65 Years of Fracturing Experience: The Key to Better Productivity is Not What we Have Learned but What we Have Forgotten and Failed to Utilize!
Bibliographic record
Abstract
Abstract Many engineers today do not have the training needed to fully understand the importance of fracture mechanics principles and are easily overwhelmed in trying to deal with proper proppant and fluid selections, perforation design and strategy, and on-site quality control of the fracturing process. The unfortunate reality is that many fracture designs are improperly engineered with critical reservoir and hydraulic fracture parameters either ignored or improperly addressed. Many completions are either marginally economical or produce at reduced commercial rates. Regardless of reservoir type, it is critically important to achieve a highly conductive hydraulic fracture that provides connectivity between the reservoir and the wellbore. Since its inception, fracturing and completion knowledge has expanded exponentially allowing the oil and gas industry to develop ultra-low permeability unconventional reservoirs. During the 1980's and 1990's technology pioneers such as Holditch, Nolte, Warpinski, Veatch, and others, further developed the principles of fracturing which recognize the importance of critical fracture parameters and their effect upon initial productivity and ultimate recovery. These gains in expertise have resulted in unprecedented activity in the Bakken, Eagle Ford, Barnett, Haynesville, and Marcellus with increasing activity in new reservoirs such as the Utica, Niobrara, and Mississippian. Although each of these reservoirs is unconventional, each is uniquely different with respect to lithology, permeability, and hydrocarbon chemistry and interaction. This paper will challenge the industry notion that infinitely conductive fractures are being placed in many unconventional completions. It further addresses the critical fracturing parameters required to achieve a high conductivity fracture, why they are important, and how to achieve proper proppant and fluid treatment designs. The importance of these fundamental principles is documented and illustrated by several case histories which demonstrate the value of achieving high conductivity fractures and the effects of improper design. This paper should be of great value to completion and operations engineers to help further their knowledge with regard to the importance of fracture conductivity and connectivity in all hydraulic fracturing applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.013 |
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".