Eagle Ford shale formation exhibits highly variability hydrocarbon production rates and EUR within small areas, indicating a highly heterogeneous reservoir. Attempts to determine performance drivers among geological, production or completion data points have produced inconclusive results. For example, production for one cluster of nearby wells may be strongly correlated with proppant quantity, while the trend is not valid for a group of similar wells a short distance away. A more widely valid set of correlations could improve engineering efficiency and productivity across the play.
Multivariate statistical modeling has indicated that wellbore architecture factors influence well performance. Such models have determined relative influence of such factors as fracturing fluid type and volumes, proppant sizes and volumes, etc. On the wellbore architecture side, prior studies found that surface latitude and longitude are among the strongest drivers. However, these studies largely omitted consideration of the third dimension (relative vertical location in the reservoir).
This study evaluates productivity influences from azimuth, dip, porpoising, and TVD from heel to toe (vertical zone coverage). It also reconsiders previously studied factors (such as fracturing fluids and proppants) with a considerably larger body of data—especially longer-term production data—than was available for the prior studies. The goal is to determine geological, wellbore architecture, and completion factors that show statistical significance as performance drivers, and where they are applicable if the results vary across the play.