Improving the Estimation of Porosity and Permeability Distribution by Linking Basin Modelling to Diagenetic Evolution of Carbonate Reservoirs
Bibliographic record
Abstract
Abstract Carbonate reservoirs have petrophysical property distributions largely controlled by a combination of the depositional, diagenetic, and structural (burial/uplift) histories of the reservoir itself and also of the basins that contain them. Carbonates are very prone to diagenetic alteration; porosity and permeability can be strongly affected by the thermal state, fluid-pressure and pore fluid chemistry through their geological history. We use a novel workflow, adapted from basin modelling, to investigate how the burial/uplift history of an offshore carbonate reservoir and its basin, taken as a system, can have controlled the fluid and heat movement within, into and out of the reservoir. The reservoir rock properties and diagenetic history are assessed, as is the local and regional geological evolution for potential contributory factors to the diagenesis. A model of the potential basin system is developed, observed reservoir diagenetic history being added to the normal basin modelling constraints. This model provides good estimates of geometry and property evolution, and of fluid transport, through geological time. Since fluid and heat fluxes are important in the diagenetic evolution of the carbonate pore system, these results are complemented by simulating the movement of heat and brine in the reservoir using finite element-finite volume simulations. These simulations capture the complex geological structures, especially fault-fracture systems, and better represent the flow physics and chemistry that control reservoir diagenesis. Results from these simulations will later be returned to the basin model to improve the calibration of the timing, depth, and rates of diagenetic events. This new workflow is applied to a Lower Eocene offshore carbonate reservoir with a complex diagenetic history which seems to have a strong basin evolution influence. Importantly this workflow is generic and can be applied to any carbonate reservoir to enhance the link between geological models at the basin scale and reservoir scale models.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".