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Record W2923190916 · doi:10.2118/0419-0027-jpt

To Solve Frac Hits, Unconventional Engineering Must Revolve Around Them

2019· article· en· W2923190916 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Petroleum Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsOil shaleHydraulic fracturingDrillingEngineeringSession (web analytics)Order (exchange)BusinessMining engineeringGeologyPetroleum engineeringFinanceAdvertisingMechanical engineering

Abstract

fetched live from OpenAlex

Hydraulic fracturing as it is now executed in North American shale plays may have to be replaced with a much more intricate scheme—one that better matches the complex fabric of tight reservoirs. The impetus for an engineering overhaul is being forced by the prevalent well-to-well fracture interactions known as frac hits. These events are the subject of intensifying study by US and Canadian shale producers that have attributed them to lowering oil recovery factors from new child wells by 20–40% while inflicting even higher losses on older, yet less productive, parent wells. How the industry manages the impact of frac hits going forward is likely to define its future growth rate. “They’re not going away—we’re only going to be drilling more and more child wells,” said Brendan Elliot, a senior completions engineer with Devon Energy, as he advised a large gathering of petrotechnical colleagues that they need to “quantify the risk” of frac hits as early as possible in order to know what to do next. Elliot provided a rare look into how a large shale operator is dealing with the problem during the opening session of SPE’s Hydraulic Fracturing Technology Conference (HFTC) held recently in The Woodlands, Texas. His outline highlighted the extent to which the Oklahoma City-based producer is revolving its infill development programs around frac hits. “The things you really want to look at are where the positive and negative events are occurring,” he explained while showing an analysis program that Devon has spent the past couple of years building to visualize those outcomes. The tool, which analyzes data from more than 2,000 frac hit events, has led the company to realize that what determines whether a frac hit will benefit or hurt production comes down to time and production volumes. While this relationship was not a new learning, Devon has quantified it to 10 months and 100,000 bbl. Once both limits have been surpassed, the expectation is that frac hits will have negative consequences on pad production. Elliot elaborated on how this trend is acted upon using the company’s three-pronged approach. Its component pieces include the design of infill wells, addressing reservoir depletion through pressure management (e.g., repressurizing tactics), and then zooming out to adjust the wider field development program. The sum of these parts is a new playbook for unconventional completions, one that stands in stark contrast to the “cookie cutter” designs that gave rise to the shale revolution. Its methodical approach to decision making is aimed at gaining control over fracture growth and maximizing production from child wells. This can be done by adjusting fluid rates in a single well scenario, or altering an entire field development plan based on the risk that frac hits pose. In just a few slides, Elliot succinctly linked together years of accumulated knowledge into a workflow that could feasibly be replicated by other companies struggling with the sector’s most pressing reservoir management issue. “These full-life cycle workflows—don’t get me wrong—these will be lengthy processes, and large projects, so we need to improve as an industry,” cautioned Elliot. “Every mitigation strategy has a risk, it’s going to be specific to each reservoir, it’s going to be variable in the black oil window and your volatile gas window, and you really must cater to the asset value and the value to protect [the resource] in place.”

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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 score0.653
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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