Background. Identifying the locations and amounts of unproduced gas in mature reservoirs is often a challenging problem, due to several factors. Complete integrated reservoir studies to determine drilling locations and potential of new wells are often too time-consuming and costly for many fields. In this work, we evaluate the accuracy of a statistical moving-window method (MWM) that has been used in low-permeability ( tight) gas formations to assess infill and recompletion potential. The primary advantages of the technique are its speed and its limited need for data, using only well location and production data. Method of Approach. To test the method, we created a number of hypothetical reservoirs and calculated infill well potential using a reservoir simulator We used the MWM to analyze these data sets, then compared results to those from the reservoir simulations. Results. The results validate empirical observations made using MWM during field evaluations. Depending on the level of reservoir heterogeneity, the MWM infill predictions for individual wells can be off by more than ±50%. The MWM more accurately predicts the production potential from a group of infill candidates, the MWM, however, more often to within 10%. We describe a procedure to estimate the number of wells needed to predict production potential to within a stipulated accuracy. The ability of MWM to accurately predict production performance for groups of wells shows that it can be a useful tool for scoping studies or identifying areas for more detailed evaluation.
[1]
J. Spivey,et al.
Practical Methods to High-Grade Infill Opportunities Applied to the Mesaverde, Morrow, and Cotton Valley Formations
,
2001
.
[2]
G. W. Voneiff,et al.
A New Approach to Large-Scale Infill Evaluations Applied to the OZONA (Canyon) Gas Sands
,
1996
.
[3]
J. E. Jochen,et al.
Practical Technique To Identify Infill Potential in Low-Permeability Gas Reservoirs Applied to the Milk River Formation in Canada
,
2000
.
[4]
G. W. Voneiff,et al.
A Tight Gas Field Study: Carthage (Cotton Valley) Field
,
1993
.
[5]
Michael Edward Hohn,et al.
Geostatistics and Petroleum Geology
,
1988
.
[6]
Duane A. McVay,et al.
Evaluation of a Statistical Infill Candidate Selection Technique
,
2002
.