| Summary: | Master's Project (M.S.) University of Alaska Fairbanks, 2018 Directional well planning has gained special attention in the Alaska North Slope (ANS) as operators are being compelled to drill increasing numbers of wells from already congested pads because of low oil prices, Capex restrictions, and environmental regulations. This research focuses on two major components of directional well planning: anti-collision and torque and drag analysis in Schrader Bluff, Milne Point. The drilling pattern at the ANS implies very high wellbore collision risk, especially at the shallower section, which affects the safety of drilling operations. However, satisfying anti-collision norms is not the solitary step towards successful well planning. Integration of anti-collision results with torque and drag analysis is essential in evaluating the safety and feasibility of drilling a particular well path and avoiding drill string failures. In the first part of the study, three well profiles (horizontal, slant, and s-shaped) were planned for each of the two new targets selected in the Schrader Bluff OA sand. Initially, this part of the research compared the performance of the newly developed Operator Wellbore Survey Group (OWSG) error model and the industry-standard Industry Steering Committee for Wellbore Surveying Accuracy (ISCWSA) error model. To provide effective guidelines, the results of error model comparison were used to carry out sensitivity analyses based on four parameters: surface location, well profiles, survey tools, and different target locations in the same sand. The results of this study aid in proposing an improved anti-collision risk management workflow for effective well planning in Arctic areas. The second part of the study investigates the drillability of the well paths planned using the improved anti-collision risk management workflow. Furthermore, this part of the research aims at defining the end point limits for critical well planning parameters, including inclination and dogleg, such that within these ...
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