Determination of eccentric deposition thickness on offshore horizontal pipes by gamma-ray densitometry and artificial intelligence technique.

The extraction of oil is accompanied by water and sediments that, mixed with the oil, cause the formation of scale depositions in the pipelines walls promoting the reduction of the inner diameter of the pipes, making it difficult for the fluids to pass through interest. In this sense, there is a need to control the formation of these depositions to evaluate preventive and corrective measures regarding the waste management of these materials, as well as the optimization of oil extraction and transport processes. Noninvasive techniques such as gamma transmission and scattering can support the determination of the thickness of these deposits in pipes.

A new application of radioactive particle tracking using MCNPX code and artificial neural network.

Stirrers and mixers are highly used in chemical, food, pharmaceutical, cosmetic, concrete industries and others. During the fabrication process, the equipment may fail to appropriately stir or mix the solution. Besides that, it is also important to determine when the right homogeneity of the mixture is attained.

Inorganic scale thickness prediction in oil pipelines by gamma-ray attenuation and artificial neural network.

Scale can be defined as chemical compounds that are inorganic, initially insoluble, and precipitate accumulating on the internal walls of pipes, surface equipment, and/or parts of components involved in the production and transport of oil. These compounds, when precipitating, cause problems in the oil industry and consequently result in losses in the optimization of the extraction process. Despite the importance and impact of the precipitation of these compounds in the technological and economic scope, there remains difficulty in determining the methods that enable the identification and quantification of the scale at an initial stage.