Interpretation of Water Injection/Falloff Test—Comparison Between Numerical and Levitan's Analytical Model
Bibliographic record
Abstract
Abstract Water injection/fall off tests are normally associated with water flood project. Recently, interested in this type of well tests has developed in the area of reservoir appraisal. In the vast majority of situations associated with exploration activities, there is no infrastructure and equipment in place to collect and export the hydrocarbon produced during well test. The common practice used in the industry is to burn the produced fluid. The demands to reduce emission during well tests put enormous pressure to avoid these tests together. This brings large uncertainties to the reservior appraisal and increases the investment risk if a decision is made to sanction a project and to develop the field. Replacing a production/build up test sequence by an injection/fall off test sequence solves the problem of emission. Levitan[1] stated that three main problems due to using water injection / fall off test might happen which are listed below: The first problem is that the character of the system changes and Instead of single-phase flow we face now with two-phase water-oil flow by their own relative permeabilities. The second problem is injection of cold water includes temperature changes in the formation and brings additional complication to pressure behaviour through temperature effects on the oil and water viscosities and the third one is injection of water may result in the formation fracturing and in coupling of rock mechanics and fluid flow problems. It is therefore, important for successful test interpretation to avoid fracturing and to inject water at below the formation fracturing pressure. This paper is divided into two parts. In the first part we are going to compare Numerical and Levitan's Analytical model for different injection and fall off periods using numerical part of Saphir well test software. In the second part as far as we have validated Saphir Numerical model compared with W-O Levitan Analytical model, now this model is used to generate pressure responses in order to investigate the influence of reservoir parameters. Methods of interpretation will be used and some specific advantages of the numerical model will be shown.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".