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Record W2059896164 · doi:10.2118/147869-pa

New and Improved Methods for Performing Rate-Transient Analysis of Shale Gas Reservoirs

2012· article· en· W2059896164 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersConocoPhillips
KeywordsSlippageTight gasPermeability (electromagnetism)Petroleum engineeringShale gasHydraulic fracturingGeologyOil shaleGeotechnical engineeringEngineeringChemistryStructural engineering

Abstract

fetched live from OpenAlex

Summary Multifractured horizontal wells are currently the most popular method for exploiting low-permeability tight and shale gas reservoirs. Production data analysis is the most widely used tool for analyzing these reservoirs for the purpose of reserves estimation, hydraulic fracture stimulation optimization, and development planning (Ambrose et al. 2011). However, as pointed out by Clarkson et al. (2012), a fundamental problem with the application of conventional production data analysis to ultralow permeability reservoirs is that current methods were derived with the assumption that flow can be described with Darcy's law. This assumption may not be valid for tight/shale gas reservoirs, as they contain a wide distribution of pore sizes, including in some cases nanopores (Loucks et al. 2009). Therefore, the mean-free path of gas molecules may be comparable to or larger than the average effective rock pore throat radius, causing the gas molecules to slip along pore surfaces. This results in slippage non-Darcy flow, which is not accounted for in conventional production data analysis. Clarkson et al. (2012) modified the pseudovariables used for analyzing gas reservoirs in production data analysis to account for slippage. They demonstrated that if the effect of slippage is not considered, it leads to noticeable errors in reservoir characterization. Clarkson et al. (2012) also mentioned that even after using the modified pseudovariables, the values for permeability and fracture half-length do not exactly match the input data to simulation. In this paper, a methodology to properly analyze the production data from a fractured well in a tight/shale gas reservoir producing under a constant flowing pressure in the presence of desorption and slippage is presented. This method uses a new pseudotime definition instead of the conventional pseudotime currently being used in production data analysis. The method is validated using a number of numerically simulated cases. It is found that the newly developed analytical method results in a more reliable estimate of fracture half-length or contacted matrix surface area, if permeability is known.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.028
GPT teacher head0.330
Teacher spread0.302 · 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