Viscosity Predictions for Crude Oils and Crude Oil Emulsions Using Low Field NMR
Bibliographic record
Abstract
Viscosity Predictions for Crude Oils and Crude Oil Emulsions Using Low Field NMR J. Bryan; J. Bryan University of Calgary Search for other works by this author on: This Site Google Scholar A. Kantzas; A. Kantzas University of Calgary Search for other works by this author on: This Site Google Scholar C. Bellehumeur C. Bellehumeur University of Calgary Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, September 2002. Paper Number: SPE-77329-MS https://doi.org/10.2118/77329-MS Published: September 29 2002 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Bryan, J., Kantzas, A., and C. Bellehumeur. "Viscosity Predictions for Crude Oils and Crude Oil Emulsions Using Low Field NMR." Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, September 2002. doi: https://doi.org/10.2118/77329-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Annual Technical Conference and Exhibition Search Advanced Search AbstractKnowledge of oil viscosity is vital to the petroleum industry, and is especially important when considering production of heavy oil and bitumen. As viscosity increases, conventional measurements become progressively less accurate and more difficult to obtain. Oil viscosities measured in the lab may also be not indicative of true in-situ viscosities. An alternate method is required for predicting oil viscosity, especially if this method can be applied in-situ. Stable crude oil emulsions are prevalent in many stages of the production and transport of heavy oil and bitumen. Knowledge of emulsion viscosity is necessary for determining energy requirements for transport and upgrading of the produced crude.Low field nuclear magnetic resonance is examined in this work for its potential to predict viscosity of crude oil and crude oil emulsions. NMR is an attractive alternative to conventional viscosity measurements, because it can provide fast, unbiased and non-destructive data. A correlation is presented that predicts fluid viscosities from under 1 cP to over 3 000 000 cP over 25–80°C, making it valid over a wider range of viscosities and temperatures than any other published NMR viscosity correlation. With tuning, this model can predict very accurate changes in viscosity with temperature for a single oil. An NMR emulsion viscosity model is also presented that uses the oil viscosity and water fraction, both determined from NMR, to predict emulsion viscosity. This correlation is able to provide order of magnitude emulsion viscosity predictions for a wide range of emulsion water cuts and viscosities. Work has also been done to extend the viscosity predictions to in-situ viscosity measurements, which can then be extracted from logs. Preliminary findings on in-situ oil viscosity are encouraging, and indicate that NMR has great potential as a tool for in-situ viscosity determination.IntroductionKnowledge of oil viscosity is essential to many areas of the petroleum industry, from reservoir engineering and enhanced oil recovery to upgrading and transport of produced fluids. When producing heavy oil and bitumen, the high viscosities are one of the major impediments to recovering these oils. Oil viscosity is often correlated directly to the reserves estimate in heavy oil and bitumen formations1, and can determine the success or failure of a given EOR scheme. As a result, viscosity is an important parameter for doing numerical simulation and determining the economics of a project.Water-in-oil emulsions, also known as crude oil emulsions, are also prevalent in the industry. All oil is produced along with some water, and for heavier crudes, which are usually produced using injected steam, the water cut can be significant. Knowledge of emulsion viscosity can aid in determining energy requirements for transport and upgrading of these fluids2.As viscosity increases, conventional measurements become progressively less accurate and more difficult to obtain. Oil samples and emulsions extracted and measured in the lab may also no longer be representative of in-situ or on site conditions1. An alternate method of measuring the viscosity of crude oils and crude oil emulsions would therefore be of great value to the petroleum industry. Low field nuclear magnetic resonance (NMR) is an attractive alternative to conventional viscosity measurements, as its measurements are fast, non-destructive and insensitive to technician error. Low field NMR is an accepted tool in conventional oil sandstone reservoirs, but has so far found only limited use in heavy oil and bitumen analysis. This work demonstrates that NMR can in fact be a valuable technology for heavy oil and bitumen formations like those in Alberta. Keywords: nmr, spectrum, viscosity prediction, viscosity model, relaxation, viscosity, droplet size, bitumen, spe 77329, emulsion Subjects: Formation Evaluation & Management, Open hole/cased hole log analysis This content is only available via PDF. 2002. Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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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 | 0.000 | 0.000 |
| 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 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".