Vaca Muerta Characterization in the Parva Negra Oeste Block, Neuquén, Argentina
Bibliographic record
Abstract
Abstract The main objective of this study is to evaluate the development of the Vaca Muerta Formation in Parva Negra Oeste Block through horizontal wells. To perform this, two vertical wells drilled recently by Capex were characterized. All information obtained was integrated, including well logs, rock data such as cuttings, sidewall cores and core samples and also 2D/3D seismic. The first step was oriented to classify the Vaca Muerta Formation into electrofacies using a commercial software. As a result of this, four electrofacies were defined. Later, a geological characterization of the electrofacies was performed using lab data such as geochemical, mineralogical, petrographic and geomechanical studies. A structural and stratigraphic framework was already available from seismic interpretation. Finally, all this information was integrated to the seismic data in order to further understand their vertical and areal distribution in the Block. This study allowed us to define four electrofacies for the Vaca Muerta Formation in the Parva Negra Oeste Block from well logs and lab data obtained from two vertical wells drilled during the last two years by Capex. These electrofacies show the following vertical variation from base to top of the studied interval: a) organic mudstones, b) silty mudstones, c) radiolaritic mudstones with high porosity and high total organic content, and d) silty fossiliferous mudstones with low porosity and low total organic content. Ultimately, the integration of the geological characterization, a geomechanical model and the seismic interpretation allowed us to define a landing zone for future development of the Block based on hard data provided by well logs, rock information and geological – seismic interpretation. Prior drilling and subsequent well characterization allowed us to extend the knowledge of the northwestern zone of the Neuquén Basin, which is not densely drilled, adding high quality data, and to evaluate the possibilities of a future development of the Block through horizontal wells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".