Department of Petroleum Engineering, Covenant University, Canaan Land, Ota, Nigeria; Faculty of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430074, China
Orodu, O.D., Department of Petroleum Engineering, Covenant University, Canaan Land, Ota, Nigeria; Tang, Z., Faculty of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430074, China; Anawe, P.A.L., Department of Petroleum Engineering, Covenant University, Canaan Land, Ota, Nigeria
Sidetrack or recompletion time (t R) is optimized for the pair of a production and injection well simultaneously under uncertainty with respect to expected monetary value (EMV) or risked net present value (NPV) as the objective function to properly understand and shed more light on the critical parameters influencing t R. The option to sidetrack or not is also evaluated. Analysis is aided by a recent time dependent analytical waterflood performance model with respect to cumulative injected water for adequate economic analysis. There exist two zones, a productive and lower zone and a lesser producible upper zone that has low recoverable reserves, of which both zones are penetrated by both wells. The injection well enhances oil production in the production well by the displacement mechanism of waterflooding. Though sidetrack is simultaneous considering negligible time interval between sidetrack of both wells, it is actually a sequential operation with regards to the decision tree schematic. A possible outcome is, if sidetrack to produce from the upper zone fails, then no sidetrack to the upper zone through the injection well. Decision tree analysis is brought to fore considering the probability of success (POS) of continual production (injection) from (to) the producing zone and production (injection) commencement possibility for the upper zone. Uncertainty of parameters including POS in evaluating the objective function, EMV, is made possible by probable values using distributions for Monte Carlo simulation run. EMV and t R are optimized for each run by constraining t R to either, after water breakthrough time to the lower zone or from time 0. The objective function is solved with a constrained non-linear generalized gradient optimization scheme. Significant match was obtained for waterflood performance, and NPV of each terminal branch of the decision tree between the analytical approach and reservoir simulator generated data. Notably, optimal t R obtained through the analytical approach is highly dependent on POS of production and injection from (to) the upper zone. Evaluation of possible dependencies of POS is essential as regards to the sequential operation brought largely by geological uncertainties and may be to a lesser extent by the sidetrack operation based on the influence of probable pathways. Other criteria for selection of optimal time are more suitable for selection of an optimal range and not a single value. These criteria in essence, boost the EMV and cannot stand alone as an optimization tool. © 2011 Elsevier B.V.
Analytical approach; Critical parameter; Decision tree analysis; Displacement mechanisms; Expected monetary values; Generalized gradients; Geological uncertainty; Injected water; Injection wells; Monte Carlo Simulation; Net present value; Non-linear; Objective functions; Oil production; Optimal ranges; Optimal time; Optimization tools; Performance Model; Probability of success; Production wells; Recompletion; Recompletion risks; Recoverable reserves; Reservoir simulator; Sequential operations; Sidetrack; Single-value; Stand -alone; Time dependent; Time interval; Uncertainty; Water breakthrough; Water flood; Waterflooded reservoirs; Computer simulation; Constrained optimization; Decision trees; Economic analysis; Function evaluation; Injection (oil wells); Monte Carlo methods; Oil well flooding; Plant extracts; Trees (mathematics); Water injection; Well flooding; Well stimulation; Wells; Petroleum reservoir evaluation; computer simulation; decision making; hydrocarbon reservoir; Monte Carlo analysis; optimization; risk assessment; uncertainty analysis; Nucleopolyhedrovirus