3-Axis Borehole Gravity: Method and Application to CO2 Storage Monitoring and Oil/Gas Production
Bibliographic record
Abstract
Abstract In the attempt to fill the scale gap between pulsed neutron and 4D seismic geophysical techniques to monitor underground reservoirs for ongoing oil/gas productionor CO2capture and storage, we introduce an emerging 3-axis borehole gravity technology that enables the recording of gravitational acceleration at high sensitivity, targeted at5 µGal. This is made possible using an innovation in resonant Microelectromechanical systems (MEMS) vibrating beam technology. This technology is designed to sense gravitational field produced by mass density changes in the subsurface, such that time-lapse wireline-based surveys may be taken to image fluid movements as far as 100s of meters from a wellbore and thereby enable time-lapse or 4D gravity monitoring. The innovation of 3-axis gravity measurement allows the acquisition of directional information about the spatial movement of fluid, even when acquired from just a single borehole.The cost effectiveness of a 4D wireline gravity survey compared to 4D seismic survey is highly attractive especially in the later stages of production surveillance programs, or as a complementary survey. We will first introduce the technology, and then present its application through a feasibility study aimed at the monitoring of CO2 in a deep storage reservoir in Canada. We model and predict the gravity variation in a 4D gravity surveylikely to be seen due to density changes during a period of CO2 injection at the storage site. Survey feasibility modelling and a workflow are presentedthat together provide important information forplanning and acquiring successful 4D gravity surveys, including the optimal time intervalbased on the planned injection rateand the optimal well location to use. The study will illustrate the general use for of time-lapse 3-axis gravity in monitoring reservoirs for optimising production over time while additionalexamples will be shown to further demonstrate application within oil/gas production reservoirs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".