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Many asset owners struggle to identify the root cause of fluctuating corrosion rates due to unreliable inspection data. Facilities worldwide are tasked with monitoring thousands of Condition Monitoring Locations (CMLs) with established NDE techniques such as manual ultrasonic testing and radiography. While these techniques can provide valuable “snapshots” of the condition of particular locations, limitations and inherent errors can compound leading to ill-advised decision making. Manually taken thickness data can vary greatly and result in unwarranted complacency or excessive and costly inspections.
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Many asset owners struggle to identify the root cause of fluctuating corrosion rates due to unreliable, infrequent, or sheer lacks of quantity of inspection data to make informed decisions on asset health. Facilities worldwide are tasked with monitoring thousands of Condition Monitoring Locations (CMLs) with established NDE techniques such as manual ultrasonic testing and radiography. While these techniques can provide valuable “snapshots” of the condition of particular locations, limitations and inherent errors can compound leading to ill-advised decision making.
One of the pillars of the fourth industrial revolution (4IR) is to let machines make decisions on behalf of humans; this paper describes new technology that allows machines to decide inspection programs and field validation and testing of results. The technology described is a part of integrity management, and uses data, statistics and expert decisions to design inspection programs. These inspection programs are an important part of the safeguarding of equipment to maintain production and safety.This technology is a data-driven predictive model of material loss from corrosion, based on domain expert input and historical data in the form of non-destructive testing (NDT) tests. The technology trends is based on historical data and SME input, while accounting for uncertainties in NDT measurements, with uncertainties in historical trends and uncertainties in future trends. This produces a more realistic failure prediction to enhance existing RBIs and adds safety by improving on early detection of trends in data. In total, this enables the machine to update inspection plans autonomously, reducing the number of inspections significantly.The paper also describes how the technology can be developed further to use production data and integrity operating windows to improve predictions, deal with localised corrosion and assess if the test points on a corrosion circuit are sufficient, can be reduced in number or should be manually evaluated by adding more test points.
Knowledge technology provides energy companies with knowledgeable applications that help them make better decisions faster in all decision points. One such knowledge application (CrudeFlex) is related to supporting the decisions of purchasing certain crudes to be processed in certain refineries through properly evaluating the risks associated with processing such crudes.In this paper, we discuss the basic concepts of knowledge modeling and how specifically CrudeFlex was developed as a knowledge application, how it works and how rifineries are leveraging it to strengthen their competitive edge and proactively evaluate and manage risks associated with the crudes.The new generation of knowledge applications are powered by a combination of computational knowledge graphs and computational algorithms. These algorithms encode the expertise of subject-matter experts, such as process engineers and combine their experience with decades of historical data extracted from databases, documents, and sensors in addition to ever-growing corpus of technical research to support better decisions faster. This technology enriches and combines companies’ internal siloed data with public data to create an integrated digital knowledge layer. Engineers can evaluate and manage the risks associated with known processing and new crudes in any of their refineries.Refining engineers have easy access to knowledge related to people, equipment, vendors, crudes and more, so that they can make better, more informed decisions faster. In this paper, we show how the application of such algorithms helps the reading of hundreds of thousands of historical reports to harvest knowledge about the risks, and store the extracted knowledge in an enterprise digital knowledge layer, saving millions of dollars by enabling experienced engineers to make significantly better decisions faster through using the harvested and captured knowledge.
In order to implement an effective iron scale mitigation strategy, operators first need to identify the main source of iron in the system. This work describes a method to predict the “maximum dissolved iron” (MDI) concentration in a reservoir/production system.
Austenitic and ferritic-martensitic steel were irradiated with protons while exposed to simulated PWR primary water for 4-72 hr in 320°C water with 3 wppm hydrogen while irradiated at surface dose rates from 400-4000 kGy/s (4x10-7 to 7x10-6 dpa/s).
Microcosm is defined as “A community, place, or situation regarded as encapsulating in miniature the characteristics, qualities or features of something much larger”. By examining a “microcosm” one can look at how an overall system or market operates and infer assumptions and regard changes by looking at manageable data sets. This paper will examine a “microcosm” of the water tank recoat market. Data was collected from the website “Civcast USA”. The projects that were examined were water tank recoats in the Texas Market.
The manufacturing and field experience of high strength low alloy (HSLA) steel plates produced by Thermo-Mechanical Controlled Process (TMCP) are well defined in industry standards and literature. The TMCP method consists of a well-prescribed rolling pass schedule followed by accelerated cooling that leads to a fine-grain microstructure with the desired mechanical properties of the produced plates.Quite recently, this TMCP process resulted in detrimental local variations with hidden hardness variations on pipe ID, so-called Local hard Zones (LHZ).
Although Microbiologically Influenced Corrosion (MIC) is a critical damage mechanism that had been researched for decades in different environments, yet diagnosing a specific industrial failure to be attributed to MIC can still be challenging. The challenge of accurately identifying an MIC failure is partially due to the similarity of the failure morphology with other damage mechanisms, e.g., pitting corrosion due to chloride. Furthermore, the variously proposed initiation and propagation mechanisms for different types of bacteria may illustrate to the failure analyst that the MIC mechanisms are not yet well established. The confusion of MIC failure identification could also be aggravated by the fact that the presence of bacteria in a system does not necessarily mean that MIC is the culprit. Therefore, this paper will shed some light on the overlapping areas between MIC and pitting corrosion, especially the morphology of the attack. Moreover, several steps will be highlighted and discussed on how to correctly identify if MIC is the culprit in a specific failure.
The formation of inorganic scale deposits in numerous waters mediated industrial applications takes place by heterogeneous nucleation and crystal growth. These processes depend on the supersaturation of the solution in contact with respect to the depositing salt, on the characteristic features of the surface on which scaling takes place, temperature, fluid velocity and the presence of foreign substances. Despite the importance of the surface on which salts form, very few studies have focused on this issue.
Many protective coatings markets have recently seen high demand for higher performing coatings or linings. For example, with enhanced oil recovery, many more assets are now used throughout these processes from the oil / water separation tanks to the acid injectors. The temperatures are higher and corrosive environments are more severe. Formulation chemists are working hard at trying to push the extent of the performance of typical resin systems, but it seems that most of the development has been done and the extent of the performance available has been maximized.