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Record W2117664127 · doi:10.2118/2007-101

After Closure Analysis in Tight Gas Reservoirs: A Case History of Pre-Fracture Injection Tests Performed in the Brassey Field

2007· article· en· W2117664127 on OpenAlexaff
Natasha Kostenuk, Richard G. Thiessen

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsTight gasClosure (psychology)Petroleum engineeringFracture (geology)GeologyField (mathematics)Geotechnical engineeringHydraulic fracturingMathematics

Abstract

fetched live from OpenAlex

Abstract The design of a fracture treatment can vary and is dependent on parameters such as formation type, formation height, reservoir pressure, porosity and flow capacity (or KH). Most of these parameters can be determined prior to the fracture stimulation relatively easily at minimal cost using well logs, static gradients, DST's, cores, etc. The exception is flow capacity. Although it can be difficult and costly to determine prior to the fracture treatment, it could be considered the most important fracture design parameter. Another consideration is whether a zone should even be completed. Without an accurate idea of the formation flow capacity, it is difficult to decide prior to fracturing the zone if it will be worth the cost of the completion. This is especially true in tight gas formations where the economics of the zone can be marginal. If a zone can be determined to be un-economic prior to the fracture treatment, then significant cost savings can be realized by aborting the treatment. After Closure Analysis (ACA) is one method of easily determining a formation's flow capacity prior to the fracture treatment at minimal cost. ACA involves pumping a small volume of fluid into the formation above fracture pressure and recording the pressure falloff that follows. The pressure data can be analyzed, and once the radial flow regime is achieved, the formation's flow capacity can be determined. If the results from ACA are to be used for making completion decisions, then the method must first be proven to be practical and reliable. This paper examines field examples of ACA used on a zone in the Deep Basin that can be considered as tight gas. The ACA was completed using a software model and then compared with the results of post fracture pressure transient analysis. This was done to determine the accuracy of the ACA. Introduction Fracture treatment designs need to be tailored to the formation being treated. Parameters such as formation type, formation height, reservoir pressure and porosity can be determined using well logs, cores, static gradients, etc. One of the most important formation parameters is the flow capacity (KH) which can be costly and time consuming to determine Although most wells are successful and produce at economic rates, others do not produce or produce at uneconomic rates. In reality, many wells are stimulated without knowing if they will be economic. As the industry develops tighter gas wells, an increasing number of wells are shown to produce at un-economic rates and volumes of gas after considerable time and money have been invested in their completion. If, prior to stimulating, it can be determined that a zone will be un-economic, the treatment can be aborted and the cost savings used to develop more economic wells. The formations flow capacity (KH) is one measure that can be used to determine a well's productivity prior to fracturing. After Closure Analysis (ACA) is a relatively easy method of determining a formation's KH prior to fracturing compared to over well tests.1

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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