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Record W2076069041 · doi:10.2118/162746-ms

Software Development for Petrophysical Analysis of Shale and Tight Formations

2012· article· en· W2076069041 on OpenAlex
Guang Yu, Roberto Aguilera

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE Canadian Unconventional Resources Conference · 2012
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPetrophysicsOil shaleGeologyPetroleum engineeringFormation evaluationReservoir modelingPorosityGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Shale and tight formations have long been a challenge for petrophysical interpretation. In the case of shales, the presence of clays and organic matter, complex mineralogy and pore structure make the log responses complicated. In tight reservoirs, the presence of connected and non-connected dissolution pores, microfractures and slot porosity also complicates the interpretations. This work seeks to integrate and digitize new petrophysical techniques and procedures that address these problems into a software system to assist with shale and tight reservoirs characterization. A petrophysics software system that includes dual and triple porosity models as well as elastic geomechanical properties has been developed to assist with the evaluation of shale and tight formations. Some critical petrophysical parameters can be quantified, such as matrix, fracture, non-connected and effective porosities, water saturation, total organic carbon, level of organic metamorphism, flow regimes (continuous vs. diffusion-like) at any pressure of interest, as well as Young modulus, Poisson’s ratio and minimum horizontal stress. Based on these estimates, detailed shale and tight reservoirs characteristics can be analyzed and the original hydrocarbons in place can be determined with good accuracy. Practical workflows for calculating each parameter are also organized and integrated. Object-oriented programming techniques are utilized for the development of this software considering its development life cycle for large-scale software development. Optimization capacity adopted in the current development for the reuse of the software components for future development is also explained. Two case studies using data from the Nikanassin formation in the Deep Basin of the Western Canada Sedimentary Basin (WCSB) and the Haynesville shale formation in Texas are presented to illustrate the software development and the application of the software. Conventional well log data, such as gamma ray, density, neutron, acoustic, resistivity, and cores and drill cuttings are utilized in the examples, which is further validated with other sources of information. It is concluded that the methodology developed in this software will prove valuable and facilitate the petrophysical evaluation of shale and tight formations.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.990

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 head0.021
GPT teacher head0.221
Teacher spread0.200 · 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