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Record W2584545177 · doi:10.2118/0716-0080-jpt

Production Performance in the In-Fill Development of Unconventional Resources

2016· article· en· W2584545177 on OpenAlexaboutno aff
Chris Carpenter

Bibliographic record

VenueJournal of Petroleum Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPetrophysicsEagleComputer scienceWorkoverReservoir simulationGeomechanicsSystems Modeling LanguageDrillingPetroleum engineeringOperations researchGeologyEngineeringPaleontologyMechanical engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 175963, “Production Performance in the In-Fill Development of Unconventional Resources,” by Bilu V. Cherian, Sanjel; Matthew McCleary, Samuel Fluckiger, Nathan Nieswiadomy, Brent Bundy, and Sarah Edwards, SPE, SM Energy; and Rafif Rifia, Kristina Kublik, Santhosh Narasimhan, James Gray, Olubiyi Olaoye, and Hamza Shaikh, Sanjel, prepared for the 2015 SPE/CSUR Unconventional Resources Conference, Calgary, 20–22 October. The paper has not been peer reviewed. Data now show that the behavior of unconventional wells to in-fill drilling varies significantly across basins. A key influence may be changes in pore pressure and saturation (saturation history). This paper presents results from the analysis of the effect of in-fill drilling on parent-well performance, and describes a simplistic approach to understanding the effect of the quest for operational efficiencies and economic cycles on development strategies. Methodology This study focuses on two unconventional plays, the Eagle Ford and the Bakken. The objective was to model the well performance of the parent wells with the aim of matching and predicting in-fill-well performance. Because the two assets are at two significantly different portions of the development cycle (Eagle Ford is very early in its cycle), the Bakken data set has the luxury of modeling and matching the performance of the parent and in-fill, whereas the Eagle Ford portion of this study focuses on forward modeling and optimizing in-fillwell completions. The methodologies used in this study (parent-well modeling, petrophysical models, geomechanics, fracture modeling, production modeling, and in-fillwell/ depletion modeling) are discussed in detail in the complete paper. Bakken System Parent-Well Modeling Petrophysics. The Middle Bakken member was divided into three main facies. Petrophysical evaluation indicates that average porosity and average water saturation were 8 and 50%, respectively, for the Middle Bakken. Average Klinkenberg permeability for the entire Middle Bakken is approximately 0.02 md. Mercury-injection capillary pressure curves indicate that irreducible water saturation is between 30 and 40% for rock with porosity between 1 and 7%. Residual oil is between 30 and 40%. Accordingly, the moveable fluid is low (20–40%), and hydraulic fracturing was recommended to stimulate more production. The Three Forks formation was divided into five facies. Petrophysical evaluation suggests that the upper part of the Three Forks, Facies TF 23, has oil potential. Most facies are strongly affected by calcite and dolomite diagenesis, which allows alternating porosity development in some cases. In this area, the Middle and Lower Three Forks have higher water saturation, with very-low-permeability streaks (less than 0.007 md).

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.125

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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 designObservational
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

Citations1
Published2016
Admission routes1
Has abstractyes

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