Completion and Fracture Modeling of Low-Permeability Gas Sands in South Texas Enhanced by Magnetic Resonance and Sound Wave Technology
Bibliographic record
Abstract
Completion and Fracture Modeling of Low-Permeability Gas Sands in South Texas Enhanced by Magnetic Resonance and Sound Wave Technology D. L. Fairhurst; D. L. Fairhurst Schlumberger Oilfield Services Search for other works by this author on: This Site Google Scholar J. P. Marfice; J. P. Marfice Schlumberger Oilfield Services Search for other works by this author on: This Site Google Scholar M. R. Seim; M. R. Seim Kerns Oil and Gas Inc. Search for other works by this author on: This Site Google Scholar M. A. Norville M. A. Norville Kerns Oil and Gas Inc. Search for other works by this author on: This Site Google Scholar Paper presented at the SPE/CERI Gas Technology Symposium, Calgary, Alberta, Canada, April 2000. Paper Number: SPE-59770-MS https://doi.org/10.2118/59770-MS Published: April 03 2000 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Fairhurst, D. L., Marfice, J. P., Seim, M. R., and M. A. Norville. "Completion and Fracture Modeling of Low-Permeability Gas Sands in South Texas Enhanced by Magnetic Resonance and Sound Wave Technology." Paper presented at the SPE/CERI Gas Technology Symposium, Calgary, Alberta, Canada, April 2000. doi: https://doi.org/10.2118/59770-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Unconventional Resources Conference / Gas Technology Symposium Search Advanced Search Abstract Recent advances in logging technology have enabled development of a better rock model and better fracture design for low-permeability reservoirs. The new measurements also have improved in-situ analysis and the identification of productive zones that might otherwise be bypassed.Sonic waveform and magnetic resonance technology enhances the standard logging platform by providing a more accurate shear modulus and permeability estimate. The accuracy is necessary for a better dimensional fracture model. The model appears reasonable for completions in the Olmos and San Miguel sands in south Texas. In some cases the magnetic resonance has identified previously bypassed permeable streaks that increased production. In other cases, sonic waveform technology has helped determine fracture direction, thereby enhancing gas drainage and well placement.In this paper, field production results are correlated to the model. Less efficient designs based on minimal data are compared with designs having more complete data sets. Recent completion data confirm that better parameters can be obtained with the new measurements. Keywords: permeability estimate, sonic data, olmo formation, society of petroleum engineers, resonance, gas sand, principal stress direction, magnetic resonance, stimulation design, permeability Subjects: Hydraulic Fracturing, Reservoir Characterization, Reservoir Fluid Dynamics, Reservoir Simulation, Formation Evaluation & Management, Flow in porous media, Open hole/cased hole log analysis Copyright 2000, Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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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) | 0.001 | 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 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".