Optimal Well Positioning under Geological Uncertainty by Equalizing the Arrival Time

Abstract

Water flooding uses water injection to increase oil production from a reservoir. In water flooding, the position of production and injection wells is one of key factors for high oil recovery. However, well positioning is typically planned with lack of geology information. Therefore, it is difficult to decide an optimal well position due to geological heterogeneity and uncertainty. This paper proposes a method to optimize the position of an injection well, thereby maximizing sweep efficiency by equalizing arrival times of the injected water. After estimating average watercut of all the producing wells from an injection well assumed, timeshifts of individual watercut are calculated to match the average watercut. Sensitivity is computed by using the Buckley-Leverett solution. Many equivalent reservoir models are generated and applied to consider geological uncertainty. The arrival time optimization proposed in this study can find the location of an optimal injection well, even if initial conditions are far from the solution or multiple equi-probable models considered at the same time. Also, a lot of simulation time can be saved because of fast convergence and analytical sensitivity computations. The suggested method is applicable to a reservoir that has geological uncertainty because of its calculation efficiency.

An initial study of the risk of coal-roof water flow based on the “three maps two predictions” method

“…In recent years, increases in resource requirements and the level of mechanized mining have reduced the amount of shallow coal that is available. The coal mining industry has thus increasingly focused on deep coal, with associated increases in head pressure during mining, the complexity of coalfield hydrogeological conditions and mining risks (Zhang et al, 2011;Jin et al, 2015). Therefore, understanding the risks associated with water flowing through the coal roof is necessary to prevent water-related accidents, decrease personnel injuries and fatalities and mitigate economic losses.…”