Study Interprets Electromagnetic-Wave Penetration, Absorption for Bitumen Reservoir
Bibliographic record
Abstract
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199941, “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,” by Matthew Morte, SPE, Hasan Alhafidh, SPE, and Berna Hascakir, SPE, Texas A&M University, prepared for the 2020 SPE Canada Heavy Oil Conference, originally scheduled to be held in Calgary, 18–19 March. The paper has not been peer reviewed. Interpretation of logging data generated through electromagnetic (EM) waves or determination of EM-wave propagation in a medium as an enhanced-oil-recovery (EOR) method are not easy tasks. The complete paper aims to identify the role of different geological settings with different types of fluid saturations in the response of EM-wave propagation and absorption. Several correlations were created in this study and 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 waves as an EOR method. Experimental Procedure Complex permittivity of synthesized rock samples was recorded by means of a vector network analyzer as the source and a dielectric probe kit as the transmitter. The dielectric probe behaves as both the transmitter and receiver simultaneously by measuring the proportion of the reflected wave. The dielectric probe is capable of measuring both the solid interface, as is the case with the synthesized reservoir rock, and fluids. The output of the vector network analyzer is both the dielectric constant, defined to be the real-portion complex permittivity, and the loss index, defined to be the imaginary portion. The loss tangent is a parameter that describes the overall efficacy of the material as a microwave absorber with higher values corresponding to higher heat generation in the reservoir. Reservoir properties of interest are isolated by taking advantage of experimentally defined synthesized cores. Variable properties are achieved by introducing a known quantity of specified materials to ensure control over the outcome of representative reservoir rock. Samples are an unconsolidated mixture of both the skeletal frame (rock matrix) as well as the pore space. The rock matrix is comprised of a systematic and stepwise variability of quartz sand, limestone sand, and kaolinite clay or bentonite clay. The fraction of each introduced mineral is manipulated to isolate the contribution of the individual components. The weights of the introduced constituents are calculated to result in a synthetic rock matrix with the desired rock mineralogy. The first batch of synthesized cores consisted of 75 mixtures. The remainder of the contrived cores were limestone. A separate 20 experiments were performed to account for the presence of both pore-filling and swelling clays, namely kaolinite and bentonite, respectively. Compaction and blending of the cores were performed by hand; homogenization of the mixture was ensured by thorough mixing.
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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 | 0.001 |
| 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) | 0.000 | 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 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".