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Record W4245207947 · doi:10.2523/78971-ms

Addressing the Clay/Heavy Oil Interaction When Interpreting Low Field Nuclear Magnetic Resonance Logs

2002· article· en· W4245207947 on OpenAlexafffundabout
F. Manalo, J. Bryan, A. Kantzas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of Calgary
FundersCanada Research ChairsUniversity of Calgary
KeywordsCitationLibrary scienceComputer science

Abstract

fetched live from OpenAlex

Addressing the Clay/Heavy Oil Interaction When Interpreting Low Field Nuclear Magnetic Resonance Logs F.P. Manalo; F.P. Manalo University of Calgary, TIPM Laboratory Search for other works by this author on: This Site Google Scholar J.L. Bryan; J.L. Bryan University of Calgary, TIPM Laboratory Search for other works by this author on: This Site Google Scholar A. Kantzas A. Kantzas University of Calgary, TIPM Laboratory Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference, Calgary, Alberta, Canada, November 2002. Paper Number: SPE-78971-MS https://doi.org/10.2118/78971-MS Published: November 04 2002 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Manalo, F.P., Bryan, J.L., and A. Kantzas. "Addressing the Clay/Heavy Oil Interaction When Interpreting Low Field Nuclear Magnetic Resonance Logs." Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference, Calgary, Alberta, Canada, November 2002. doi: https://doi.org/10.2118/78971-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 International Thermal Operations and Heavy Oil Symposium Search Advanced Search AbstractLow field nuclear magnetic resonance (NMR) in the form of logging tools, bench top analysers or on-line sensors has shown tremendous promise for the interpretation of logs and subsequent characterization of heavy oil and bitumen reservoirs as well as the evaluation of recovery efficiency. The key for this success is the ability to identify properly the NMR response of the heavy oil and bitumen components of the spectra. Contrary to earlier belief on this topic, NMR can detect at least part of the response of heavy oil and bitumen either down-hole or in the production line. The majority of the spectra for heavy oil and bitumen samples are detected at relaxation times less than 10 ms. In clay free sands this spectrum is quite clear and the response of the NMR interpretation algorithms is accurate. However, the spectra of sand containing clays show clay bound water to be in the same range as bitumen. Not properly accounting for the contribution of the clay bound water in NMR spectra results in the overestimation of oil or bitumen content of a given formation. This paper presents experimental results of heavy oil samples and also the spectra of clay bound water for common clays found in Alberta and Saskatchewan. After the spectra are compared independently, sand packs containing different amounts of clay and bitumen are prepared and their NMR spectra are obtained. Patterns of spectra overlapping are identified and a preliminary clay bound water prediction algorithm is presented. This algorithm allows for the separation of the oil contribution from the total NMR spectrum. Examples from different formations illustrate the process by which NMR can be used to determine the oil saturation in different Alberta formations.IntroductionNuclear magnetic resonance (NMR) logging tools have been used in numerous applications within the petroleum industry. In addition to porosity and permeability determination, NMR has been used to analyse heavy crude oils, analogous to the saturates-aromatics-resins-asphaltenes test1, composition determination of oil/water emulsions3,4. NMR spectra contain a vast amount of information but present NMR logging tools are incapable of detecting the complete spectrum from heavy oil and bitumen formations, which has made characterization attempts problematic. While high field NMR can overcome this problem, it is not possible to implement this technology downhole or in water/oil/solids mixtures. Low field is more appropriate for analysis of porous media because the lower field gradient minimizes the possibility of data degradation over the course of the measurement5. While fluids produce characteristic spectra, amplitude peaks for heavy oil and clay bound water appear at similar relaxation times (T2), making it difficult to differentiate between the oil and water signals from a sample that contains both fluids6. This makes the T2 cutoff method7, implemented by many, impossible to use because the assumption that the signal below the T2 cutoff value is due to oil alone is wrong. Some of the signal below the T2 cutoff is due to water bound to clays. Making the distinction between amplitude signals due to oil and clay bound water is important for determining oil and water saturations. Attempts have been made to separate oil and water signals by using multiple time-echo (TE) values8 but this is not applicable for heavy oil and bitumen. Others have tried utilizing dual wait-time to separate signals7 however this is not applicable for use on heavy oil or bitumen samples with clay bound water.The purpose of this paper is to determine the effect of clay content and type on NMR spectra of brine and/or heavy oil in clay/sand mixtures. The results obtained from these experiments were used to formulate an algorithm for differentiating between clay bound water and bulk heavy oil in NMR logs. The ability to do so would enable one to determine oil and brine saturation in samples containing heavy oil and clay bound water, thus increasing the value of using NMR logging tools in the petroleum industry. Keywords: heavy oil, clay sand mixture, brine, clay concentration, composition, clay content, saturation, relaxation time, well logging, upstream oil & gas Subjects: Formation Evaluation & Management, Open hole/cased hole log analysis This content is only available via PDF. 2002. SPE/PS-CIM/CHOA International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference 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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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.

Opus teacher head0.026
GPT teacher head0.315
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations2
Published2002
Admission routes3
Has abstractyes

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