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Record W2434511543 · doi:10.2118/180884-ms

An Integrated Method to Characterize Shale Gas Reservoir Performance

2016· article· en· W2434511543 on OpenAlexafffund
Jie Zhan, Steve Seetahal, Jinhong Cao, S. Hossein Hejazi, D.. Alexander, Rongjie He, Kunyan Zhang, Zhangxin Chen

Bibliographic record

VenueSPE Trinidad and Tobago Section Energy Resources Conference · 2016
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaKorea Research Council of Fundamental Science and TechnologyCMG Reservoir Simulation FoundationUniversity of Calgary
KeywordsHydraulic fracturingPetroleum engineeringGeomechanicsOil shalePermeability (electromagnetism)Reservoir simulationGeologyTight gasFracture (geology)Geotechnical engineering

Abstract

fetched live from OpenAlex

Abstract The application of horizontal well drilling coupled with the multistage fracturing technology enables commercial development of shale gas formations. However, due to the complexity of fracture network propagation, simulation of such reservoirs is challenging and associated with uncertainties. In order to minimize the uncertainty of modeling, we correlate first-hand pumping schedule data with the reservoir performance directly through coupling a fracking process with a reservoir simulator. This provides us an integrated way to characterize a well trajectory, hydraulic fracture configurations and shale gas reservoir performance. In addition, a geomechanical effect on the reservoir performance under certain fracture configurations is studied using a geomechanics module developed by CMG Ltd. GOHFER is widely used in a hydraulic fracking analysis. In this work, we couple GOHFER simulation output with the CMG module to determine the hydraulic fracture configuration. Thus, a method to correlate the first-hand pumping data (a slurry rate, slurry concentration and pumping pressure) with the reservoir simulator is given. Because of the stress sensitivity of a shale formation, we employ a linear-elastic constitutive law to depict the rock behavior with Young's modulus of 5,000,000 psi and Poisson's ratio of 0.2. Moreover, a Barton-Bandis model is used to describe the tensile opening of natural fractures for the dual-permeability reservoir model. From a series of numerical simulation studies, we find that the effective normal stress will increase with the development of a shale gas reservoir which will lead to a decrease in porosity and permeability. For the base case without a geomechanics effect, it will produce higher cumulative gas production than the case with the geomechanics effect. When producing for six months, the difference of the cumulative gas production between the two cases is 14.3%. The integrated process provides insights about shale gas reservoir performance with available data and handy tools.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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Same venueSPE Trinidad and Tobago Section Energy Resources ConferenceSame topicHydraulic Fracturing and Reservoir AnalysisFrench-language works237,207