A New Approach for Geomechanical Evaluations with Modified Pickett Plots
Bibliographic record
Abstract
Abstract A Pickett plot is a powerful graphical technique for petrophysical analysis of well logs, which was developed initially to represent Archie's equation visually. Pickett plots rely on pattern recognition on a log-log scale observable on a set of porosities and the corresponding true resistivities taken from well logs. The analyses of these plots have been used in the past, primarily for the determination of water saturation. However, throughout the past years, Pickett plots have been extended and modified for the evaluation of other reservoir parameters of interest, such as permeability, process/delivery speed, bulk volume water, and pore throat apertures. In some recent works, applications of the Pickett plot have been extended from representing only a snapshot on time to describing and explaining several millions of years of burial, compaction, maturation trajectories, and petroleum generation. The word ‘petroleum’ as used in this paper includes oil, gas, and natural gas liquids. In this study, the Pickett plot has been modified and extended to include geomechanical parameters such as Vp/Vs, Poisson's ratio, Young's modulus, Shear modulus, bulk modulus, friction angle and Unconfined Compressive Strength (UCS). A better understanding of these parameters helps to minimize risks associated with drilling, stimulation, and wellbore stability problems. Geomechanical characterization is vital to understand fracture creation and propagation. Hydraulic fractures are more likely to be generated in brittle zones with lower tensile strength, lesser Poison's ratio, and higher Young's modulus. Mechanical properties are usually measured in laboratory experiments such as Triaxial Compression Tests carried out on core samples. But cores are not always available for testing; therefore, the original contribution of this paper is the construction of a modified Pickett plot that can help to perform quick and reasonable evaluations of geomechanical properties while at the same time carrying out standard petrophysical analysis of petroleum reservoirs. This type of integrated petrophysical-geomechanical interpretation on a single plot is not currently available in the literature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".