Data Driven Risk Analysis and Production Forecast Deration for Matrix Bypass Events in the West Sak Oil Pool, Alaska North Slope

Abstract

West Sak is a shallow viscous oil reservoir located partially within the Kuparuk River Unit on the North Slope of Alaska. The poorly consolidated reservoir is prone to sand production, leading to a significant risk for the development of void space conduits, locally known as matrix bypass events (MBEs). MBEs result in pattern breakage and lost production capacity, and this needs to be accounted for in production forecasting. In this study, a data-driven analysis is performed to identify factors that cause differential risk for MBE formation in each well. This analysis is then used to inform the creation of a tool that determines the expected production impacts of future MBEs and derates the forecast accordingly. The well patterns and MBE history in the West Sak reservoir are analyzed for differential risk based on sand geomechanics and producer/injector well completions. Specifically, the B sand was found to have the highest MBE risk due to its lower geomechanical strength, the D sand was found to have a significant yet lesser risk, and the A sand was found to have negligible risk. MBE risk is greater for patterns with horizontal production laterals without sand control and is negligible for horizontal producers with sand-exclusion screens or vertical producers. MBE risk is reduced when vertical injectors are used instead of horizontal injection laterals. This history is used to inform the development of MBE risk type curves based on the fatigue life distribution family of curves. These curves are used as input into an MBE deration forecasting tool, which produces a range of risk-informed MBE schedules. Based on each schedule, the tool "breaks" and "repairs" patterns accordingly, determining production losses based on allocation to each pattern. These individual production loss forecasts are then averaged to provide the expected outcome for forecast deration attributed to MBEs. The tool was successful in developing reasonable deration expectations on a well-by-well basis. The work done offers a probabilistic workflow to predict well downtime due to MBEs. Data-driven evidence is provided for factors that influence MBE risking, providing a means to capture expected production losses. This evidence proves to be consistent with physical models of this enigmatic phenomenon and informs future development opportunities to mitigate this risk. The approach pursued here can be applied to other known risks to production.