Estimating corrosion growth rate for underground pipelines is a non-linear multivariate problem. There are many potential confounding variables such as soil parameters cathodic protection AC/DC interference seasonal / climate conditions and proximity to unique geographic features such as wetlands or polluted environments. The work presented provides an approach for estimating underground corrosion growth rates using a dataset of observations from a North American pipeline operator. Extensive geospatial data is utilized that has been obtained from public and private sources and extrapolated using Inverse distance weighted (IDW) interpolation. This work presents a model using IDW to estimate parameters involving soil interference geography and climate factors for any location in North America.Using this data this work then presents several different machine learning approaches including Generalized Linear Models eXtreme Boosted Trees and Neural Networks. All three provide an accurate estimation for corrosion growth rates for an underground asset at any latitude and longitude pair in North America. Each method comes with potential benefits and pitfalls specifically; trade-offs between model accuracy and transparency. This work presents a framework for comparing geo-spatial and machine learning estimates. Findings and a framework are provided for owners to assess how to think machine learning on their own assets.

The control of multiphase flow corrosion in oil and gas industry is one of the biggest challenging tasks. Since the 1990s, several organizations have established and operated large-scale flow loops to simulate and reproduce the field service environment of oil and gas pipelines. Based on comparison and investigation of the above loops, a new and advanced system, including several four inches internal diameter loops for studying corrosion under multiphase flows, was successfully built by us. By using this system, multiphase flows with various combinations of gas, water, oil and sand can be realized at the highest temperature of 140 oC and the highest pressure of 10 Mpa. Moreover, some loops in this system can adjust pipeline at different angels from 0 to 90°, which allow horizontal/vertical/sloping conditions to be simulated in laboratory. Many advanced measuring and monitoring technologies, such as Particle Imaging Velocimetry (PIV), high speed video camera and LPR/ER probe, are employed for simultaneously recording flow events and corrosion rates. An inhouse plane three-electrode probe is employed for conducting in situ electrochemical measurements. Such technologies would allow deep researching of corrosion behaviors and mechanisms in multiphase flow environments. Moreover, a new software based on Fluent and the existing multiphase corrosion models was developed to realize the numerical simulation of multiphase flow in loop. 

The Bureau of Reclamation has encountered challenges with coatings on pump casings. The casings are exposed to aggressive erosion conditions due to the suspended solids such as sand and debris in the water.