Imaging Injected Water flood Fronts between Wells in a Complex Carbonate Reservoir: Designing Completions to Optimize Image Resolution
Bibliographic record
Abstract
Abstract In the paper, we will briefly review the pilot design and demonstrate the utility of applying the EM imaging to the pilot. We will also show the benefit of the optimized casing material on the resolution of the crosswell EM resistivity images and describe the methods employed for monitoring the fluid flow and show preliminary results of the modeling process. This crosswell EM technique which has been successfully employed and proven in other geographical areas is being implemented first time in UAE. The EMI technology is being deployed in southern part of a complex carbonate reservoir in the middle-east where an uneven flood front advance has been observed in different reservoir units. It has been observed that water front has advanced much faster in the highly permeable upper reservoir units as compared to lower reservoir units. In order to understand the horizontal and vertical fluid flow behavior, an inverted 5-spot water injection pilot pattern is being implemented. The pilot will address the issues of the uneven sweep efficiency, bypassed oil and effectiveness of stylolites across different units. The pilot results and observed data will be used in the simulation to design an optimum development scheme for the lower reservoir units in the southern part of the field. The current dynamic simulations predicted that the injected water will reach producers after 7 to 10 years. However, the decision on field developments have to be taken early enough to avoid the slumping of water from upper to lower units and loss of reserves in the lower units. Early imaging of the injected water from the injection well into the reservoir is paramount in assessing the success of the pilot and future field development issues. It is anticipated that this tomographic Cross-well Electro-magnetic (EM) resistivity technique will provide sufficient imaging information to track the water flood movement between wells. The most favorable conditions to acquire reliable formation resistivity distribution information, EMI require at least one kilometer distance or separation between wells. Prior to the field deployment, simulations were run to confirm the applicability of the technique and define the parameters for the survey with objectives; 1) to check the sensitivity of EM technique to the reservoir conditions and injected fluids, and 2) to carry out actual EM tool simulation and check the quality of tool response. The study concluded; 1) cross-well EM resistivity technique is well suited for tracking the water front in the current reservoir conditions, 2) the injected fluids create enough resistivity contrast to be easily picked up by the technique, and 3) the flood front progress can be captured by conducting the surveys in a time-lapse mode. As part of this project, lab tests were conducted to choose a material that would limit the attenuation at high frequency as much as possible at source and receiver locations.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".