Localized internal corrosion,paraffin/wax deposition,microbiologically induced corrosion or MIC,andsolids accumulation are some of the primary issues throughout a pipeline's lifecycle,especially,at low flowconditions.Although significant progress has been made in the development of methodologies and standardsfor detecting internal corrosion in different types of pipelines,little work has been done on providing cost-effective methods and technologies for the implementation of preventive corrosion strategies.Pigging andchemical inhibition continue to be the first choice of oil and gas producers in addressing asset integrity andflow assurance issues.This paper describes an Artificial Intelligence(AI)technology that enables operatorsof oil and gas gathering facilities to transport produced fluids as a sequence of alternating controllable fluidbatches to remove stationary beds of solids or soft wax from flowlines and pipelines,including unpiggablelines,without human input.The AI technology is used to determine fluid batch launch times to maximizethe system performance.A brute-force search algorithm was developed for this purpose to maximize thenumber of batches launched during one operation cycle.An example is presented to demonstrate the systemoperation in an offshore oil gathering system.Pigging and chemical inhibition costs can be substantiallyreduced,and the useful life of pipeline infrastructure and facilities can be extended using the proposedtechnology solution at all stages of field development.
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