The First Out-of-Sequence-Fracturing Field Test in North America: Key Learnings from Operation, Petrophysical Analysis, Fracture Modeling, and Production History Matching
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Bibliographic record
Abstract
Summary One of the considerations in out-of-sequence-fracturing treatment is creating fracture complexity through reducing the in-situ differential stress to enhance hydraulic-fracture connectivity by activating natural fractures, fissures, faults, and cleats within the formation to create secondary or branch fractures (induced-stress-relief fractures) and connect them to the main biwing hydraulic fractures. In out-of-sequence fracturing, this is achieved by beginning fracturing Stage 1 at the toe of the well and then moving toward the heel and fracturing Stage 3 so that there is a degree of interference between the two fractures, followed by placing Stage 2 between the previously fractured Stages 1 and 3. Out-of-sequence fracturing in this mode ensures that the fracture in Stage 2 (center fracture) takes advantage of the altered stress in the rock and connects to the stress-relief fractures from the previous Stages 1 and 3 (outside fractures), thus enhancing the connectivity of the fracture network. The first successful field trial of out-of-sequence fracturing was executed by Lukoil in treating eight wells in western Siberia in 2014. The first case of out-of-sequence fracturing in North America was later conducted in western Canada in 2017, with eight more trials followed in 2017, 2018, and 2019. In this work, a 3D hydraulic-fracture-extension simulator is rigorously calibrated by history matching the observed treatment pressures from the out-of-sequence-fracturing field treatment in western Canada to reliably quantify the effective fracture geometries. Then, a separate set of fracture modeling is conducted to predict the hydraulic-fracture geometries in a conventional (sequential-fracturing) treatment of the same candidate well. Finally, production forecasting is used to assess the production potential from the candidate well according to each set of the generated fracture geometries from each of the scenarios (out-of-sequence fracturing vs. conventional sequential fracturing). The results of coupling the rigorously calibrated fracture modeling and production forecasting indicate noticeable production-uplift potential from a carefully designed out-of-sequence-fracturing vs. sequential-fracturing treatment. Besides, the discovered characteristic trends in fracture geometries in out-of-sequence fracturing confirm some of the findings obtained in a previous sensitivity analysis of out-of-sequence fracturing. The previous sensitivity study entailed analyzing nearly 200 fracture-modeling scenarios using a variety of geomechanical properties and treatment-design variables. These characteristic trends render unique opportunities and advantages for the optimization of fracturing treatments and field development. This work is the first attempt in comparative evaluation of the effect of out-of-sequence fracturing by incorporating the actual field data into fracture modeling coupled with production forecasting. The learnings from this multifaceted study are worth sharing with the industry and could be used to guide future successful designs of the out-of-sequence fracturing for completion optimization in both unconventional and conventional reservoirs. From a large-scale field-development perspective, when conducted in multiple wells, optimized out-of-sequence fracturing has the potential of rendering full-length interference effect and optimizing the stress shadowing while reducing the risk of well bashing.
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Full frame distilled prediction
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 | 0.000 | 0.000 |
| 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)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it