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Record W2073838005 · doi:10.1115/imece2002-32348

A Pumping System to Enhance Production From Gas Wells

2002· article· en· W2073838005 on OpenAlexaffabout
Jeffrey J. Rudolf, T. R. Heidrick, Brian A. Fleck, R. K. Ridley, V. S. V. Rajan

Bibliographic record

VenueFluids Engineering · 2002
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPetroleum engineeringNatural gasWet gasVolumetric flow rateFlow (mathematics)Environmental scienceGeologyEngineeringMechanicsWaste management

Abstract

fetched live from OpenAlex

A new pumping technology has been developed and patented by the Alberta Research Council [1–3] to address the problem of liquid loading in natural gas wells at low, depleted pressures. This technology consists of a pump installed at the bottom of the well bore that is driven by the reservoir gas pressure to bring the produced liquids to the surface as they accumulate thereby improving gas production from shallow gas wells. The above pump concept has been investigated in two stages of research. In the first stage, a mathematical model was developed to estimate the minimum reservoir pressure required to prevent liquid build up in a gas well with either: • the reservoir pressure (and flow) itself carrying the produced liquids to the surface in a two-phase flow, or • the reservoir gas pressure powering a pumping device to carry the produced liquids to the surface in the most efficient manner possible. The objective of the second stage of this investigation was to look at the feasibility of using a reciprocating pump powered by gas pressure. In particular, the effect of the pump Area Ratio (ratio of the area being pushed by the gas to the area pushing the liquid) on the use of reservoir gas pressure was investigated. There are approximately 70,000 flowing gas wells in Western Canada and these gas wells were categorized by depth and production rate. From this list of gas wells, a typical well was chosen and its production data and well characteristics were incorporated into the mathematical model. The model was tested in both the above-mentioned investigations and the results show that there is a significant increase in the operating range when the reservoir pressure is used more efficiently to produce gas from the well. It was determined that higher pump area ratios lead to a more efficient use of reservoir pressure and for the gas well investigated in this study, an optimum area ratio of 40 was identified as the best design. The concept of multistage pumping was also investigated. The results presented are the basis for experiments presently being designed that will validate the current model of the system and allow for possible improvements.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.188
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations0
Published2002
Admission routes2
Has abstractyes

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