Combination of Basin Scale Data Analysis and Numerical Simulations for the Interpretation of the Coexistence of Thermal Water and Hydrocarbon Accumulations
Bibliographic record
Abstract
During the evolutionary stages of sedimentary basins, different processes are active. Secondary migration means the movement from the source area to the trap and it has most likely the tendency to move along with water. Thus, the secondary migration of petroleum is directly affected by the different driving forces which also influence the ambient groundwater (Tóth 1988). In other words, understanding the regional groundwater flow systems and driving forces may support petroleum exploration. In this theoretical framework, a hydrogeological evaluation of the broader environment of Ebes-Hajdúszoboszló area(Eastern Hungary, Pannonian basin) was executed on the interpretation of the coexistence of thermal water and hydrocarbon accumulations in the specific area. The study is based on the application of two different methods. At first a basin-scale hydrogeological evaluation of the recent fluid flow condition including archive hydraulic, chemical, borehole temperature data interpretation, and regional pressure field evaluation was carried out. These data confirmed the superposition of an over-pressured flow regime driven by tectonic compression and compaction and the upwelling of fluids in the gravity driven-flow system in the upper part (Zentai-Czauner et al., 2018). The data analysis could provide initial understanding and conceptual framework for 2D numerical evaluation of superposition of the topography differences and overpressure as driving forces It was carried out using the Heat Flow Smoker software version 7.0 developed by (Molson, 2014) which can simulate density-dependent flow and advective-dispersive transport of thermal energy, mass or residence time in three-dimensional porous or fractured media. The interpretation of the 2D simulation of the cross-section was compared with the results of the data analysis and it can show the relationship between the hydrocarbon accumulations and the existence of thermal water is due to groundwater flow. The regional data analysis and subsequent 2D simulation could confirm the favorable conditions for hydraulic trapping of hydrocarbons and the heat accumulation in groundwater due to advective heat transport. This work is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 810980. Keywords: Groundwater-flow, thermal water, hydraulic trapping, hydrocarbons, migration, accumulation. References: Szabó Zs., Zentai-Czauner B., Mádl-Szőnyi J., 2018 Hydrogeological evaluation of the broader environment of Ebes concession area for the understanding of recent fluid flow conditions, final report of Vermillion Energy Hungary. Toth J., 1988, Groundwater and hydrocarbon migration, in back, W., Rosenshein, J. S., and Seaber, P. R., eds., Hydrogeology: Boulder, Colorado, Geological Society of America, The geology of North America, v. O-2, chap. 48, pp. 485-502. John W. Molson, 2019. Heat Flow Smoker, Version 7.0, density-dependent flow and advective-dispersive transport of thermal energy, mass or residence time in three-dimensional porous or fractured porous media, université Laval, University of Waterloo.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".