Low Field NMR Water Cut Metering
Bibliographic record
Abstract
Abstract We have developed a new on line water cut meter using low field Nuclear Magnetic Resonance (NMR) technology. This instrument is designed for use on heavy oil systems where conventional instruments experience difficulties. We describe the process of developing and implementing this new technology. Data from successful field tests near Cold Lake, Alberta, Canada, shows that the instrument is capable of making water cut measurements over a wide range of fluid types and temperatures. The instrument is capable of functioning accurately where a wide range of emulsions and/or foams exists and where the salinity of the water phase can go through significant variations. The current application is for water cut measurements on well site. The instrument can be applied in any system where heavy oil / bitumen / water / gas / solid systems may be encountered. It can be used for water cut volume or mass fraction measurements. The instrument is equally capable of performing well site monitoring for regulatory / reconciliation purposes, for characterizing produced fluids, in separation, pipelining and upgrading processes for process control and quality testing. Introduction Over the past few years the Tomographic Imaging and Porous Media (TIPM) Laboratory has expanded into the use of low field Nuclear Magnetic Resonance (NMR) for various applications in the oil industry. Much of the work has centered around core analysis, but considerable efforts have also taken place in the area of analysis of fluid streams of various types(1–6). In co-operation with Canadian Natural Resources Limited (CNRL) we have operated a water cut meter utilizing low field NMR technology for approximately two years on two different cyclic steam injection heavy oil well pads. This represents perhaps a most difficult flow stream for any instrument to measure as there are extreme variations in water cut, temperature, flow rate and salinity as well as a variety of possible phases, making it difficult to get one instrument to be accurate for all likely conditions. In a previous paper1 we have shown that the technology is capable of measuring flow stream fluids containing water and bitumen over a wide range of water cuts and variations of the emulsion phase. In this paper we report on the field trials. The main challenges in the field are temperature compensation and automatic analysis - i.e. removing the expert from the instrument. The instrument itself is as described elsewhere1. There are a few key features that should be mentioned. The sensor part consists of an assembly of permanent magnets and transmitter/receiver coils. The permanent magnets cannot be exposed to temperatures greater than 80 °C without being damaged. Originally the instrument was designed for pre-conditioned process flow where the process stream was cooled to 60 °C in order to eliminate this problem. When it became clear how many other problems this would cause, the instrument was modified to handle higher temperatures. The main modification was to provide magnet cooling by injecting air between the sample tube and the magnet assembly. Unfortunately, the volume of air available on site limits the maximum process flow temperature to 150 °C.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".