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Collaborating Authors
Hailu, Thomas
Mitigating Multi-Bench Parent-Child Effect in Eagle Ford Play Using High Volume Preloads
Aniemena, Chigozie (BPX Energy) | Chirinos, Christopher (BPX Energy) | LaBryer, Allen (BPX Energy) | Latta, Caitlin (BPX Energy) | Moulton, Mickey (BPX Energy) | Johnson, Rebecca (BPX Energy) | Hailu, Thomas (BPX Energy)
Abstract Well performance data across several US shale plays shows that child wells typically underperform relative to parent wells (parent-child effect). The Eagle Ford shale is known to exhibit some of the most severe cases of parent-child effect with up to 60% degradation in normalized child well performance relative to parent wells. Further studies indicate that parent-child effect manifest primarily through geomechanical pathways (stress rotation, fracture asymmetry) and that sufficient repressurization of the parent wells has the potential to mitigate parent-child effect. This paper reports an industry-first application of multi-well high-volume preloads to mitigate the effect of Lower Eagle Ford depletion on the performance of child wells in the Lower Eagle Ford, Upper Eagle Ford, and Austin Chalk formations. Preload design is based on simple material balance while preload performance analysis is done within a rate transient analytics framework with relative fracability as the key variable of interest. Fracability assessment indicates that parent well depletion in the Lower Eagle Ford may degrade fracability of child wells (across multiple benches) by 65% on average even in the absence of volumetric interference. Degradation in child well fracability in turn results in up to 62% normalized EUR degradation in child wells. Preload performance analysis shows that in units with preloads, child well relative fracability exceeds that of non-preload units by an average of 61% which translates to a 65% increase in relative EUR on average across all wells. The results suggests that multi-bench infill development may benefit from high-volume preload and should be considered on a case-by-case basis. Introduction As US shale development progressed from acreage capture to full field development, operators have consistently reported child well underperformance relative to parent wells with consequent downward pressure on development program economics. Walser (2016) reports a 27% performance degradation in child wells relative to parent wells in the North Dakota Bakken shale, 30% in the Permian and 28% to 35% across various US shale gas plays. Using data from 2,000 frac hit events, a major operator reported 20% to 40% child well underperformance relative to parent wells when no mitigation steps are taken (Jacobs, 2019). These numbers may be significantly higher when parent and child wells are normalized for treatment size and lateral length since many child wells have larger treatment designs than parent wells. Figure 1 shows a comparison of parent and child well normalized EUR using company operated data in the Eagle Ford Karnes County (EUR normalized for lateral length, treatment volume and proppant concentration) revealing a 62% child well underperformance relative to parent wells.
- Research Report > New Finding (0.49)
- Research Report > Experimental Study (0.48)
- Geology > Petroleum Play Type > Unconventional Play > Shale Play (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.97)
Multi-Well Pressure History Matching in Delaware Play Helps Optimizing Fracturing for Subsequent Pads
Suarez-Rivera, Roberto (W. D. Von Gonten Laboratories) | Panse, Rohit (W. D. Von Gonten Laboratories) | Sovizi, Javad (Baker Hughes) | Dontsov, Egor (ResFrac Corporation) | LaReau, Heather (BP America Production Company, BPx Energy Inc.) | Suter, Kirke (BP America Production Company, BPx Energy Inc.) | Blose, Matthew (BP America Production Company, BPx Energy Inc.) | Hailu, Thomas (BP America Production Company, BPx Energy Inc.) | Koontz, Kyle (BP America Production Company, BPx Energy Inc.)
Abstract Predicting fracture behavior is important for well placement design and for optimizing multi-well development production. This requires the use of fracturing models that are calibrated to represent field measurements. However, because hydraulic fracture models include complex physics and uncertainties and have many variables defining these, the problem of calibrating modeling results with field responses is ill-posed. There are more model variables than can be changed than field observations to constrain these. It is always possible to find a calibrated model that reproduces the field data. However, the model is not unique and multiple matching solutions exist. The objective and scope of this work is to define a workflow for constraining these solutions and obtaining a more representative model for forecasting and optimization. We used field data from a multi-pad project in the Delaware play, with actual pump schedules, frac sequence, and time delays as used in the field, for all stages and all wells. We constructed a hydraulic fracturing model using high-confidence rock properties data and calibrated the model to field stimulation treatment data varying the two model variables with highest uncertainty: tectonic strain and average leak-off coefficient, while keeping all other model variables fixed. By reducing the number of adjusting model variables for calibration, we significantly lower the potential for over-fitting. Using an ultra-fast hydraulic fracturing simulator, we solved a global optimization problem to minimize the mismatch between the ISIPs and treatment pressures measured in the field and simulated by the model, for all the stages and all wells. This workflow helps us match the dominant ISIP trends in the field data and delivers higher confidence predictions in the regional stress. However, the uncertainty in the fracture geometry is still large. We also compared these results with traditional workflows that rely on selecting representative stages for calibration to field data. Results show that our workflow defines a better global optimum that best represents the behavior of all stages on all wells, and allows us to provide higher-confidence predictions of fracturing results for subsequent pads. We then used this higher confidence model to conduct sensitivity analysis for improving the well placement in subsequent pads and compared the results of the model predictions with the actual pad results.
- South America > Argentina > Patagonia > Neuquén > Neuquen Basin > Vaca Muerta Shale Formation (0.99)
- Asia > China > Sichuan > Sichuan Basin (0.99)
- North America > United States > Texas > Permian Basin > Midland Basin > Wolfcamp A Formation (0.89)
- (2 more...)
- Well Completion > Hydraulic Fracturing (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Faults and fracture characterization (1.00)