Effects of High Process-Zone Stress in Shale Stimulation Treatments
Bibliographic record
Abstract
Abstract Over the last few years shale plays across North America have received significant attention because of their revenue potential and the supplementary reserves they add to the U.S. natural-gas reserves. However, the flow capacity (i.e., permeability) of these shales is very low and, therefore, requires some sort of stimulation to make them economically viable. Problems during stimulation treatments can lead to "pressure outs" and screenouts. One of the main reasons that lead to "pressure outs" is high process-zone stress (PZS). With high PZS, the chance for pressuring out is higher than screenout (i.e., one can still flush the job at lower rates provided the sand has not settled in the wellbore). The purpose of this work is to show the effects of high PZS in shale stimulation treatments and the associated production from such zones. Examples are presented from three shale wells in the Rocky Mountain region. Well A provides examples from the Gothic and Hovenweep shales, while Well B consists of an example from the Mancos shale. A Diagnostic Fracture-Injection Test (DFIT) was performed in the Gothic and Hovenweep shales before the stimulation treatment, and the results obtained point to very high PZS. History-match analysis of the Gothic and Upper or Main Hovenweep stimulation treatments using a grid-oriented, fully functional three-dimensional (3D) fracture simulator confirmed the same. Solutions are provided to overcome this effect and successfully "place" the stimulation treatment. However, the production associated with such high PZS zones is not very encouraging. Well A is temporarily abandoned because of poor production, and the Mancos shale well with high PZS (Well B) is one of the poor producers in the field. Finally, another example (Well C) from a successful Mancos test is also included in this work to show the difference in production between high- and low-PZS zones. This paper discusses methods for early identification of high-PZS shale zones to possibly avoid stimulation treatments in order to pay more attention to the low-PZS zones that require stimulation.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".