Evaluation of a statistical infill candidate selection technique

Quantifying the drilling or recompletion potential in producing gas basins is often a challenging problem, because of large variability in rock quality, well spacing, and well completion practices, and the large number of wells involved. Complete integrated reservoir studies to determine infill potential are often too time-consuming and costly for many producing gas basins.
In this work we evaluate the accuracy of a statistical moving-window technique that has been used in tight-gas formations to assess infill and recompletion potential. The primary advantages of the technique are its speed and its reliance upon well location and production data only.
We used the statistical method to analyze simulated low-permeability, 100-well production data sets, then compared the moving-window infill-well predictions to those from reservoir simulation. Results indicate that moving-window infill predictions for individual wells can be off by more than 50%; however, the technique accurately predicts the combined infill-production estimate from a group of infill candidates, often to within 10%.
We found that the accuracy of predicted infill performance decreases as heterogeneity increases and increases as the number of wells in the project increases. The cases evaluated in this study included real-world well spacing and production rates and a significant amount of depletion at the infill locations. Because of its speed, accuracy and reliance upon readily available data, the moving window technique can be a useful screening tool for large infill development projects.