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Record W2043491075 · doi:10.2118/103514-jpt

Coalbed- and Shale-Gas Reservoirs

2008· article· en· W2043491075 on OpenAlexaboutno aff
Creties Jenkins, C.M. Boyer

Bibliographic record

VenueJournal of Petroleum Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCoalbed methaneOil shalePetroleum engineeringNatural gasDrillingGeologyFossil fuelShale gasUnconventional oilMining engineeringPetroleumEngineeringCoalCoal miningPaleontologyWaste management

Abstract

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Distinguished Author Series articles are general, descriptive representations that summarize the state of the art in an area of technology by describing recent developments for readers who are not specialists in the topics discussed. Written by individuals recognized as experts in the area, these articles provide key references to more definitive work and present specific details only to illustrate the technology. Purpose: to inform the general readership of recent advances in various areas of petroleum engineering. Introduction Annual natural-gas production from coalbed- and shale-gas reservoirs in the US is approximately 2.7 Tscf, which represents 15% of total natural-gas production. Approximately 1.7 Tscf of this gas comes from more than 40,000 coalbed gas wells completed in at least 20 different basins. The remaining 1.0 Tscf comes from more than 40,000 shale gas wells completed in five primary basins. While the pace of coalbed-gas drilling is starting to slow, shale gas continues to be one of the hottest plays in the US, and drilling is expanding rapidly, especially in the south-central US (the Barnett shale and its equivalents), the Appalachian basin, and numerous Rocky Mountain basins. Outside the US, more than 40 countries have investigated the potential of coalbed gas, resulting in commercial projects in Australia, Canada, China, and India. No commercial shale-gas projects currently exist outside of the US, but work continues to identify both new shale-gas reservoirs and to add incremental shale-gas production in existing reservoirs. Given that worldwide coalbed-gas resources are estimated to exceed 9,000 Tscf and shale-gas resources are estimated to exceed 16,000 Tscf, it is clear that tremendous potential exists for future growth (Kawata and Fujita 2001). Reservoir Fundamentals Coals are sedimentary rocks containing more than 50 wt% organic matter, whereas shales contain less than 50 wt% organic matter. Methane is generated from the transformation of this organic matter by bacterial (biogenic gas) and geochemical (thermogenic gas) processes during burial. The gas is stored by multiple mechanisms including free gas in the micropores and sorbed gas on the internal surfaces of the organic matter. Nearly all coalbed gas is considered to be sorbed gas, whereas shale gas is a combination of sorbed gas and free gas. Coalbed-gas reservoirs contain an orthogonal fracture set called cleats that are oriented perpendicular to the bedding and provide the primary conduit for fluid flow. Gas diffuses from the matrix into the cleats and flows to the wellbore. In shale-gas reservoirs, gas is sometimes produced through more-permeable sand or silt layers interbedded with the shale, through natural fractures, or from the shale matrix itself. In some cases, natural fractures are healed by a mineral filling and must be forced open by hydraulic-fracture stimulation. It also is possible to have both shales and coals interbedded in a single reservoir, resulting in gas contributions from both lithologies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.007

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 head0.010
GPT teacher head0.206
Teacher spread0.197 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations184
Published2008
Admission routes1
Has abstractyes

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