplish a particular task. In transit mode this relates to the resistance of the ship's hull to moving through the water at a certain speed given a certain sea-state (wind, waves, currents, etc). In seismic production mode, it relates to reducing the overall drag developed by towing a particular seismic spread at a certain survey speed.

Exhaust cleaning technologies refer to methods of reducing harmful chemical components from the ship's engine exhaust. This can be accomplished in two primary ways; prevention of the generation of harmful gases in the exhaust and chemical reactions to transform a harmful gas component into a more benign form. In the first instance, the choice of fuel has a significant impact on the resultant SO_x content of a ships exhaust. There is a direct relationship between the sulfur content of marine fuels and the volume of SO_x contained in the exhaust.  A commitment to the use of low sulfur fuels will lead directly to a concomitant reduction in emitted SO_x gases.

In the second instance, incorporation of high specification exhaust catalytic converters can provide oxidation catalysts which use O₂ to oxidize CO to CO₂ and any residual hydrocarbons to H₂O and CO₂.  A second stage selective catalytic reduction uses Urea, (NH₂)₂CO, as a catalyst to reduce NO₂ to simple nitrogen gas. The two stage process is predicted to reduce NO₂ emissions by close to  90%, residual hydrocarbons by 80 - 90%, soot particles by over 20%, and as an added benefit an exhaust vent noise reduction of 20 - 35 dB (A).

As stated, the emission model and the choice of exhaust cleaning technologies can lead to predictions of expected reduction in component volumes of NO_x, SO_x, and CO_x gases in the seismic survey vessel's engine exhaust for any given activity. The real test, however, is to monitor a ship's performance against the model predictions. At Polarcus we have instituted a suite of onboard measuring and monitoring systems to allow us to collect data on the component gas volumes in our ships' engine exhaust. These systems are continuously in operation to monitor the state of the exhaust for all of a ship's activities. In Q2 2010 Polarcus received a DNV Vessel Emissions Qualification Statement. This document qualifies the Polarcus emissions reporting methodology and accuracy of data, verifying the company's ability to predict the exhaust emissions footprint for any project and then, post-project, to subsequently provide actual emissions measurements.

Fig2.  The emission reports for our first two survey projects, one for the Polarcus Nadia and the other for the Polarcus Naila

There are several interesting features to note from these data. First, the Polarcus Nadia was the first operational vessel for Polarcus and thus our first experience in attempting to monitor and mitigate our gaseous emissions. This is apparent in two metrics in the data, the reduction in NO_x values for the transit and production periods. During the transit a lack of sufficient quantities of Urea impacted the efficiency of NO_x reduction highlighting the importance of a sustained supply chain for this material. During production sufficient Urea was on hand so that even though the power requirements were significantly greater than during the transit, the overall NO_x reduction was greater. This production period was also the first operational activity for a Polarcus vessel. That time was an initial period for engineers to learn to interact with the feedback relationship between the operational performance of the vessel and emission mitigation efficiency. The results of this learning curve show up in the improved performance of the Polarcus Naila which was the second vessel to enter into operational service.

As subsequent projects were conducted more accurate data was acquired which helped evaluate the accuracy of the emissions model to the different operational situations of the vessel.

Fig3.  The emission tracking over the period of one of the Polarcus Naila's projects offshore Norway in 2010

There are many interesting features in this data but two in particular deserve comment. The trend in emitted NO_x is directly correlated with the activity of the vessel being much higher during acquisition (i.e. towing a heavier load) versus periods when the acquisition spread was not fully deployed. In either case, the percent of NO_x reduction remained near constant indicating a constant efficiency in NO_x mitigation. The second noticeable feature is the constantly small volumes of emitted SO₂ gases. This is directly attributed to a concerted effort to procure the lowest sulfur content fuel available in the market. On average the Polarcus fleet has used fuel with less than 0.15% sulfur content during the first year of operation.

A year later the work-to-emissions feedback system is still being fine-tuned on a project by project basis. However, the data collection so far proves that the Polarcus fleet has approximately 540% less emission than the competitions fleet of seismic vessels. The results provide a real time ability to optimize operational performance during the course of a survey in order to reduce the overall emissions footprint. The data will also prove valuable to clients who wish to document or report specific emissions measurements such as NOx gases, or who are seeking to meet specific emissions reduction targets.