Evaluation of a Statistical Method for Assessing Infill Production Potential in Mature, Low-Permeability Gas Reservoirs

Abstract

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.

New Methods for Determining Infill Drilling Potential in Large Tight Gas Basins

“…Guan et al (17)(18)(19) have systematically evaluated the accuracy of the moving window technique and they concluded that this technique can accurately predict infill well performance for a group of infill candidates, often to within 10%. However, predicted infill potential for individual wells can be off by more than +/-50%.…”

“…In an effort to explain why the fast method does not accurately predict infill well performance for certain individual wells, Guan et al (17)(18)(19) closely examined the wells for which the technique overestimated or underestimated performance by more than 50% in a test data set and they found that the primary reason for inaccurate predictions is unsampled high local variability in permeability. For example, the fast method will underestimate the performance of an infill well offsetting a low-permeability well if there is a high permeability located nearby that is not sampled by a well.…”

Infill-Drilling Potential in Tight Gas Reservoirs

“…So, According to Eqs. (5) and (8), we should get a straight line by plotting cumulative production versus a certain function of time.…”

“…Based on Eqs. (5) and (8), we should plot cumulative production versus f'^ for bilinear flow and i"^ for linear flow. In majority of cases, we observe that linear flow works the best.…”

“…The statistical drainage area and estimated ultimate recovery data were combined to estimate the potential reserve growth with 40-acre development. Guan et al [4,5] used the statistical moving window technique to evaluate the inflU candidates. The research evaluated the accuracy of moving window method which has been used in the tight gas resei"voir to assess the infill well potential.…”