Analysis of the Japanese Depleted Gas Fields’ Prospect for Underground Hydrogen Storage
Bibliographic record
Abstract
Abstract A method for reducing power peak is to store hydrogen (H2) underground in depleted gas reservoirs (hereafter UHS). In contrast to alternative solutions, like salt caverns or aquifers, the availability of depleted gas reservoirs gives a greater storage capacity. But choosing the right gas field for the UHS and carrying it out are tricky. As a result, the goal of this work is to characterize the UHS in the chosen field and rank Japanese gas fields for it. To begin with, we ranked and screened potential H2 storage locations in Japan using the Analytical Hierarchy Process (AHP). The best locations for UHS, according to our calculations using the AHP approach, are Sekihara, Kumoide, Katakai, Nakajo, Kubiki, Shiunji, Iwafune-oki (gas), and Minami-Nagaoka. These fields’ high flow capacity, depth, current reservoir pressure, and dip angle are the causes of their elevated position. Then, based on a volumetric reservoir, we studied the H2 injection, storage, and withdrawal capacity at the chosen site in the Niigata Prefecture using the CMG reservoir simulator. For the first time in Japan, this work offers a framework for evaluating and ranking potential depleted gas reservoirs as a UHS option. It also includes a reservoir simulation study to comprehend the impact of various parameters such as hysteresis trapping, number of injection and withdrawal cycles, and type of cushion gas on the efficiency of H2 storage and withdrawal in a volumetric gas reservoir.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.006 | 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".