Fracture Network Characterization by Analyzing Flowback Salts: Scale-Up of Experimental Data
Bibliographic record
Abstract
Abstract As observed in many shale-gas plays, the produced flowback water is highly saline and the salt concentration increases with time. Several past studies investigated water-rock interactions to interpret flowback chemical data, evaluate reservoir performance, and investigate the environmental impacts of fracturing operations. In this study, we measure the total ion produced (TIP) during flowback process for two wells completed in the Horn River Basin. We also conduct two sets of imbibition experiments to investigate the effects of water-rock surface area (As) and rock volume (Vs) on the TIP in laboratory. Furthermore, we compare the experimental correlations between As - TIP and Vs - TIP with the TIP measured in the field flowback water to estimate fracture surface area (AFrac) and invaded reservoir volume (IRV). In order to investigate the effect of As on the TIP, we conduct a series of imbibition experiments using shale samples of different As but similar Vs at constant temperature. The experiments are performed at T = 23, 45, and 65°C to investigate the temperature effect on the TIP. The experimental correlation between TIP and As at constant temperature is applied to estimate AFrac using field data of TIP. We further utilize AFrac - T correlation to extrapolate AFrac at reservoir temperature. In order to evaluate the estimated AFrac values we also calculate AFrac by rate-transient-analysis (RTA). In order to investigate the effect of Vs on the TIP, we conduct a series of imbibition experiments using shale samples of different Vs but similar As at constant temperature. Experimental results indicate that the TIP increases with both As and temperature. The calculated AFrac value at reservoir temperature is approximately 106m2 for both target wells. These results are in agreement with RTA calculation of AFrac values for both target wells (≈ 106m2). Our estimated values of AFrac are also in agreement with the field data of water recovery. The well with higher estimated value of AFrac has lower water recovery in the field as opposed to the well with lower estimated value of AFrac and higher water recovery in the field. Additionally, the estimated IRV is approximately 105 - 106m3 for both target wells. Our estimated values of IRV are also in agreement with the field data of water recovery and experimental results of water uptake. The well with higher estimated value of IRV has higher water uptake during imbibition experiments and also higher leak-off rate in the field. In contrast, the well with lower estimated value of IRV has lower water uptake during imbibition experiments and also lower leak-off rate in the field.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".