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Record W4255110532 · doi:10.2523/100226-ms

Modeling of Stress-Dependent Hydraulic Fracturing in a Dynamic Flow Simulation

2006· article· en· W4255110532 on OpenAlexaff
Axel Kaselow, Leonhard Ganzer

Bibliographic record

VenueProceedings of SPE EUROPEC/EAGE Annual Conference and Exhibition · 2006
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsCitationExhibitionHydraulic fracturingGeologyWork flowComputer scienceMining engineeringPetroleum engineeringEngineeringArchaeologyLibrary scienceGeography

Abstract

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Modeling of Stress-Dependent Hydraulic Fracturing in a Dynamic Flow Simulation Axel Kaselow; Axel Kaselow Seismic Micro-Technology, Inc. Search for other works by this author on: This Site Google Scholar Leonhard Ganzer Leonhard Ganzer SMT Alps Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Europec/EAGE Annual Conference and Exhibition, Vienna, Austria, June 2006. Paper Number: SPE-100226-MS https://doi.org/10.2118/100226-MS Published: June 12 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Kaselow, Axel, and Leonhard Ganzer. "Modeling of Stress-Dependent Hydraulic Fracturing in a Dynamic Flow Simulation." Paper presented at the SPE Europec/EAGE Annual Conference and Exhibition, Vienna, Austria, June 2006. doi: https://doi.org/10.2118/100226-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Europec featured at EAGE Conference and Exhibition Search Advanced Search AbstractIn this work we present a new approach to include the influence of hydraulically induced fractures on the performance of a reservoir. Hydraulic fracturing has become a state-or-the-art completion for all kinds of wells and reservoirs. Especially in the case of low permeable tight gas reservoirs, fracturing is essential for efficient reservoir exploitation. As a result of this, most gas wells are nowadays hydraulically stimulated. However, in the case of low permeable tight gas reservoirs with rather long fractures an appropriate simulation requires a highly-flexible time-dependent adaptive gridding of the model in the vicinity of the created fracture.Our work is based on a recently proposed simulation method which combines a dual continuum approach with a time-dependent highly flexible gridding method in order to accurately simulate the influence of hydraulic fracturing on well and reservoir performance. We extend this method by treating the process of hydraulic fracturing as a part of the simulation. At any given time during the simulation a hydraulic fracture can be initiated for any desired well. The geometry of the fracture is inferred from a given state of stress, injection rate, and elastic rock properties using the Perkins-Kern-Nordgren model. Once the fracture is created the simulation grid is appropriately adopted.We have implemented our approach in a commercial reservoir simulator which provides the necessary gridding flexibility and a dual continuum formulation that allows for the definition of locally restricted dual porosity or dual permeability cells. We will show how the accuracy and flexibility of our method enhances the ability to simulate the performance of a reservoir fracture treatment.IntroductionHydraulic fracturing has become a widely accepted and frequently applied tool for enhancing the productivity of reservoirs. Of special interest is the stimulation of tight gas reservoirs. By 1993 almost 70 percent of new gas and 40 percent of new oil wells in North America are stimulated using hydraulic fracturing (Economides et al.,[1] 2002).Due to the remarkable economical role of fracture treatments especially in low permeability reservoirs the necessity to estimate the post-treatment productivity of a reservoir by means of field scale reservoir simulation arose. One way to include hydraulic fractures in a simulation model is to tune the corresponding well properties, e.g., in terms of the skin factor. Another conventional approach models the fracture as a channel of enhanced permeability and/or porosity. Haddad and Sonrexa[2] (1991) use a double-porosity formulation to simulate artificially induced fractures.In this paper we focus on the simulation of the influence of hydraulic fracture treatments in tight gas reservoirs on the reservoir scale. In such reservoirs, treatments are usually aiming at creating long and narrow fractures, which are most appropriately described in terms of the Perkins-Kern-Nordgren (PKN) fracturing model.[3,4]This paper succeeds a recent publication by Ganzer and Kiraly[5] (2005). They showed the efficient and accurate simulation of hydraulic fractures on the field scale by the used simulator. The simulator applies a dual-continuum approach where the fracture cells are only locally defined at the specific well locations without changing the underlying basic grid elsewhere. This is enabled through the usage of a highly flexible unstructured grid. In addition, the basic grid modifications at the well location are treated in a time dependent manner, which means, they become active only when the treatment is actually performed during the simulation. Our paper extends the work from Ganzer and Kiraly[5] by adding a simple, straightforward fracture design tool with automatic grid adjustment. Moreover, it is important to note that our approach is designed to include hydraulic fractures in a field scale reservoir simulation model for pre- and post-treatment productivity analysis. Thus, the approach handles the fracture creation as an instantaneous process with a static result: the fracture. Thus, dynamic aspects of fracture growth and initial closure after treatment end are neglected.Perkins-Kern-Nordgren (PKN) ModelThe PKN model (Perkins and Kern,[3] 1961; Nordgren,[4] 1972) is a well established formalism to describe hydraulic fractures. The fundamentals of the model are described in detail in Economides and Nolte[6] and Economides et al.[1] In the following we will give a brief summary of those aspects of the PKN model which are most relevant for our work. Keywords: hydraulic fracturing, orientation, flow simulation, fracture half-length, flow in porous media, grid domain, correspond, porosity, Upstream Oil & Gas, fracture grid Subjects: Hydraulic Fracturing, Reservoir Fluid Dynamics, Flow in porous media This content is only available via PDF. 2006. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.714

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 communication0.0000.001
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 head0.008
GPT teacher head0.216
Teacher spread0.207 · 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".

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