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Record W2050176749 · doi:10.2118/149404-ms

Analysis of Production Data in Shale Gas Reservoirs: Rigorous Corrections for Fluid and Flow Properties

2011· article· en· W2050176749 on OpenAlex
M.. Nobakht, Christopher R. Clarkson

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 Eastern Regional Meeting · 2011
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsEncana (Canada)University of Calgary
FundersConocoPhillips
KeywordsSlippagePermeability (electromagnetism)Tight gasFlow (mathematics)Petroleum engineeringRelative permeabilityShale gasOil shaleSquare rootMechanicsGeologyMathematicsGeotechnical engineeringMaterials scienceHydraulic fracturingChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Analysis of long-term linear flow periods associated with shale gas production has received much attention in recent literature as a means of obtaining information about stimulation efficiency. However, the most popular methods for analysis (ex. square-root of time plot) can lead to incorrect characterization. Nobakht and Clarkson (2011a) demonstrated that the square root-time plot may not be a straight line for constant gas rate production linear flow and the non-linear shape may lead to incorrect flow regime identification. The square root-time plot is however a straight line for constant flowing pressure (Nobakht and Clarkson, 2011b). Ibrahim and Wattenbarger (2005; 2006) and Nobakht and Clarkson (2011b) showed that using the slope of square root-time plot, for constant flowing pressure constraint, leads to an overestimation of fracture half-length. Additional important considerations for shale gas analysis are non-Darcy flow and non-static reservoir properties. Clarkson et al. (2011) demonstrated that ignoring gas slippage effects, thought to be important in ultra-low permeability reservoirs, can cause errors in reservoir characterization. They incorporated slippage into pseudo-variables for production data analysis, as has been done with non-static permeability (Thompson et al., 2010). Finally, Nobakht et al. (2011) extended the methodology proposed by Nobakht and Clarkson (2011b) to properly analyze linear flow in the presence of slippage and desorption. The purpose of the current work is to evaluate the current methods for analyzing linear flow in shale gas reservoirs, and establish which method is the most accurate for reservoir characterization. First, recent studies addressing linear flow under constant flowing pressure and constant gas rate production are briefly reviewed. Then, a comparison among the above-mentioned methods for calculating fracture half-length or contacted matrix surface area is made. It is shown that Nobakht et al. (2011) method yields the fracture half-lengths that best match the expected values for constant flowing pressure. Finally, we present a method for analyzing linear flow for real production data, where neither flowing pressure nor gas rate is constant. The method is validated using three numerically-simulated cases. It is found that this method works well for the three cases provided.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.071
GPT teacher head0.245
Teacher spread0.174 · 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