Delaware Basin Bone Springs. A Study of the Evolving Completion Practices to Create an Economically Successful Play
Bibliographic record
Abstract
Abstract The Bone Springs play of South East New Mexico USA is currently in full development. The play contains three pay sections, with all, two or sometimes just one pay section providing economic hydrocarbons for Operators to develop and exploit. This paper will discuss the evolution of how the play was developed by abandoning vertical wellbores, and then using horizontal wells with multi-stage fracture treatments. The paper will focus on how each hurdle was overcome to discover economically beneficial technology including: lateral azimuth; lateral length; frac fluid and proppant selection; fracture design and evaluation as well as production results for each hurdle. Further discussions will emphasize the selection of lateral landing depth and the impact of depth on propping each fracture, the evolution from perf-and-plug to selective isolation with usage of sliding sleeve technology as well as the final state-of-the art on well design for the play. All of these facets are proven to demonstrate an improved production and cash flow to generate an optimized well plan. Key learnings will be in the area of logic, the workflow to determine key anchor points from data and understanding trade-offs for less expensive yet not as rewarding technologies and practices.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".