Quantifying the Effects of Parent-Child Communication Using Dynamic Fluid-In-Place Calculations
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Bibliographic record
Abstract
Abstract Multi-fractured horizontal wells completed in the same reservoir layer, or different reservoir layers, commonly experience inter-well communication through hydraulic fractures. For example, after a parent well is placed on production, its production performance can be impacted by communication with an offsetting child well placed on production after the parent well. The degree of communication between parent-child wells is important to quantify for the purposes of well production forecasting, reserves estimation, and completions and well spacing design optimization. In this study, dynamic fluid-in-place calculations performed using parent well production rates and flowing pressures are used to quantify the impact of child well communication on parent well contacted fluid-in-place estimates. Agarwal (2010) demonstrated that pressure transient analysis theory can be used to derive the volume of fluid in place contacted by a well (CFIP) over time during constant rate, transient production. The method was later extended to variable-rate/pressure scenarios. However, all previous applications of Agarwal’s method were for single, isolated wells. In order to evaluate the usefulness of the method for quantifying parent-child communication, for this study, multiple numerical simulation cases are generated to simulate different degrees of communication. This is achieved by simulating light oil and gas production scenarios, where the parent and child wells are communicating through a hydraulic fracture with a specified transmissibility multiplier (Tmult) used to adjust the amount of inter-well communication. The CFIP diagnostic plot (i.e., log-log plot of CFIP versus material balance time) is applied to the parent well to evaluate the CFIP trend before and after child well production, and the magnitude of CFIP change. Practical application of the method is demonstrated with field cases. From the simulation cases, it is observed that, after the child well is put on production, a reduction of CFIP for the parent well occurs (rapidly decreasing at first, then stabilizing after a transition period) proportional to productivity index reduction. The loss in CFIP for the parent well can be determined simply by estimating the parent well CFIP immediately before and after child well production. The loss in CFIP is verified using drainage volume estimates in the simulator. For the Tmult=0.25, 0.5, and 1 cases (where Tmult=1 yields the greatest degree of communication), the slope of the CFIP trend for the parent well = 0.5 (pure transient linear flow) before and after child-well communication/transition, and the CFIP change is estimated to be about 40% for oil and 47% for gas. For the case of Tmult =0.001, the CFIP change for the parent well is smaller (28% for oil, 39% for gas) than for Tmult > 0.25. The slope of the CFIP plot for the parent well in this case, prior to child-well production, is > 0.5, but stabilizes at 0.5 after interference. For the case of Tmult =0 (no communication case), as expected, the child well does not influence parent well production, the CFIP change is zero, and the CFIP trend line slope = 0.5. For one of the field cases studied (Well 23 of the SPE data repository), where communication with an offset well is interpreted to occur, the reduction in CFIP is estimated to be 37-38%, consistent with an independent study performed using a more complex history matching procedure (35%). In addition, analysis of three producing parent-child well pairs, drilled from a 6-well pad, results in CFIP reduction estimates of 33-74% for the parent wells. This study demonstrates for the first time that CFIP calculations can be applied for the purpose of quantifying inter-well communication, providing operators with a simple-yet-rigorous method for estimating changes in parent well CFIP/drainage volume caused by child-well interference.
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Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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