Vaca Muerta: Naturally Fractured and Oil-Wet Shale Characteristics Revealed by Water Saturation (Sw) Modeling Using Archie's Equation and Pickett Plot
Bibliographic record
Abstract
Abstract Sw modeling in Vaca Muerta using ‘resistivity-based’ methods has been recognized as challenging due to the complex mineralogical and depositional settings of Vaca Muerta. Consequently, ‘resistivity-free’ methods are commonly preferable. In this study, Sw modeling using Archie's equation (1942) and Pickett plots (1966, 1973) have been used with the inclusion of thin bed heterogeneity. Despite the complexity, the analysis reveals the variability of both naturally fractured and oil-wet shale characteristics of Vaca Muerta. Several published studies have used Archie's equation to model Sw in Vaca Muerta, but often assumed that the porosity exponent, m is equal to the water saturation exponent, n. In this study, a new approach is presented using Archie's equation, but this time with the m and n being determined from Pickett plots for each stratigraphic unit. Although this method is simple, no such application has been published for the studied area. This technique is very powerful as it helps to relate the vertical variation of m and n to the complex pore system and wettability characteristics in Vaca Muerta. The Sw analysis using Archie's equation and Pickett plots shows vertical variability in m and n values in each stratigraphic unit of a vertical well. The decreasing m and increasing n values with depth are corroborated by the increasing natural fractures intensity and oil wettability towards the Lower Vaca Muerta (LVM), as indicated by the cuttings descriptions, micro-resistivity images and a published Scanning Electron Microscopy (SEM) study. Better reservoir quality lies in the deeper section, especially the LVM with lower Sw, higher Total Organic Carbon (TOC) and porosity. The organic rich unit also has a higher intensity of thin bed heterogeneity, which comprises bedding parallel calcite-filled microfractures (beef), ash beds and calcite nodules. This emphasizes the criticality of including them in petrophysical evaluation. The most pronounced effect of thin bed heterogeneity is on the resistivity log. Despite the complexity, the modelled Sw matches well the Sw determined from retort and Dean Stark measurements. This shows that resistivity and porosity-based techniques, such as Archie's equation and Pickett plots are applicable in the complex Vaca Muerta shale. Through analysis of Sw modeling using Archie's equation and Pickett plot, the variability of naturally fractured and oil-wet shale characteristics are revealed in each stratigraphic unit of a vertical well in Vaca Muerta. Despite its complexity, the analysis also includes, for the first time, thin bed heterogeneity. These challenges do not hinder the application of the above resistivity and porosity-based techniques which are proven to be powerful tools for characterizing the complex Vaca Muerta shale.
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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 | 0.000 | 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) | 0.000 | 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".