Impact of Wettability on Rock Mechanics and Oil Recovery: A Comparative Study on Different Outcrop Chalks
Bibliographic record
Abstract
Chalk reservoirs are highly fractured and are known for their remarkable storage capacity as a reservoir rock for the petroleum industry. Chalk is a sedimentary carbonate rock primarily made up of calcium carbonate (calcite, CaCO3) and is a very important reservoir rock in the Norwegian and Danish Continental Shelfs. Water flooding has been used as a secondary production method in chalk reservoirs as it provides pressure maintenance to the reservoir and is a proven improved oil recovery (IOR) method to produce more oil from the production facilities. Ekofisk field in the Norwegian Continental Shelf is a successful example of production by water flooding method, where seawater is used as the injection fluid. The initial estimated oil recovery was 18% as mentioned in the initial development plan of the field and today’s estimates lie well above 50%.\nHowever, seawater has also shown to enhance reservoir compaction due to water weakening of the chalk formation. It can, for example, lead to buckling and loss of well pipes, arching of overburden rocks leading to stress redistributions, and the porosity/permeability decline of the producible formation, all physical effects that alter the ultimate recovery and recovery rates of oil-bearing chalk reservoirs.\nThe detection of subsidence of the Ekofisk field in the Norwegian North Sea around 35 years ago has been linked to the compaction of chalk formations due to porosity reduction associated with field production. It attracted the attention of oil and gas researchers across the globe and since that time, considerable research has been carried out concerning chalk behavior, especially on how the pore fluid composition alters the mechanical properties of chalk.\nResearch on chalk, so far, has primarily been carried out on water-wet systems. The studies have shown that when reactive brines are injected through chalk at elevated temperatures, chemical reactions occur between the rock and the injected brine, which affects chalk mechanical stability. It has been found that the divalent ions, such as magnesium (Mg2+), calcium (Ca2+) and sulfate (SO42-) play an important role in defining chalk mechanics. Mg2+ ions in the injected brines lead to dissolution of calcite, which in turn leads to precipitation of new mineral phases such as magnesite, huntite, talc, anhydrite etc. Both Mg2+ and SO42- ions also adsorb on the chalk surface leading to a reduction in the strength of the rock.\n[...]
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".