As operators shift their focus toward operating within cashflow, understanding the true potential of these unconventional resources is becoming increasingly important. Simultaneously, accurate modeling of EURs in shale wells is becoming increasingly complicated. There are multiple factors at play for this increase in complexity, key amongst them, are well interactions. Well interactions or interference have increased with the concentration of field development in core areas of various basins and have completely changed with production behavior in shale wells. The present paper handles this multi-variable problem by incorporating well design, completion and petrophysical variables in a prediction model. Furthermore, the analysis is presented from a viewpoint of parent, child, parent/child and co-completed wells to accurately understand the variability in the driving factors.

Terminal decline rate in shale wells is the decline rate wells settle at once the pressure transient reaches the boundary of the well. At this point, the well transitions to a boundary dominated flow regime and continues to drain from a fixed area. Estimating the rate of terminal decline is critical in accurate EUR modeling because changes in transition point can have a significant impact on production behavior of the well and in-turn EUR. The present paper attempts to predict the transition point using an ACE Non-Linear Regression model which is trained on a large multi-variate dataset. Variables incorporated in this analysis include terminal decline month, gas-oil-ratio based of the first three months of production, horizontal length, oil EUR, proppant per foot, average distance from the base of the producing zone, nearest neighbor mean spacing, and hydrocarbon in-place. In order to determine spacing status and nearest wellbore distances, a segment-wise analytical distance approach was taken. These distances and spacing status flags were incorporated into a multi-variate model in-order to model terminal decline rates.

The transformations observed from the model showed high dependence on terminal decline month and oil EUR. However, this was less pronounced in parent/child and child wells. In parent/child and child wells completion metrics and HCIP more significantly influenced production behavior. Specifically, child wells saw a higher dependence on first three-month GOR and lateral length compared to parent/child wells which had a higher dependence on proppant per foot and average distance from the base of the producing formation. Additionally, spacing showed a moderate impact on transition point and associated terminal decline rates, but overall increased spacing caused a delayed transition point and consequently a lower terminal decline rate. Understanding how cause-and-effect relationships between parent and child wells differ offers a unique perspective into production behavior and consequently provides better insights into infill wells placement and production prediction.

The present paper offers a unique perspective in looking at a key decline variable, transition point, for shale reservoirs. By using multivariate analysis, it incorporates the incremental complexity of the modeling effort and attempts to provide best practices in understanding the impact on production behavior. Furthermore, by incorporating a segment-wise analytical distance approach to determine spacing, the paper adds to the existing body of literature by providing a new perspective for a well interaction standpoint and defines the cause and effect relationships within.

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