Abstract
Abstract
The phenomenon of child wells’ Estimated Ultimate Recovery (EUR) underperformance relative to that of parent wells has been well documented in industry papers and investor presentations for several years. The exact mechanisms for the differential performance between parent and child wells are difficult to resolve due to the large number of variables involved. In this case study, we share an engineering analysis on a large and consistent data set and summarize key drivers and learnings from the parent-child relationship.
A fit-for-purpose parent-child classification system was developed to consistently characterize wells as parents or children based on their spatial and development timing characteristics. A geospatial algorithm was then implemented to calculate depletion volumes around child wells prior to the start of the child well production. The results were then analyzed using a statistical approach to identify the key drivers of well performance.
The analysis yielded learnings on the relationship between cumulative oil production and variables reflecting parent-well impact. Studying this relationship led to identification of optimal timing for infill development based on depletion volumes. Additionally, we observed that long-term production performance can be reasonably inferred based on secondary performance indicators including early time GOR and Initial Pump Intake Pressure.
This case study is based on a uniquely consistent data set with a large well count in a highly developed, contiguous area. These wells were drilled at similar spacing, completed with similar fracture intensities and produced by the same artificial lift methods. Because the data set is consistent, the key drivers to child well performance, including depletion and well spacing are evident and quantifiable. All of these characteristics make for a high-quality statistical analysis and provide key learnings and rules of thumb to apply in developing future wells with the goal of improving well performance and economic results.