Geothermal Energy Extraction–Induced Ground Movement Monitoring by InSAR and Its Implication for Reservoir Management
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Bibliographic record
Abstract
Global climate change highlights the significance of renewable clean energy. Geothermal energy from oilfields is abundant and can be utilized for residential heating and oil transportation. However, unreasonable heat exchange methods lead to groundwater level decline. Differences and delays between water extraction and reinjection inevitably cause land subsidence, hindering the sustainable utilization of geothermal energy resources. It is crucial to effectively monitor large-scale ground surface deformation characteristics in geothermal fields. In the research, 55 Sentinel-1A images from October 2018 to May 2022 were collected, and the ground deformation of Caofeidian new district in Bohai Bay Basin, where Nanpu Oilfield is located, in North China, was inverted by short baseline subsets-interferometric synthetic aperture radar (SBAS-InSAR) technology. The maximum subsidence velocity in Caofeidian new district exceeded 50 mm/year. Since April 2019, there has been concentrated ground subsidence in the Caofeidian new district, with a maximum cumulative subsidence exceeding 50 mm. The maximum cumulative subsidence exceeded 150 mm by May 2022. Combined with pumping and recharging tests near heating project in Caofeidian new district, the temporal subsidence mechanisms were revealed. The water extraction from the thermal reservoir caused drainage consolidation of the strata, triggering rapid subsidence in November. In April, discrepancy between water extraction and reinjection flow rate in thermal reservoir caused drainage consolidation of the strata, further exacerbating the subsidence trend. During rainy seasons, despite water reinjection and groundwater replenishment from precipitation, the strata in the Caofeidian new district underwent irreversible plastic deformation, with a slow rebound process, lagging behind urban areas without geothermal development by one month. InSAR is a reliable technology for understanding the ground deformation process in geothermal fields. Clarifying the subsidence mechanisms guides the selection of water-heat exchange methods, ensuring the sustainable development of geothermal resources.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it