Quantifying uncertainty in infill well placement using numerical simulation and experimental design: case study

Abstract

The risky nature of petroleum exploration and production requires that the decisions on reservoir management must consider uncertainties and risks associated with all proposed development programmes. The primary objective of the case study was to evaluate infill drilling potentials. However, the selection of type and placement of the proposed infill wells has been a challenge due to the presence of large number of uncertainty. The study utilized numerical simulation, pressure, and saturation maps to determine infill well location and its optimal placement within the reservoir. Evaluation and selection of infill opportunity was carried out by simulating reservoir incremental oil production and water breakthrough time from vertical and horizontal wells completed within the reservoir sub-regions. For proxy modeling, Placket–Burman and uniform design were integrated. Quadratic response surface was developed and validated. For uncertainty quantification, a full Bayesian treatment of uncertainty was performed using Markov Chain Monte Carlo. The posterior summaries of the parameters along side their uncertainties given by P2.5 %, P10 %, P50 %, P97.5 %, and P90 % quartiles were identified for investment decisions. The methodology is straight forward, easy and can be applied in other fields for the assessment of infill opportunity involving infill location, selection, and placement as well its associated risks for optimal return on investment.