Determination of Real-Time Dynamic Fluid Levels by Analysis of the Dynamometer Card
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Bibliographic record
Abstract
Abstract Although the beam pumping is the dominant pumping system in the onshore oilfields, many issues pertaining to its hydraulic performance have not been well understood. This is mainly ascribed to the fact that it is difficult to determine the downhole pump performance data, such as the dynamic fluid levels. In practice, the dynamic fluid levels are traditionally measured on-site by using the acoustic method. This method, however, finds its limitations in determining the real-time dynamic fluid level. Recently, the automation technology has been widely used in the oilfields, it is essential to measure the real-time dynamic liquid levels for optimum reservoir management. In this paper, a method is developed to determine the real-time dynamic liquid levels by analyzing the measured dynamometer card. Theoretically, a mathematical model is developed to determine dynamic fluid levels by using the average polished-rod loads (PRLs) for the two turning points at the end of the upstroke and downstroke, respectively. In practice, the average PRLs can be directly obtained from the dynamometer cards and then used to determine the dynamic fluid level. It has been found from field applications that this newly developed method provides accurate determination of the dynamic fluid levels which will not be affected by the existence of noise, dogleg, tubing collars, and annular gas. In addition to determination of the real-time dynamic fluid level, this method greatly reduces the production maintenance cost. A PC-based software for determining the dynamic liquid levels is also developed. Introduction The dynamic fluid level, defined as the distance from the wellhead to the fluid level in the annulus, is a key pumping parameter to be measured on a regular basis. It has been well accepted that fluid level survey is considered as the primary diagnostic tool for monitoring downhole status and confirming the problem[1]. In general, the dynamic fluid level can be used to determine the production strategies, analyze the reservoir performance, and to estimate the reservoir pressure at the various stages of field development since it is constrained by the formation pressure and the production rate[2, 3]. In addition, the dynamic fluid level together with other pumping parameters can be used not only to determine the downhole pumping status, but also to perform well diagnosis and maintenance[4]. At present, numerous techniques have been developed to measure the dynamic fluid level, among which the acoustic method is the simple and widely used one. More specifically, an acoustic wave is first generated at the surface, transmitted to the dynamic fluid level in the annulus, and then reflected back to the surface. The time interval is recorded from the emission of the acoustic wave to the return of its reflection to the surface. Then the dynamic fluid level in the annulus is determined as the velocity of the acoustic wave in the air is known[5]. In practice, it is difficult to use this technique for measuring the real-time dynamic fluid levels where the automatic monitoring system is installed due mainly to its limitation of continuously generating the acoustic wave[6].
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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