Effects of Lithofacies and Reservoir Heterogeneity on Improved Oil Recovery Processes
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A comprehensive understanding of reservoir geology plays an important role in the success of oil/gas recovery processes. Several emerging IOR (improved oil recovery) techniques have been proposed in the past decades with promising results. However, a systematic study of reservoir heterogeneity on these advanced processes has yet been presented in the literature. This paper provides one of the first comparative evaluations of the effects of reservoir heterogeneity on various IOR processes such as water flooding, CO2 flooding, Low Salinity Waterflooding (LSW) and CO2 LSWAG for a wider and more successful implementation of these projects. Since several weaknesses exist in the current simple and unrealistic models, detailed geostatistic models are employed in this study to provide a more realistic and unbiased evaluation of reservoir heterogeneity. We first present an innovative approach that allows us to capture the critical effects of geological heterogeneity. This new approach involves the integration of geological software, a reservoir simulator and a robust optimizer in a closed-loop for generating multiple geologically driven realizations and uncertainty assessment of different recovery processes. Then a series of numerical simulations have been conducted to investigate the influences of fining- and coarsening-upward sequences on oil recovery. Finally, we evaluate the uncertainty range of reservoir heterogeneity using a large number of geological realizations with significant differences on porosity and permeability distributions. The effect of the Kv/Kh (aspect) ratio is also addressed in this study. The simulation results indicate that the lithofacies has a dominant effect on oil recovery in all recovery processes. The coarsening-upward distribution demonstrates superior performances over the fining-upward distribution. However, it is observed that the differences on oil recovery from two stratified reservoir models are not similar in all injection methods. Although the lithofacies distribution has a slight effect on the conventional waterflooding, this effect becomes significant in CO2 flooding and more drastical in LSW and CO2 LSWAG. This observation is very important for maximizing oil recovery by taking into account the crucial effects of reservoir geology in these emerging technologies that have never been considered in the past. Additionally, the heterogeneity of lithofacies also affects the flow direction and injectivity of displacing fluids, and, consequently, influences the ultimate oil recovery factor. Reservoir heterogeneity plays a critical role in the successes of IOR processes but it has never been comprehensively quantified, especially for some emerging techniques. Thus the results from this paper are very important to overcome the current challenges in capturing the importance of geological uncertainties in the current and future IOR/EOR projects.
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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 | 0.001 |
| 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