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Record W2326077868 · doi:10.2118/176828-ms

Delaware Basin Bone Springs. A Study of the Evolving Completion Practices to Create an Economically Successful Play

2015· article· en· W2326077868 on OpenAlexaff
Lyle V. Lehman, Randy Andress, Mike Mullen, Raymond L. Johnson

Bibliographic record

VenueSPE Asia Pacific Unconventional Resources Conference and Exhibition · 2015
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsSt. Peter's Hospital
Fundersnot available
KeywordsExploitWorkflowCompletion (oil and gas wells)Production (economics)Plan (archaeology)Cash flowComputer scienceGeologyKey (lock)Petroleum engineeringMining engineeringEngineeringBusinessEconomicsFinancePaleontology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.252
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2015
Admission routes1
Has abstractyes

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