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Record W4235125936 · doi:10.2523/99386-ms

How Reliable Is Fluid Gradient in Gas/Condensate Reservoirs?

2006· article· en· W4235125936 on OpenAlex
C. Shah Kabir, Julian Pop

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of SPE Gas Technology Symposium · 2006
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCitationComputer scienceDownloadInformation retrievalLibrary scienceOperations researchWorld Wide WebEngineering

Abstract

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How Reliable Is Fluid Gradient in Gas/Condensate Reservoirs? C. Shah Kabir; C. Shah Kabir Chevron Corp. Search for other works by this author on: This Site Google Scholar Julian Pop Julian Pop Schlumberger Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Gas Technology Symposium, Calgary, Alberta, Canada, May 2006. Paper Number: SPE-99386-MS https://doi.org/10.2118/99386-MS Published: May 15 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Kabir, C. Shah, and Julian Pop. "How Reliable Is Fluid Gradient in Gas/Condensate Reservoirs?." Paper presented at the SPE Gas Technology Symposium, Calgary, Alberta, Canada, May 2006. doi: https://doi.org/10.2118/99386-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Unconventional Resources Conference / Gas Technology Symposium Search Advanced Search AbstractCollection and analysis of gas/condensate fluid samples present considerable challenges. That is because downhole sampling of a gas/condensate fluid, unlike its oil counterpart, does not guarantee retrieval of single-phase fluid. The same is true for surface sampling because of incomplete surface and/or downhole separation. Given this reality, the PVT analysis of any fluid sample with an equation-of-state (EOS) model demands that the results are verified with independent measurements.Our analyses of many samples show that a good correspondence exists between the PVT-derived gradient and that obtained from wellbore-flow modeling of production-test data. Older generation formation testers, those prior to 1990, although yielding comparable results, had larger error bars owing to system limitations in repeatability of both pressure and depth measurements.We developed a yield-temperature correlation to fill in the information void for reservoirs that fall within the bounds of measured data over a large geographic area. Correlating CO2 with formation temperature was a stepping stone to the yield/temperature relationship. This approach is applicable for the analysis of both single-reservoir and multi-reservoir samples, which is particularly useful when rapid assessment is needed over large regions.IntroductionThe presence of a compositional gradient in reservoirs containing hydrocarbon columns has long been recognized since Sage and Lacey (1939) published their seminal work. Segregation of asphaltenes causes compositional grading in oil (20–30 ºAPI) columns. In contrast, compositional grading in light-hydrocarbon (> 35 ºAPI) columns occurs for near-critical fluids or, more appropriately, for fluids close to the spinodal curve (Lira-Galeana 1992). Equilibrium between gravitational and chemical forces of various hydrocarbon components results in a variable saturation pressure in a fluid column (Schulte 1980; Riemens et al. 1988; Wheaton, 1991). According to Hirschberg (1988), the time to reach such equilibrium (10 million to 1 billion years) is comparable to the geologic time of a typical reservoir.A number of authors have reported field experiences with compositional grading in gas/condensate reservoirs (Creek and Schrader 1985; Smith et al. 2000; Ghorayeb et al. 2003). Ordinarily, the equilibrium approach appears to explain gradients observed in the field. In reality, however, heat flux can potentially prevent attaining true equilibrium in a hydrocarbon column owing to temperature gradient in a reservoir (Pedersen and Lindeloff 2003; Hoier and Whitson 2001; Ghorayeb and Firoozabadi 2000; Firoozabadi 1999). Irreversible thermodynamics appears to explain compositional grading in most systems. In this study, we will assume that thermal diffusion does not play a dominant role in distributing hydrocarbon components in the fluid columns studied.As discussed, depth-dependent fluid property variation has been shown to occur by discerning PVT properties (Hanafy and Mahgoub 2005; Smith et al. 2004; Montel et al. 2003). However, direct comparison of independent measurements contributing to fluid gradients has been rare. The principal objective of this study is to compare fluid gradients from three different sources to seek consistency, en route to establishing liquid content in gas/condensate systems. These independent sources include (1) EOS-model-derived compositional grading, (2) spot pressures measured by wireline formation testers, and (3) wellbore static gradient from a dynamically calibrated drillstem test (DST) data.Case StudiesSpot pressures and the attendant fluid gradients derived from wireline formation testers (FT) are invaluable to all, earth scientists and engineers alike. While the ability of formation testers to reveal fluid gradients is seldom questioned, we probe whether fluid gradients of sufficient accuracy can be discerned to yield reliable liquid content in gas-condensate systems.In this study, besides FT we examined two other sources of fluid gradient information; compositional gradients based on EOS models and the static-fluid gradient obtained from a calibrated wellbore flow model. The compositional gradient is obtained after tuning an EOS model and the wellbore model is calibrated with DST flowing pressures and temperatures at both bottomhole and wellhead. Note that all the necessary ingredients, such as surface rates of both phases, pressures and temperatures at both wellhead and sandface, are available from a DST. Keywords: fluid modeling, Reservoir Surveillance, PVT measurement, liquid content, correlation, presentation, production control, equation of state, drillstem/well testing, liquid dropout Subjects: Well & Reservoir Surveillance and Monitoring, Fluid Characterization, Formation Evaluation & Management, Phase behavior and PVT measurements, Fluid modeling, equations of state, Drillstem/well testing This content is only available via PDF. 2006. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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