Dashboard for visualization, evaluation and modeling of wellbore and field H2S production
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- Master's theses (TN-IEP) 
For several years, continuously increasing amounts of hydrogen sulfide (H2S) are being produced from numerous fields on the Norwegian Continental Shelf as a result of reservoir souring. Reservoir souring – increasing concentration of H2S in production fluids from initially sweet reservoirs – is, typically, encountered after the breakthrough of seawater that is injected for higher recovery purposes. Failure to control and mitigate elevated H2S production may result in serious health issues of operating personnel, loss of production liquid quality and amount, as well as escalated operational expenditures. Despite the importance of the question, modeling and prediction attempts of reservoir souring suffers from less reliable outcomes let alone its mitigation approaches, which could be attributed to the limited understanding of factors governing increased H2S production.To address the challenge of understanding the factors influencing and/or prohibiting H2S production, the aim of building a dashboard for visualization of relevant reservoir souring data has been set. Thus, the main objectives of the work to achieve the goal are defined as follows:• Gather necessary data for H2S production evaluation;• Build a platform in Tibco’s Spotfire tool based on the collected data that allows charting interactive and flexible 2D visualizations;• Propose a structure for the evaluation of H2S production;• Incorporate developed H2S production models (correlations).Current work presents a workflow for building dashboard for H2S production evaluation where gathering, cleaning and manipulation of necessary data are done within Spotfire. The evaluation of H2S production data is performed in three interactive levels, namely field, reservoir and wellbore levels. Field level contains the analysis for overall comparison of fields in question. Reservoir level illustrates the relationship between water cut and H2S production per formation. Most of the analysis was carried on wellbore level owing to data availability and quality. Cumulative H2S vs. cumulative seawater plots are generated for all wellbores and cumulative H2S is mapped per wellbore where areal variety in oil composition can be investigated. Besides, ion data analysis is also carried out and more accurate seawater fraction calculation is suggested.Developed empirical correlation for matching H2S production history is integrated into the dashboard and finally, a workflow for integration of dashboard with SourSim®RL prediction results through H2S production optimization tool is proposed.
Master's thesis in Petroleum Engineering