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Harvesting ocean energy will play an important role in supplying fossil-free energy for future generations. The oceanic environments around the world are unfortunately of the toughest possible to operate in. Most technologies use a power take-off (PTO) unit with mechanisms that are placed inside protective enclosures or sealed buoys to protect from the harsh environment in seawater. This gives a barrier from the corrosive electrolyte and biological activity that can deteriorate the components. The energy from the oceans in form of relative movements and forces are transferred to the PTOs with help from complex dynamic sealing systems.
Power Take Off steel rods are key components in wave energy. Their surfaces are exposed to among others, marine corrosion, marine biofouling, and mechanical wear. Protective coatings are sought for, and test and validation protocol for these coatings are needed. In this study metallic matrix coatings applied by laser cladding, have been tested. Accelerated testing and field methods have been employed. The goal is to use these coatings as study case for evaluation of methods itself for corrosion and wear resistance validation. The methods and preliminary results are presented and discussed. In particular: a) field test of a biofouling control strategy using mechanical scraping at different intervals; b) continuous salt spray test in three different media (conventional NaCl; artificial seawater; and natural seawater); c) cyclic potentiodynamic polarization measurement (ASTMG61) for ranking of nickel- and cobalt-based coatings and study susceptibility to localized corrosion; d) Critical crevice temperature test for nickel-based alloys (ASTMG48–D); d) Multi-degradation testing where synergy effects from wear and corrosion are considered (only discussed). The goal is to evaluate methods and experimental design to both reduce uncertainty, assist in material selection, and finally provide a pathway for final validation of PTO coatings toward a third-body certification.
Hydrocarbon production currently occurs in a variety of onshore and offshore locations. Most offshore production in shallow water (< 500 m) has reached maturity, with most of the more accessible reserves having already been exploited. As a result, exploration and production in offshore environments has been extended to deeper water (> 500 m), which usually incurs more expense and overall project risk for operators and service providers. Production from deepwater oil fields is expected to grow by 40%, to 10 million bpd (10% of total global output), by 2025.
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In aqueous carbon dioxide (CO2)-saturated environments, such as those found in geothermal energy, oil and gas and carbon abatement industries, various naturally occurring layers can be found on the internal surface of carbon steel infrastructure, such as pipelines, as they corrode in the mildly acidic conditions. Amongst the most commonly found layers are iron carbonate (FeCO3), iron carbide (Fe3C) and magnetite (Fe3O4). FeCO3 can offer corrosion protection to the underlying steel when formed under certain conditions, as too can Fe3O4. Fe3C is typically associated with enhancement of electrochemical activity of carbon steel and is revealed due to preferential dissolution of ferrite in the steel microstructure – through the formation of a porous network at the steel surface. Each of these layers play a fundamental role in the uniform and localized corrosion of the underlying carbon steel.
Precipitation and deposition of wax or asphaltenes is a commonly encountered issue in the oilfield, causing flow restrictions, compromising the integrity and performance of equipment (some safety critical), limiting access during well interventions, causing “fill” in vessels, stabilizing emulsions and sometimes enhancing corrosion due to under-deposit corrosion and increased biofouling. Developing an effective management strategy that minimizes the total cost associated with these threats requires reliable prediction of whether they will occur, their severity and their location within the production system. Such prediction typically combines the use of compositional data and phase behaviour (typically referred to as “PVT data) with Equation of State (EoS) modelling plus the experimental measurement of key parameters specific to each issue.