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Record W2888680913 · doi:10.1190/int-2018-0067.1

Application of instantaneous-frequency attribute and gamma-ray wireline logs in the delineation of lithology in Serbin field, Southeast Texas: A case study

2018· article· en· W2888680913 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInterpretation · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
FundersImperial College LondonMcGill University
KeywordsLithologyGeologyPetrophysicsOil shaleLow frequencyWell loggingField (mathematics)SeismologyPorosityMineralogyPetrologyGeophysicsPaleontologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Although Serbin field in Southeast Texas was discovered in 1987, lithologic and petrophysical properties in the southeastern part of the field have not been fully evaluated. We have generated instantaneous frequency from 3D seismic data and predicted gamma-ray response volume from seismic attributes. By extracting maps of the instantaneous frequency and gamma-ray response along interpreted horizons, and crossplotting the instantaneous frequency against gamma-ray logs and integrating core data, we generated lithology maps to identify shale-prone zones that stratigraphically trapped hydrocarbons in the southeastern part of the field. We determine that Serbin field is separated into two areas: (1) a high-frequency, high-gamma-ray, and high-acoustic-impedance area in the northwest and (2) a low-frequency, low-gamma-ray, and low-acoustic-impedance area located in the southeast. By developing a lithologic map and relating it to the corresponding instantaneous-frequency map and log data, we also find that the southeastern part of the field can be divided into three zones: (1) zone 1, composed of approximately 0.7–2.7 m (approximately 2–8 ft) thick sandstone-rich beds of moderate frequency (25–30 Hz); (2) zone 2, composed of high-frequency (33–60 Hz) shale-rich zones that serve as stratigraphic-trapping-mechanisms; and (3) zone 3, composed of approximately 1.7–4 m (approximately 5–13 ft) thick sandstone-rich beds of low frequency (0–18 Hz) and relatively high porosity. These methods can be applied in other areas of the field with limited well control.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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