Interpretation of Electromagnetic Wave Penetration and Absorption for Different Reservoir Mineralogy Quartz-Rich, Limestone-Rich, and Clay-Rich and at High and Low Water Saturation Values for a Bitumen Reservoir
Bibliographic record
Abstract
Abstract Electromagnetic (EM) waves are used in the oil and gas industry to identify the geology of the formation and the type of the fluid saturating the medium. There is also an interest to use the electromagnetic waves as an enhanced oil recovery (EOR) method. However, interpretation of logging data generated through electromagnetic waves or determination of the electromagnetic wave propagation in a medium as an EOR method are not easy tasks. This study aims to identify the role of different geological settings with different types of fluid saturations in the response of electromagnetic wave propagation and absorption. To reach this objective multitude-systematic laboratory scale experiments were conducted on different reservoirs fluid and rock pairs. As reservoir mineralogy, different grain size of quartz, clay, or limestone is used to prepare the reservoir rocks at different porosity. Water is known as a good absorber for EM waves, thus, pore space were saturated at different water saturations and a bitumen sample (10,000 cP, 12° API) from Canada. Prepared samples were packed into in-house-built-Plexiglas core holder which allows measurements with EM waves. The response of EM waves propagation and absorption was measured by using a vector network analyzer at varying frequencies (500 MHz to 4 GHz) through dielectric properties (dielectric constant, loss tangent, and penetration depth). The results were used to obtain correlations between dielectric properties and physical properties (reservoir rock mineralogy, porosity, water saturation, and oil saturation) of the reservoir rock-fluid blends. Water saturation gives a perfect correlation with dielectric constant and loss tangent values of the saturated medium. Because dielectric constant and loss tangent parameters provide an idea on the absorption characteristics of EM wave in the medium, and because water is a strong EM wave absorber, as it was expected, with the increase in water saturation, the dielectric constant and loss tangent parameters of the medium are also increased; on the other hand, penetration depth was decreased. With the increase in quartz content in the medium, it has been observed that EM wave penetration is enhanced. As a result, several correlations were created in this study and they can be used to better interpret the reservoir mineralogy and fluid saturation as a response to EM wave logging. Moreover, these results can be used to estimate the effective area (penetration depth) of EM wave as an EOR method in different mediums.
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 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 | 0.000 |
| 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) | 0.002 | 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".