Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer Flowback

The productivity of a hydraulically fractured well depends on the fracture geometry and fracture–wellbore connectivity. Unlike other fracture diagnostics techniques, flowback tracer response will be dominated only by the fractures, which are open and connected to the wellbore. Single well chemical t...

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Principais autores: Ashish Kumar, Mukul M. Sharma
Formato: Artigo
Idioma:English
Publicado em: MDPI AG 2020-10-01
coleção:Energies
Assuntos:
Acesso em linha:https://www.mdpi.com/1996-1073/13/21/5644
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author Ashish Kumar
Mukul M. Sharma
author_facet Ashish Kumar
Mukul M. Sharma
author_sort Ashish Kumar
collection DOAJ
description The productivity of a hydraulically fractured well depends on the fracture geometry and fracture–wellbore connectivity. Unlike other fracture diagnostics techniques, flowback tracer response will be dominated only by the fractures, which are open and connected to the wellbore. Single well chemical tracer field tests have been used for hydraulic fracture diagnostics to estimate the stagewise production contribution. In this study, a chemical tracer flowback analysis is presented to estimate the fraction of the created fracture area, which is open and connected to the wellbore. A geomechanics coupled fluid flow and tracer transport model is developed to analyze the impact of (a) fracture geometry, (b) fracture propagation and closure effects, and (c) fracture complexity on the tracer response curves. Tracer injection and flowback in a complex fracture network is modeled with the help of an effective model. Multiple peaks in the tracer response curves can be explained by the closure of activated natural fractures. Low tracer recovery typically observed in field tests can be explained by tracer retention due to fracture closure. In a complex fracture network, segment length and permeability are lumped to define an effective connected fracture length, a parameter that correlates with production. Neural network-based inverse modeling is performed to estimate effective connected fracture length using tracer data. A new method to analyze chemical tracer data which includes the effect of flow and geomechanics on tracer flowback is presented. The proposed approach can help in estimating the degree of connectivity between the wellbore and created hydraulic fractures.
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spelling doaj.art-ea9f501aa6ac4c78990f6a6c2fdff9ef2023-11-20T18:53:22ZengMDPI AGEnergies1996-10732020-10-011321564410.3390/en13215644Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer FlowbackAshish Kumar0Mukul M. Sharma1Department of Petroleum Engineering, The University of Texas at Austin, Austin, TX 78703, USADepartment of Petroleum Engineering, The University of Texas at Austin, Austin, TX 78703, USAThe productivity of a hydraulically fractured well depends on the fracture geometry and fracture–wellbore connectivity. Unlike other fracture diagnostics techniques, flowback tracer response will be dominated only by the fractures, which are open and connected to the wellbore. Single well chemical tracer field tests have been used for hydraulic fracture diagnostics to estimate the stagewise production contribution. In this study, a chemical tracer flowback analysis is presented to estimate the fraction of the created fracture area, which is open and connected to the wellbore. A geomechanics coupled fluid flow and tracer transport model is developed to analyze the impact of (a) fracture geometry, (b) fracture propagation and closure effects, and (c) fracture complexity on the tracer response curves. Tracer injection and flowback in a complex fracture network is modeled with the help of an effective model. Multiple peaks in the tracer response curves can be explained by the closure of activated natural fractures. Low tracer recovery typically observed in field tests can be explained by tracer retention due to fracture closure. In a complex fracture network, segment length and permeability are lumped to define an effective connected fracture length, a parameter that correlates with production. Neural network-based inverse modeling is performed to estimate effective connected fracture length using tracer data. A new method to analyze chemical tracer data which includes the effect of flow and geomechanics on tracer flowback is presented. The proposed approach can help in estimating the degree of connectivity between the wellbore and created hydraulic fractures.https://www.mdpi.com/1996-1073/13/21/5644chemical tracerhydraulic fracture diagnosticsfracture wellbore connectivity
spellingShingle Ashish Kumar
Mukul M. Sharma
Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer Flowback
Energies
chemical tracer
hydraulic fracture diagnostics
fracture wellbore connectivity
title Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer Flowback
title_full Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer Flowback
title_fullStr Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer Flowback
title_full_unstemmed Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer Flowback
title_short Diagnosing Hydraulic Fracture Geometry, Complexity, and Fracture Wellbore Connectivity Using Chemical Tracer Flowback
title_sort diagnosing hydraulic fracture geometry complexity and fracture wellbore connectivity using chemical tracer flowback
topic chemical tracer
hydraulic fracture diagnostics
fracture wellbore connectivity
url https://www.mdpi.com/1996-1073/13/21/5644
work_keys_str_mv AT ashishkumar diagnosinghydraulicfracturegeometrycomplexityandfracturewellboreconnectivityusingchemicaltracerflowback
AT mukulmsharma diagnosinghydraulicfracturegeometrycomplexityandfracturewellboreconnectivityusingchemicaltracerflowback