Sandstone Injections at Jotun Oil Field, Norwegian North Sea—Modeling Their Possible Effect on Hydrocarbon Recovery
Bibliographic record
Abstract
Abstract This chapter describes three-dimensional (3-D) stochastic modeling of the Jotun field, which was initially undertaken in 1998 and updated after the first four wells came on production. The Jotun field contains both differential compaction traps (Elli and Elli South four-way dip closures) and a stratigraphic pinch-out trap (Tau West). It produces from the distal parts of the Paleocene Heimdal Formation sand-rich submarine-fan system. A predrill (1997) deterministic oil-in-place geological model was history matched so that simulated pressure drop resulting from Heimdal field gas production matched the observed pressure drop in the Jotun appraisal wells, with aquifer size and conductivity as the main history-matching parameters. With a development plan strategy of four producers on Elli, two on Elli South, and five producers on Tau West (all highly deviated or horizontal), the predicted aquifer support was such that predrilling water injectors for pressure support was unnecessary. This saved the considerable capital expenditure of three water injectors. Predicted hydrocarbon recovery was influenced by vertical sweep efficiency, dependent on vertical permeability (kv)/horizontal permeability (kh), controlled, in turn, by the architecture of the interlayer shales. Reservoir heterogeneity was introduced in the 1998 model as architectural facies bodies in a 3-D object-based (Roxar STORM software) stochastic geological model. This captured and integrated the core-scale features in a seismic-scale stratigraphic and structural framework, using rules from outcrop analogs to fill in the missing scale. Subsurface realizations reflected different geological possibilities while preserving their influence in the upscaled dynamic simulation models. One of the major uncertainties in the geological modeling was considered to be the extent of faulting, sandstone injection, and slumping as features, which disrupt shale continuity at core scale and which might greatly increase vertical communication and, hence, recovery. If such features are not common, significant volumes of oil could be trapped beneath laterally continuous shale barriers. Different scenarios of geometry, properties, and distribution were used to investigate the significance of such features on the expected ultimate reserves of the field. Both the large aquifer support and a high level of connectivity between the separate structures were confirmed by the first four producers brought on stream.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".