Parent-child interactions have been a continual challenge for the unconventional oil and gas industry in recent years. At HFTC 2022, Devon and ResFrac co-authored a study on modeling parent-child interactions in the STACK in Oklahoma (). The parent well, two generations of children wells, and a remediation treatment in the parent well are modeled in a single, continuous ResFrac model. The continuous nature of the ResFrac modeling allowed for fluid exchanges between parent and children wells to be captured, while also requiring a holistic explanation for performance degradation in parent well post-hit. The model quantitatively described all historical observations (including damage to parent and subsequent recovery after remediation treatments) and is now suited for optimization of child well design and parent remediation programs.
The subject well pad has six wells (one parent, one first-generation child, and four second-generation children). Ratcliff et al. show the ResFrac calibration process to treating pressures, sealed-wellbore pressure monitoring data (SWPM), interference testing, and production data. The parent well experiences two frac hits, the first after one year of production, and the second after two years of production. As a result of the frac hits, the parent well exhibits a greater than 90% loss in production rate. Additionally, the children wells closest to the parent well underperform their expectations and child performance improves as a function of distance from the parent.
Several different mechanisms may cause damage in parent and surrounding children wells. For the subject wells in this study, Devon had direct evidence of “gummy bears” (Rassenfoss, 2020) in the wells and the production behavior matched the signatures of mechanisms as presented in Fowler et al. (IPTC-22194). Conductivity damage of the proppant pack occurs in the model as frac fluid interacts with hydrocarbons in the proppant pack. Historical data is matched by adjusting the potency and reaction rate of the damage reaction. In the Devon data set, the damage reaction calibrated to the first frac hit at one year was predictive of the frac hit at year two, with no adjustments, demonstrating the predictivity of the model.
Additionally, the conductivity damage in the parent fracs also inhibits production of the nearest children due to intersecting fracture networks (and hydrocarbon “leakage” from the parent well to the children wells through the fracture network during shut-in). Thus, the children wells nearest the parent are inhibited not only because of the presence of depletion but also “collateral” damage from the damage in the parent fractures. Ratcliff et al. show that the ResFrac model not only tightly matched the parent well production but also all of the children wells.
With the model fully calibrated, it can be used to assess and optimize placement and treatment of child wells offsetting depletion and/or design remediation treatments on parent wells already affected by conductivity damage. Devon was able to recover meaningful rates from the parent well in the subject data set. To model this, Ratcliff et al. use a reverse damage reaction in ResFrac and successfully replicate the regained production Devon realized. The reverse damage reaction is the same as the original damage reaction, but uses a negative potency.
Fracture conductivity damage occurring in a parent well (Note: this is a generic example, images of Devon model can be found in the SPE paper)
References
IPTC-22194. Fowler,Garrett, Ratcliff, Dave, and Mark McClure. “Modeling Frac Hits: Mechanisms for Damage Versus Uplift.” Paper presented at the International Petroleum Technology Conference, Riyadh, Saudi Arabia, February 2022. doi: https://doi.org/10.2523/IPTC-22194-MS
Rassenfoss. 2020. Solving the gummy bears mystery may unlock greater shale production. Journal of Petroleum Technology.
SPE-209152. Ratcliff, Dave, McClure, Mark, Fowler, Garrett, Elliot, Brendan, and Austin Qualls. “Modelling of Parent Child Well Interactions.” Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, Texas, USA, February 2022. doi: https://doi.org/10.2118/209152-MS