Using open hole and cased-hole resistivity logs to monitor gas hydrate dissociation during a thermal test in the mallik 5L-38 research well, Mackenzie Delta, Canada
Bibliographic record
Abstract
Gas hydrates, which are naturally occurring ice-like combinations of gas and water, have the potential to provide vast amounts of natural gas from the world's oceans and polar regions. However, producing gas economically from hydrates entails major technical challenges. Proposed recovery methods such as dissociating or melting gas hydrates by heating or depressurization are currently being tested. One such test was conducted in northern Canada by the partners in the Mallik 2002 Gas hydrate Production Research Well Program. This paper describes how resistivity logs were used to determine the size of the annular region of gas hydrate dissociation that occurred around the wellbore during the thermal test in the Mallik 5L-38 well. An open-hole logging suite, run prior to the thermal test, included array induction, array laterolog, nuclear magnetic resonance and 1.1-GHz electromagnetic propagation logs. The reservoir saturation tool was run both before and after the thermal test to monitor formation changes. A cased-hole formation resistivity log was run after the test. Baseline resistivity values in each formation layer (R t ) were established from the deep laterolog data. The resistivity in the region of gas hydrate dissociation near the wellbore (R xo ) was determined from electromagnetic propagation and reservoir saturation tool measurements. The radius of hydrate dissociation as a function of depth was then determined by means of iterative forward modeling of cased-hole formation resistivity tool response. The solution was obtained by varying the modeled dissociation radius until the modeled log overlaid the field log. Pretest gas hydrate production computer simulations had predicted that dissociation would take place at a uniform radius over the 13-ft test interval. However, the post-test resistivity modeling showed that this was not the case. The resistivity-derived dissociation radius was greatest near the outlet of the pipe that circulated hot water in the wellbore, where the highest temperatures were recorded. The radius was smallest near the center of the test interval, where a conglomerate section with low values of porosity and permeability inhibited dissociation. The free gas volume calculated from the resistivity-derived dissociation radii yielded a value within 20 per cent of surface gauge measurements. These results show that the inversion of resistivity measurements holds promise for use in future gas hydrate monitoring.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".