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Record W2918068819 · doi:10.2118/1106-0068-jpt

Overview: Gas Production Technology (November 2006)

2006· article· en· W2918068819 on OpenAlexaboutno aff
Edward Wichert

Bibliographic record

VenueJournal of Petroleum Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsNatural gasPetroleum engineeringFossil fuelEnvironmental scienceLiquefactionAssociated petroleum gasWaste managementGeologyEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

The gas-production and -processing industry continues to apply new technologies, as well as improve old technologies, to produce gas and bring it to market. For many years, gas in remote locations had virtually no value because markets were not within economic reach by pipeline. In recent years, with the increase in the value of oil and the products derived from oil, technologies to convert natural gas chemically to liquid hydrocarbons are being applied to monetize remote gas. This increase in gas-liquefaction capacity is in addition to the older technology that physically changes phases of natural gas from gaseous to liquid by deep cooling for transportation to market. Natural gas often is produced from tight geological formations. To produce gas from low-permeability reservoirs economically, it is necessary to hydraulically fracture the rock. This process requires pumping a large amount of water or a suitable hydrocarbon liquid at high pressure as carrier fluid for the proppant. Minimizing the leakoff of the fluid being pumped enhances the effectiveness of such stimulation treatments. New approaches to the selection of specific fluid additives, designed to reduce surface tension and leakoff, can extend the fracture length and increase the well's productivity. A common hindrance to gas production in low-productivity gas wells is the ever-present problem of coproduction of water. While this problem has been studied extensively in the past, new technology can be combined with existing technology to extend the productive life of low-rate gas wells. For high-pressure gas production, a reduction of the water vapor contained in the produced gas can be achieved through the application of supersonic nozzles, in place of traditional dehydration methods. The above-mentioned topics and other innovations regarding gas production technology were examined in papers presented during the past year at various SPE technical meetings worldwide. Gas Production Technology additional reading available at the SPE eLibrary: www.spe.org SPE 100442 "Selective Removal of Water From Supercritical Natural Gas" by A. Karimi, Memorial U. of Newfoundland, et al. SPE 98285 "Arqumia Field: Mexico's Highest-Deliverability Gas Well" by A.E. Guzmán, SPE, Pemex E&P, et al. SPE 97070 "Identifying the Timing and Sources of Damage in Gas-Storage Wells Using Smart Storage Technology" by J.P. Spivey, SPE, Phoenix Reservoir Engineering, et al.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.246
Teacher spread0.238 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2006
Admission routes1
Has abstractyes

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