MétaCan
Menu
Back to cohort
Record W2319815522 · doi:10.2118/176835-ms

Reservoir Characterisation of the Spring Gully Coal Seam Gas Field

2015· article· en· W2319815522 on OpenAlexaff
Xuejun Lin, Petrina Weatherstone, David Weichman

Bibliographic record

VenueSPE Asia Pacific Unconventional Resources Conference and Exhibition · 2015
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsGeologySpring (device)Coal miningHydrology (agriculture)Natural gas fieldProductivityCoalPermeability (electromagnetism)Structural basinReservoir simulationField (mathematics)Hot springMining engineeringEarth sciencePetroleum engineeringGeomorphologyNatural gasPaleontologyGeotechnical engineeringGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract The Spring Gully coal seam gas (CSG) field, operated by Origin Energy on behalf of Australia Pacific LNG, is located in the southern region of the Bowen Basin. Commercial production commenced in 2005 from the Late Permian Bandana coal seams. This paper describes the reservoir characterisation methodology employed to history match geologically unique regions of the Spring Gully field and to understand production mechanisms across the field. In addition, the paper presents a detailed discussion on how learnings from the developed region of the field has been applied to characterise the future development regions of the field for forecasting. The Spring Gully CSG field exhibits a large degree of localized heterogeneity and extensive regional geological variability. Strong gas productivity and rapid water gas ratio decline have been observed in the north-eastern region of the field. While in the western portion of the field there exists moderate gas productivity and minimal water decline. A comprehensive, multi-disciplinary evaluation of the Spring Gully CSG field reservoir and production characteristics was performed in 2014. A reservoir simulation model has been constructed based on a number of geological and reservoir characterisation studies, combined with reservoir inputs and production analysis. The integrated subsurface model forms the basis to understand Spring Gully CSG field production mechanisms and ultimately to perform production forecasts for reserve and resource estimates, for ongoing reservoir management needs and appropriately size gas and water treatment facilities. A novel approach of constructing the permeability and porosity distribution in the reservoir model was implemented. Historical well peak water and gas rate, rig testing water rate and welltest-derived permeability were used to construct the permeability distribution in the model. The permeability distribution was transformed to porosity distribution. The faulting and compartmentalisation were introduced in the north-eastern region of Spring Gully reservoir model during the history match stage to match the rapid decline of reservoir pressure. The learnings obtained from studying well production mechanisms and model history matching were subsequently applied to the undeveloped regions of the field. Extensive validation and quality control of forecast methodology, forecast parameters assumptions and life-of-field production forecasting were performed.

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 score0.381
Threshold uncertainty score0.396

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)0.0000.000

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 head0.025
GPT teacher head0.225
Teacher spread0.199 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueSPE Asia Pacific Unconventional Resources Conference and ExhibitionSame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207