Preferential weld corrosion offers a uniquely different mitigation challenge to operators of high throughput oilfield production in carbon steel pipelines. This has a significant impact on the expected lifetime of the pipeline and thus will require chemical inhibition programs to control such localized corrosion effects. As a part of OPEX these programs require field optimization whilst providing the desired level of corrosion protection at minimum inhibitor dose rate.A low dose corrosion inhibitor has been developed that inhibits sour corrosion of individual weld components of pre-corroded steel coupons prepared from pipeline material. Metallurgical analysis of the weld section extracted from the pipeline was performed which illustrated unusual composition of the material.The lower corrosion inhibitor dose also reduces the influence of secondary effects (including emulsion and foaming) eliminating the need for specialized formulation additives and the injection of additional chemistries. Due to the low water cut and the stratified flow regime of a subsea pipeline the partitioning behavior of the product was an important consideration during product development. Since the treatment of bacteria in the pipeline was necessary the compatibility of the inhibitor with the incumbent biocide was critical.This paper details the test work performed to develop a new inhibitor to prevent weld corrosion under sour conditions. The inhibitor was evaluated in numerous performance under including kettle tests high pressure autoclaves partitioning and autoclave weldment corrosion tests.

Nickel-Aluminum Bronze (NAB) and Copper-Nickel alloys (CuNi) are commonly used in seawater environment in raison of their strength combined with a good corrosion resistance and a high resistance to biofouling. However localized corrosion failures have been reported often attributed to abnormal service conditions. The effect of several service condition parameters on the localized corrosion of NAB and CuNi alloys 90/10 and 70/30 have been investigated in natural seawater. It includes flow conditions (flowing quiescent and stagnant) chlorination sulphide pollution and crevice geometries. Both indoor and outdoor exposures (biodeposit promoting conditions) have been tested in temperate and in tropical seawaters. The global stability of the protective oxide layer of the tested copper-based alloys was mainly affected by sulphide pollution in aerated seawater (general corrosion). Under the tested conditions localized corrosion under-biodeposit clearly appeared as the critical failure for the tested alloys. The conditions in which biodeposit appeared critical for copper-nickel alloys was investigated. The current for cathodic protection of NAB in natural seawater have also been investigated as function of flow rate. 

Accurate knowledge of corrosion location severity cause and growth rate is critical to pipeline integrity and in‑line inspection (ILI) is widely regarded as the most reliable and convenient method of obtaining such knowledge. Much industry effort has therefore centred on improving the metal loss detection and sizing capabilities of ILI tools.However when ILI data are lacking or unattainable operators must seek alternative ways to monitor the integrity of an asset. For managing internal corrosion Internal Corrosion Direct Assessment (ICDA) is perhaps the best known alternative. ICDA employs the engineering analyses of corrosion and flow modelling to identify areas at high risk from internal corrosion. The highest priority areas are excavated and directly examined in order to establish the condition of the pipeline. This combination of corrosion and flow modelling can be used to provide detailed corrosion predictions but in the absence of ILI data selection of excavation sites can be problematic. The inherent randomness and uncertainty in the models means that the outputs must often be overly conservative; consequently ICDA can be a costly process with no guarantee of quality.The shortcomings of ICDA (and related methods) create a need for a more reliable and accurate corrosion prediction solution which does not require a pipeline to be inspected using ILI. This paper explores the use of Bayesian Belief Networks (BBNs) for this purpose. BBNs are graphical models capable of integrating expert knowledge and data into a single system; ‘expert knowledge’ is captured through industry standard corrosion modelling techniques while ‘data’ is captured through historical ILIs for piggable pipelines. A trained BBN can then be used to make predictions for pipelines without ILI data based on a knowledge of their operational conditions alone.Using case studies on real pipelines it is demonstrated that BBNs can lead to more intelligent predictions of internal corrosion behaviour and improved pipeline integrity management decisions.