Vaca Muerta: An Emerging Shale Petroleum Reservoir
Bibliographic record
Abstract
Abstract Argentina is ranked second globally in terms of technically recoverable shale gas, and fourth in shale oil (EIA 2015). The most prolific shale is the Vaca Muerta formation. The objective of this paper is to present geological and reservoir characterization, drilling and production strategies, as well as historical performance and economics of Vaca Muerta. The word petroleum as used in this paper includes oil, natural gas, and natural gas liquids. This paper describes natural fractures and their impact on hydrocarbon productivity. The successful commercial production from this unconventional resource has been driven by many factors, including regional geology, availability of advanced technology such as horizontal drilling and multi-stage hydraulic fracturing, as well as domestic and regional hydrocarbon demand (Sierra 2016). Vaca Muerta itself is very unique with multiple hydrocarbon windows from east to west, ranging from dry gas to wet gas, to light oil and black oil. The productivity of Vaca Muerta is benchmarked to some of the best US shale plays such as the Eagle Ford and the Marcellus. Vaca Muerta contains 1202 Tcf of risked gas in-place and 270 billion barrels of risked oil in-place. It is estimated that 308 Tcf and 16 billion barrels of these resources are technically recoverable (EIA 2015). To date, the total number of horizontal wells exceeds 600, mostly drilled in the black oil window (Secretaria de Energia de Argentina 2020; Wood Mackenzie 2020b). Dubbed the ‘golden goose’ of Argentina, the last decade has seen rapid exploration and development activities. The Argentina state oil company (YPF) leads the development in this region together with its partners. In 2019, production from Vaca Muerta reached 90,000 bbl/d of oil and 1180 MMcf/d of gas, contributing 21% of Argentina's total production (Secretaria de Energia de Argentina 2020; Wood Mackenzie 2020b). YPF predicted these rates would increase by 150% in 2022 (Rassenfoss 2018). Part of this increase will be contributed by La Amarga Chica block, where YPF and its partner, PETRONAS approved their 30-year master development plan in late 2018 to deliver 54,000 boe/d by 2022 (Zborowski 2019). This production increase has obviously been delayed due to the COVID-19 pandemic. The novelty of this paper is integration of geological and reservoir characterization, drilling and production strategies, as well as historical performance and economics of Vaca Muerta. It is concluded that oil and gas potential in the Vaca Muerta shale is significant and rivals the potential of some of the shales widely developed in the Unites States and Canada.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".