Coupling Analytical and Numerical Methods to Assess Performance and Stimulation Efficiency in Multi-Stage Fractured Horizontals
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Bibliographic record
Abstract
Abstract Despite the technological advances in stimulation practices of Multi-fractured-horizontal well (MFHW), many operators (in early-life) still wrestle with the question – "Is it the rock properties or is the stimulation that is impacting my performance?" Addressing this question requires forensic considerations. From the perspective of rate transient analytics (RTA), the bulk linear flow parameter (LFP) has received much attention in literature as a means of characterizing the performance in MFHW; specifically, in tight rock systems. The most common means of assessing the LFP is via the straight-line approach reconciliation of the rate-normalized (pseudo-) pressure versus square root-time, and time may not necessarily be actual time. Having said that, this a critical step prior to jumping to the square root time plot is to confirm the linear flow regime exists. Best practice is to employ the log-log (specialized plot of the) rate normalized pressure and derivative functions, and confirm that a half-slope is discernible. This approach coupled with the square root time plot bodes the confidence needed for interpretation. While the bulk Linear Flow Parameter, or the A√K value is a proxy for flow capacity, the constraint is that it cannot uniquely distinguish the quantitative measure of the induced fracture properties from the intrinsic permeability of the rock. Furthermore, it is only an approximate solution with fundamental assumptions and/or required corrections if non-constant diffusivity applies, as well as high-drawdown, multiphase phenomena, exotic diffusion mechanisms and/or compaction effects. This paper explores the interplay of the individual linear flow parameters by testing various reservoir and stimulation properties via numerical models (i.e. synthetic cases with control variables). The permutations of these tests are reflected via the flow regime signatures observed with the respective LFP and the associated production impacts. Actual field cases studies are also provided and evaluated analytically to establish consistency and validate the aforementioned observations. The case studies are specific scenarios where production impairment is suspected and could potentially be attributed to stimulation efficiency issues. In other words, field cases are presented where a flow restriction could exist in the respective laterals and the coupled numerical and analytical methods confirm whether milling interventions would or would not necessarily improve production performance.
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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 | 0.000 |
| 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 it