Estimation of Oil Production Rates in Reservoirs Exposed to Focused Vibrational Energy
Bibliographic record
Abstract
Abstract Elastic wave-based enhanced oil recovery (EOR) is being investigated as a potential EOR method, since strong wave motions within an oil reservoir - induced by earthquakes or artificially generated vibrations - have been reported to improve the production rate of remaining oil from existing oil fields. To date, there are few theoretical studies on estimating how much bypassed oil within an oil reservoir could be mobilized by such vibrational stimulation. To fill this gap, this paper presents a numerical method to estimate the extent to which the bypassed oil is mobilized from low to high permeability reservoir areas, within a heterogeneous reservoir, via wave-induced cross-flow oscillation at the interface between the two reservoir permeability areas. This work uses the finite element method to numerically obtain the pore fluid wave motion within a one-dimensional fluid-saturated porous permeable elastic solid medium embedded in a non-permeable elastic semi-infinite solid. To estimate the net volume of mobilized oil from the low to the high permeability areas, a fluid flow hysteresis hypothesis is adopted to describe the behavior at the interface between the two areas. Accordingly, the fluid that is moving from the low to the high permeability areas is assumed to transport a greater volume of oil than the fluid moving in the opposite direction. The numerical experiments were conducted by using a prototype heterogeneous oil reservoir model, subjected to ground surface dynamic loading operating at low frequencies (1 to 20 Hz). The numerical results suggest that a substantial amount of oil could be mobilized via the elastic wave stimulation. It is also observed that certain excitation frequencies are more effective than others in mobilizing the remaining oil. We remark that these amplification frequencies depend on the formation's elastic properties. The numerical simulations show that wave-based mobilization of bypassed oil in a heterogeneous oil reservoir is feasible, especially when combined with another EOR method, such as wettability alteration by low-concentration surfactant injection. The extension of this research into a more realistic three-dimensional reservoir model would help determine the optimal locations and frequencies of wave sources.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".