Several gas basins within North America are under-going a period of infill drilling in order to supply the increasing demand for natural gas. It is not uncommon for an operator to have hundreds, if not thousands of infill candidates from which to choose. Is there a practical way to high-grade infill locations within a particular basin or field? This paper presents several practical techniques to high-grade infill drilling opportunities when faced with large data sets and little time. We will present results for the Mesaverde in the San Juan Basin, the Morrow in the Permian Basin, and the Cotton Valley in east Texas.

We calculated the infill potential for each of the three example formations. Based on our experience, we have found that comparisons between actual and predicted individual infill well performance can vary significantly. Therefore, ranking infill candidates on predicted individual well performance may not necessarily yield the best overall results. Poor wells, predicted to be good wells, may still be drilled and good wells, predicted to be poor wells, may not be drilled at all.

Alternatively, when considering an infill drilling program as a whole, we have found that the predicted performance for the group can be quite accurate. In this paper, we will present a method to divide a basin or field into smaller areas and predict the distributions of infill performance as a group for the smaller areas, rather than individual wells. We will then present two methods to rank the small areas to achieve the most economic results. The first method ranks the areas based on the average of the distribution. The second method uses decision tree analysis to calculate a typical infill well in an area using the P10, P50, and P90 values from the distribution.

We considered actual recent drilling programs in each of the three formations, used the above techniques to eliminate predicted uneconomic wells, and compared the actual to predicted drilling program results. We found that the finding and development costs were lower, return on investment was higher, and the success ratio was higher when the techniques presented in this paper were used to high-grade drilling opportunities.

The results of a study applying this analysis technique can be used when budgeting and planning near- and long-term drilling programs.

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