Underground Gas Storage in a Partially Depleted Gas Reservoir
Bibliographic record
Abstract
Abstract The main objective of this study is to perform a real case study of an Iranian gas condensate reservoir for the purpose of underground gas storage. Doing such a study for this reservoir will aid in the development of this technology and will also demonstrate a new concept for underground gas storage in partially depleted gas reservoirs. After gathering some data about the reservoir and preparing a geological model for the field, a simulation plan was considered for this field. A geostatic model was converted to a dynamic one by assigning reservoir fluid and rock data. Finally, a compositional model of the reservoir was prepared and verified to be accurate through a history matching process. After verifying the accuracy of the model and validating it, different scenarios for underground gas storage were developed. Depletion and gas storage scenarios were constructed for the field and results were obtained. Gas storage in a partially depleted gas reservoir was also considered in these scenarios for developing this field. After comparing different scenarios, some practical results were achieved and the best scenario for developing this field was chosen. Introduction An underground gas storage system can be defined as a combination of a constant supply with a variable demand for economic advantage(1). In other words, it helps to combine low summer season demand and high winter season demand to ensure that supply is maintained as a constant. The whole process is comprised of injecting natural gas or (rarely) other gases into the subsurface reservoir during periods that demand falls below the gas supply. When demands exceed the supply, the gas will be withdrawn from the reservoir. Fluctuating demand, due to temperature and climate, makes it necessary in many cases for the pipelines that inject or withdraw the gas be used efficiently(2). It also helps to have effective delivery during peak demand. This process can also be adapted to producing oil or condensate and can be considered as an IOR method(3). Increasing demand for gas in many areas of the world make storage plan development and effective use of existing storage sources a priority to ensure engineering and economic advantages. Figure 1 illustrates the relationship between natural gas supply and demand and clarifies the importance of storing gas during low demand periods in order that it may be used in high demand periods. Reservoir Summary A gas condensate reservoir that is located in central Iran is chosen for the purpose of underground gas storage. This field was FIGURE 1: Natural gas supply and demand(2). Available in Full Paper. discovered in 1955 and production started in 1959. It has a structure that is a northwest-southeast trending anticline approximately 25 km long and about five km wide. The structure was investigated by surface and seismic surveys and eight wells were drilled in the field. The production zone is in a formation of Oligo-Miocene limestone and is marly lime. The top of the producing zone is approximately at 5,200 ft.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".