Material Balance Forecast of Huff-and-Puff Gas Injection in Multiporosity Shale Oil Reservoirs
Bibliographic record
Abstract
Abstract Primary oil recovery from shales is very low, rarely exceeding 10% of original oil in place (OOIP). The low recovery has aroused a recent and growing interest in the petroleum industry for using Improved Oil Recovery (IOR) methods in shales. This paper presents a new semi-analytical material balance equation (MBE) to forecast the performance of shale oil reservoirs under natural depletion and huff-and-puff gas injection scenarios. For undersaturated reservoirs, recovery is calculated from the proposed MBE explicitly using a multiporosity effective oil compressibility. For saturated reservoirs, the MBE is solved at each pressure step using a finite differences scheme. For huff-and-puff gas injection, the average reservoir pressure p is calculated after injecting a certain gas volume during the huff period. At each huff-and-puff cycle, the remaining OOIP is considered, and the injected gas volume (which is known) is written in terms of the p following injection (which is unknown). Adding the gas injection term to the MBE generates a nonlinear equation for p, which is solved using a numerical method. Results indicate that oil recovery from shales can be increased significantly by huff-and-puff gas injection. A case study from the Eagle Ford shale in the United States is used to demonstrate these results, which are presented in tabular form as well as crossplots of oil rates, cumulative oil production, gas-oil ratio and average reservoir pressure vs. time. An important feature of the proposed MBE is the inclusion of hydraulic fractures, as well as inorganic, organic and natural fracture porosities. These porosities are included in a history-matching presented in detail for a well undergoing huff-and-puff gas injection. The novelty of this work resides on the introduction of a new MBE that considers multiple porosities and enables quick evaluations of primary recovery and huff-and-puff gas injection scenarios in shale oil reservoirs. The new MBE results compare favorably against real data of the Eagle Ford shale. The good comparison allows making reasonable projections of future oil rates and cumulative oil recoveries by huff-and-puff gas injection.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".